Multi-rotor unmanned aerial vehicle with vector-composite layout and energy management and control method

Abstract

This invention relates to a vector-hybrid multi-rotor unmanned aerial vehicle (UAV) and its energy management and control method, belonging to the field of UAV technology. It includes: main rotor power systems and thrust vectoring power systems mounted on the left and right wings of the fuselage; a vertical tail on the rear of the fuselage; main rotor power systems mounted aft and forward on the wings; and thrust vectoring power systems mounted on the outer ends of the wings. It adopts a controlless design. The main rotors of the main rotor power systems directly generate pitch and roll control torques using a differential lift control mechanism. The thrust vectoring power system provides vector thrust through differential tilt, forming a redundant control system of "four rotors + thrust vectoring". Combined with a full-cycle intelligent energy dynamic optimization and control system, it achieves a minimalist configuration and ultra-high reliability, breakthrough energy efficiency and balanced performance across all operating conditions, intelligent integrated control, and strong anti-interference capabilities.

Description

Technical Field

[0001] This invention relates to multi-rotor unmanned aerial vehicles (UAVs) and energy management and control methods, belonging to the field of UAV technology. Background Technology

[0002] The inherent contradictions between traditional multi-rotor and vertical takeoff and landing fixed-wing (compound) systems in terms of energy management and control methods directly motivated the development of this vector rotor hybrid layout UAV. This contradiction manifests in multiple technical dimensions, causing existing platforms to experience performance gaps in the specific scenario of "medium-low speed long endurance + efficient hovering".

[0003] The fundamental limitation of traditional multirotors lies in the inherent conflict between their one-dimensional dependence on energy conversion efficiency and the flight state. Their energy management logic relies entirely on lift generated by rotor slipstream. While the control method achieves pitch, roll, and yaw through differential rotation speed, which is simple, direct, and has a high bandwidth, the cost is a severe imbalance in flight performance. When mission requirements exceed conventional speeds (typically >10 m / s), the airframe must fly forward at a large angle of tilt, causing a sharp increase in drag with respect to the square of speed, leading to a simultaneous deterioration in induced drag. This results in the rotor needing to continuously consume high power to maintain altitude and forward flight. Typically, a 5kg-class multirotor's range drops drastically to less than 15 minutes at a cruise speed of 20 m / s, only 60% of its hovering range, exhibiting an unacceptable non-linear decline in energy efficiency. Even more problematic is the inherent flaw in the yaw control mechanism—traditional multirotors can only generate yaw torque through anti-torque differential. This torque is small in magnitude and slow in response. In situations requiring precise pointing during hovering in windy conditions or high-speed forward flight, insufficient control effectiveness severely restricts mission performance. This "speed-time-control" paradox means that although multi-rotor aircraft can hover for 20-25 minutes, they are unable to undertake efficient surveying and mapping over a range of tens of kilometers.

[0004] The attempt to integrate the aerodynamic efficiency of fixed wings by compound wings has introduced new contradictions between the complexity of control systems and the economy under all operating conditions. Its energy management is completely separated between hovering and cruise states: during vertical takeoff and landing, it relies on an independent lift rotor, and due to the need to retain dead weight such as the propeller and control surfaces, hovering time is only 8-12 minutes, with efficiency more than 30% lower than multi-rotor aircraft; during cruise, although the wing provides the main lift, its control method must coordinate at least four sets of servo linkages involving the ailerons, elevators, and rudder, forming a multi-actuator coupling with the lift rotor and propeller. This "hybrid power layout" control architecture not only increases structural weight by 5-8% and introduces multiple points of failure, but more importantly, the low-to-medium speed range of 15-20 m / s is precisely the most commonly used economical speed for industrial inspections. Because the compound wing is below the stall limit, it cannot fly efficiently using only the wing; it must simultaneously activate three systems: lift rotor trim, control surfaces, and propeller propulsion. This drastically increases the complexity of control coordination, and prevents it from operating within the optimal energy consumption range of any subsystem. Compound airfoils are not economical at this speed range. Their system complexity does not translate into all-condition advantages, but rather into segmented performance distortion: acceptable at high speeds, awkward at medium and low speeds, and weak at hovering. In addition, the control bandwidth during vertical takeoff is weaker than that of pure multi-rotor airfoils due to control surface failure and reliance solely on rotor differential control, thus limiting wind resistance.

[0005] The fundamental contradiction between these two technologies lies in the mismatch between their configuration genes and mission requirements, creating a "valley of death" in the 15-20 m / s speed range. The "all-rotor" gene of multirotors predisposes them to high-speed inefficiency, while the "fixed-wing+" gene of compound wings results in low-speed complexity. The former cannot utilize aerodynamic lift to reduce load, while the latter cannot escape the weight increase from mechanical control surfaces; the former lacks yaw moment, while the latter has low hovering efficiency. This dual deficiency forces existing technologies to either sacrifice range (multirotors), or hovering capability (compound wings), or fail to achieve economic returns in the mid-speed range at the cost of structural complexity (compound wings). The current market gap lies precisely here: multirotors have short flight times and slow speeds, while compound / tilt rotors have weak hovering, complex mode switching, and high costs, whereas 15-20 m / s cruising combined with efficient hovering is precisely the core requirement for tasks such as power line inspection and pipeline maintenance.

[0006] The prior art, disclosed in US12491993B2, is an electric VTOL aircraft with tilt propellers and lift propellers. Its technical solution discloses a drone with a six-rotor structure, specifically two lift rotors and four tilt rotors, four of which are located on the front and rear sides between the two wings. This design results in a reduced lever arm and the use of more tilting mechanisms, which affects efficiency. The invention, disclosed in CN120065758B, entitled "An Adaptive Control Method and Computing Device for an Aircraft," reveals a method for determining the actual and simulated aircraft states corresponding to the current control cycle. The actual aircraft state is determined using onboard sensors, while the simulated aircraft state is determined using a reference model. An adaptive controller is used to determine the control target compensation amount for the current control cycle based on the difference between the actual and simulated aircraft states. Based on the control target compensation amount and the initial control target for the current control cycle, a corrected control target is determined. An inner-loop controller controls the aircraft based on the corrected control target and the actual aircraft state. The reference model is then used to simulate the aircraft state for the next control cycle based on the corrected control target and the simulated aircraft state. This method can provide precise control commands under conditions of large control envelope and strong coupling, improving the aircraft's anti-interference capability. However, it does not disclose how to optimize the overall energy management of the aircraft.

[0007] Therefore, there is an urgent need to propose a vector-composite configuration for multi-rotor UAVs and energy management and control methods to solve the above-mentioned technical problems. Summary of the Invention

[0008] To address the aforementioned problems, a vector-composite configuration multirotor unmanned aerial vehicle (UAV) and its energy management and control method are provided. A brief overview of the invention is given below to provide a basic understanding of certain aspects of the invention. It should be understood that this overview is not an exhaustive summary of the invention. It is not intended to identify key or essential parts of the invention, nor is it intended to limit the scope of the invention.

[0009] The technical solution of this invention:

[0010] The vector-composite layout multi-rotor UAV includes: main rotor power systems and thrust vector power systems installed on the wings on both sides of the fuselage; a vertical tail on the rear side of the fuselage; main rotor power systems installed on the wings in a forward and backward arrangement; and thrust vector power systems installed on the outer ends of the wings.

[0011] The main rotor of the main rotor power system uses a differential lift control mechanism to directly generate pitch and roll control torques. By adjusting the speed distribution ratio of the diagonal rotors, the attitude control of the airframe is achieved.

[0012] A method for energy management and control of a multi-rotor UAV with a vector-composite configuration, based on the aforementioned multi-rotor UAV with a vector-composite configuration, includes the following steps:

[0013] Configuration design: Through the unified design of rudderless design and power redundancy and the unified design of aerodynamic-propulsion coupled energy management architecture, the two work together to realize the hardware configuration, and the configuration design supports the software framework;

[0014] Software framework: Through the deep integration of the full-cycle intelligent energy dynamic optimization system and the MRAC-ADRC integrated intelligent control system, the two work together to support the performance of the flight platform.

[0015] Preferred design: A unified design of rudderless operation and power redundancy includes:

[0016] The main rotor power system and thrust vectoring power system are installed on the wings on both sides of the fuselage. The fuselage has a vertical tail at the rear. The main rotor power systems are installed on the wings, which are arranged in front and behind. The thrust vectoring power system is installed on the outer end of the wings.

[0017] The main rotor of the main rotor power system adopts a differential lift control mechanism to directly generate pitch and roll control torques. By adjusting the speed distribution ratio of the diagonal rotors, the attitude control of the airframe is achieved.

[0018] The tilt servo of the thrust vectoring power system adopts a direct-drive topology, and the auxiliary rotor of the thrust vectoring power system tilts.

[0019] Preferred: Aerodynamic-propulsion coupled energy management architecture includes:

[0020] Select the appropriate flight mode through flight mode decision;

[0021] By controlling the distribution, commands are sent to the main rotor power system and / or thrust vectoring power system to control the rotor speed and tilt angle;

[0022] This reduces the load on the main rotor and adjusts the direction by tilting the auxiliary rotor.

[0023] Preferred flight modes include: hexacopter low-speed mode, transitional flight mode, and quadcopter + vector cruise mode. The different control methods corresponding to the above modes in sequence include differential tilt, one-time / gradual tilt, and thrust vector deflection.

[0024] Preferred configuration: The six-rotor mode is used in the vertical take-off and landing phase and hovering / low-speed operation scenarios. The tilt servos of the two thrust vectoring power systems are controlled to form a six-rotor layout.

[0025] The transition flight mode is applied during the tilt flight phase. This mode employs two methods to complete the transition:

[0026] Method 1, One-time tilt transition: After reaching the critical tilt speed through flight in six-rotor mode, the tilt servo of the thrust vector power system is directly controlled at a tilt angle of about 0 degrees.

[0027] Method 2, Gradual Tilting: The tilting motor angle of the thrust vector power system is calculated based on the MRAC-ADRC intelligent control system. As the speed increases, the thrust vector power system gradually tilts to about 0 degrees.

[0028] The quadcopter + vector cruise mode is applied during the cruise flight phase. In this mode, the tilt servos of the two thrust vector propulsion systems will be controlled at a tilt angle of about 0 degrees, forming a vector-composite layout of quadcopter + vector propulsion. While providing the main thrust for forward flight, the auxiliary rotor generates auxiliary pitch / roll torque through vector deflection, forming a redundant trim system of "quadcopter + thrust vector".

[0029] Preferred: The MRAC-ADRC integrated intelligent control system includes:

[0030] The MRAC module includes:

[0031] Main controller: Outputs signals after receiving the desired command;

[0032] Control distribution module: converts the signals output by the main controller into the output of the machine body;

[0033] Adaptive law design: Based on the output error between the reference model and the actual machine system, the main controller parameters are dynamically adjusted to enable the actual machine to track the performance of the reference model;

[0034] The ADRC module performs real-time online estimation of the total disturbance through ESO. This observer constructs a state-space extended model based on the system input and output data, observes the disturbance as an extended state, and designs an appropriate observation bandwidth to balance noise suppression and dynamic tracking capabilities. It can achieve disturbance feedforward compensation without relying on an accurate aerodynamic parameter model. At the same time, the outer control loop introduces the MRAC reference model, selects a second-order ideal system as the reference model, selects an appropriate natural frequency and damping ratio, and designs an adaptive law to adjust the control gain online through Lyapunov stability theory, forcing the actual state error to converge asymptotically.

[0035] Preferred: The full-cycle intelligent energy dynamic optimization system is built on the basis of the MRAC-ADRC fusion control system, including:

[0036] Intelligent mission planning: Receives input information; performs optimal flight profile planning based on a digital twin model;

[0037] Real-time energy optimization: Combining the MRAC-ADRC fusion control system, it realizes the switching of flight modes and converts control commands into action commands;

[0038] Execution layer energy efficiency optimization: Based on the unified design of rudderless surface and power redundancy, the command is further optimized by the energy management architecture of aerodynamic-propulsion coupling to realize the control of the tilt servo's rotation angle and the speed of the power motor.

[0039] Preferred: In intelligent task planning, the input information includes route information, inspection point distribution, weather information, and battery status information.

[0040] The present invention has the following beneficial effects:

[0041] 1. Minimalist design and ultra-high reliability

[0042] The vector-composite layout multi-rotor UAV provided by this invention adopts a "rudderless + thrust vector" design, which simplifies the traditional compound wing's 9 execution units to 6 rotors + 2 tilt servos, reducing weight by 5-8% and eliminating the risk of mechanical failure of the rudder. The redundant architecture of the six power units supports reconfiguration control within 50ms after a single motor failure, maintaining attitude controllability and safe return within the full speed envelope, breaking through the bottleneck of single-point failure of quadcopters.

[0043] This invention employs a layout of four lifting rotors and two tiltrotor rotors, with the two tiltrotor rotors located at the tips of the two wings. This location maximizes the lever arm of yaw and roll moments, resulting in higher efficiency, while also utilizing fewer tilting mechanisms. It adopts a controlless design, meaning it lacks ailerons, flaps, rudders, and a horizontal stabilizer, as the overall configuration is designed for a cruise speed range of 15-20 m / s, where control surfaces would be extremely inefficient. The use of fewer mechanisms leads to weight reduction and improved reliability, reduced mechanical complexity, lower maintenance costs, and fewer potential failure points. A corresponding intelligent energy management method is included, enabling efficient energy management and control allocation for this configuration. Further optimization of commands is possible based on the unified design of the controlless design and power redundancy, and the aerodynamic-propulsion coupled energy management architecture.

[0044] 2. Breakthrough in energy efficiency and balanced performance across all operating conditions

[0045] This invention utilizes aerodynamic-propulsion coupled energy management to achieve 30-40% lift from the wing and low-power operation of the main rotor during cruise at 20 m / s, resulting in a pure electric flight time of up to 40 minutes. During hovering, the six-rotor configuration is over 30% more efficient than a compound rotor, with a hovering time of 20 minutes. It precisely targets the core speed range of 15-20 m / s for industrial inspection, bridging the performance gap between traditional multi-rotor aircraft (short endurance) and compound rotor aircraft (weak hovering).

[0046] 3. Intelligent integrated control and strong anti-interference capability

[0047] The vector-composite layout multirotor UAV and energy management and control method provided by this invention improves the anti-disturbance capability by more than 2 times and the pitch angle response overshoot is less than 5%; the cross tilt yaw technology completely solves the pain point of slow yaw response of traditional multirotors; the full-cycle energy dynamic optimization reduces the total energy consumption by 5-8% through mission planning and realizes the closed-loop management of "prediction-feedback-optimization-execution";

[0048] This invention employs a hierarchical intelligent energy dynamic optimization system. The main difference in the control layer is the adoption of a deeply coupled architecture of Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC). An ADRC module is added on the basis of the inner-loop MRAC for feedforward disturbance compensation. The MRAC module itself only changes the parameters of the main controller. The architecture and logic of the control layer are completely different from existing technologies. The control layer of this invention is more complex, but it can dynamically adjust the control rate according to the configuration and dynamically compensate for disturbances. At the same time, in conjunction with the full-cycle intelligent energy dynamic optimization system, it can achieve optimal energy management for the whole machine for more task objectives. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of a multi-rotor UAV with a vector-composite configuration;

[0050] Figure 2 This is a block diagram of intelligent energy management and control for a multi-rotor UAV with a vector-composite layout;

[0051] Figure 3 It is a unified design drawing for rudderless design and power redundancy;

[0052] Figure 4 This is a diagram of an energy management architecture that combines aerodynamics and propulsion.

[0053] Figure 5 This is a schematic diagram of the low-speed mode of the six-rotor aircraft;

[0054] Figure 6 This is a schematic diagram of a quadcopter with vector cruise mode;

[0055] Figure 7 This is a diagram of an intelligent control system that integrates MRAC and ADRC;

[0056] Figure 8 It is a diagram of a full-cycle intelligent energy dynamic optimization system. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention is described below with reference to specific embodiments shown in the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0058] Specific implementation method one: Combining Figure 1-8 This embodiment describes a multi-rotor UAV with a vector-composite layout. The main rotor power system 1 and the thrust vector power system 2 are symmetrically installed on the wings on the left and right sides of the fuselage, respectively. The fuselage has a vertical tail 3 on the rear side. The vertical tail adopts a small-area V-shaped design. The main rotor power system 1 is symmetrically arranged on each wing 4, and the thrust vector power system 2 is installed on the outer end of each wing 4.

[0059] The main rotor of the main rotor power system uses a differential lift control mechanism to directly generate pitch and roll control torques. By precisely adjusting the speed distribution ratio of the diagonal rotors, it achieves three-axis full-authority control of the aircraft attitude; the main rotor is located on the horizontal plane.

[0060] This invention employs a layout of four lifting rotors and two tilt rotors, with the two tilt rotors located at the tips of the two wings. This location has the largest lever arm for yaw and roll moments, resulting in higher efficiency, while also using fewer tilting mechanisms. It utilizes a control-free design, meaning no ailerons or flaps, no rudder, and no horizontal stabilizer. Because the overall configuration is designed for a cruise speed range of 15-20 m / s, control surface efficiency is extremely low. The use of fewer mechanisms further reduces weight and improves reliability, decreases mechanical complexity, lowers maintenance costs, and reduces potential failure points.

[0061] Specific Implementation Method Two: Combining Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite configuration, including:

[0062] Flight platform configuration design: Through the unified design of controlless surface and power redundancy and the unified design of aerodynamic-propulsion coupled energy management architecture, the two (the unified design of controlless surface and power redundancy and the aerodynamic-propulsion coupled energy management architecture) work together to realize the hardware configuration, and the configuration design supports the software algorithm framework.

[0063] Flight platform software framework: Through the deep integration of the full-cycle intelligent energy dynamic optimization system and the MRAC-ADRC integrated intelligent control system, the two (the full-cycle intelligent energy dynamic optimization system and the MRAC-ADRC integrated intelligent control system) work together with software algorithms to support the performance of the flight platform;

[0064] This invention addresses the inherent contradictions in energy management and control methods between traditional multi-rotor and compound-wing UAVs (i.e., traditional multi-rotor UAVs suffer from low cruise efficiency and slow cruise speed, while compound-wing UAVs exhibit low hovering efficiency and poor reliability). It proposes a vector-compound layout multi-rotor UAV and an intelligent energy management and control method. Through an innovative "aerodynamic-propulsion coupling" design, the wings share most of the lift during the cruise phase, allowing the main rotor to operate with low power consumption. This specifically optimizes the energy efficiency gap of the traditional configuration at 15-20 m / s, achieving a balance between hovering and cruise efficiency. Furthermore, through a "control surface-free design" and "thrust vector redundancy," the lift differential of the main quadcopter replaces all traditional control surfaces, significantly simplifying the mechanical structure and improving reliability. Simultaneously, the tilt rotors at the wingtips provide vector thrust at high speeds to enhance control, and vertically form a six-rotor layout at low speeds to improve control torque. Combined with cross-tilt yaw control technology, this completely solves the problem of slow yaw response in traditional multi-rotor UAVs. This design, which integrates the agile control of multi-rotors with the efficient cruise of fixed-wing aircraft through system integration and simplification, ultimately creates a flight platform that combines high energy efficiency, high reliability, and strong anti-interference capabilities within a specific performance range.

[0065] Specific implementation method three: Combining Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. The unified design of controlless surface and power redundancy includes:

[0066] The main rotor power system and thrust vectoring power system are symmetrically mounted on the wings on both sides of the fuselage. The fuselage has a vertical tail with a small-area V-shaped design. Each wing is equipped with a main rotor power system symmetrically arranged front and rear, and a thrust vectoring power system is installed at the outer end of each wing.

[0067] The main rotor of the main rotor power system uses a differential lift control mechanism to directly generate pitch and roll control torques. By precisely adjusting the speed distribution ratio of the diagonal rotors, it achieves three-axis full-authority control of the aircraft attitude; the main rotor is located on the horizontal plane.

[0068] The output shaft of the tilt servo of the thrust vectoring power system is coaxially fixed to the rotor nacelle, adopting a direct-drive topology. The auxiliary rotor of the thrust vectoring power system can tilt differentially and act as an aileron control surface during high-speed forward flight. A tilt servo is set at the wingtip, and the output end of the tilt servo is connected to the drive motor of the auxiliary rotor. During the tilting process, the position of the auxiliary rotor can be adjusted from any position on the path from the vertical plane to the horizontal plane, thus achieving pitch adjustment.

[0069] The entire aircraft follows the minimalist actuator concept of "no control surfaces + thrust vectoring," simplifying the nine actuators (4 rotors + 4 control surfaces + 1 propeller) of the traditional compound wing to six rotors + two tilt servos. The main quadcopter achieves pitch and roll control through lift differential, completely eliminating the mechanical complexity of the servo-linkage mechanism, reducing weight by 5-8% while eliminating the risk of control surface jamming. The tilt servos directly drive the rotor nacelles without the need for additional transmission mechanisms, further improving reliability. The system has six redundant power units. If any motor fails, the flight control can immediately reconfigure the control allocation matrix and switch to the remaining five-rotor or four-rotor mode to maintain attitude control and safe return. This capability is effective in both high-speed forward flight and hovering, significantly surpassing the single-point failure bottleneck of traditional quadcopters.

[0070] Specific implementation method four: Combination Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. The flight control system regulates the main rotor motor and auxiliary rotor motor of the thrust vector power system, and independently regulates the tilt servo. The flight control system is used for fault diagnosis and health assessment, instantaneously calculates and reconstructs the control allocation matrix of the rotor degradation mode, and ensures the controllability of the airframe attitude and safe return capability by dynamically adjusting the speed limits and torque distribution weights of the remaining motors.

[0071] like Figure 7 , 8 As shown, the flight control system refers to Figure 7 and Figure 8 The algorithm represents a full-cycle intelligent energy dynamic optimization system and an intelligent control system integrating Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC); it can use any open-source flight controller, as long as it implements... Figure 7 and Figure 8 The relevant algorithms are sufficient;

[0072] The vector-vector multi-rotor UAV adopts a rudderless design, consisting of a fuselage (5), wings (4), vertical tail (3), four main rotor power systems (1), and two thrust vectoring power systems (2). Each main rotor power system includes a drive motor, rotor, and connecting mechanism. Each thrust vectoring power system includes a tilt motor, rotor, drive motor, and connecting mechanism. The four main rotor power systems are symmetrically mounted at the front and rear of the two wings. The two thrust vectoring power systems are symmetrically mounted at the wingtips of the outermost ends of the two wings. In the thrust vectoring power system, the rotor is directly driven by the drive motor, which is connected to the tilt motor through the connecting mechanism and controlled by it to achieve tilting. The flight control system independently regulates the two motors to coordinate the rotation and tilting movements of the rotor.

[0073] This vector-composite layout multi-rotor UAV and intelligent energy management and control technology solution achieves a breakthrough in dynamic energy allocation and robust control under all operating conditions through systematic integration of configuration innovation, algorithm fusion and mode optimization.

[0074] Specific Implementation Method Five: Combining Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. The aerodynamic-propulsion coupled energy management architecture includes:

[0075] Select the appropriate flight mode through flight mode decision;

[0076] By controlling the distribution, commands are sent to the main rotor power system and / or thrust vectoring power system to achieve control of the corresponding rotor speed and tilt angle;

[0077] The goal is to reduce the load on the main rotor and adjust the direction by tilting the auxiliary rotor, thereby achieving the optimization objectives of unloading the main rotor from tilting, reducing drag and induced drag, and breaking through the power decoupling limitation.

[0078] The energy management architecture of this UAV breaks through the limitations of traditional power decoupling between multi-rotor and fixed-wing aircraft, establishing a "lift sharing-power optimization" mechanism based on flight state adaptation. At a typical cruise speed of 20 m / s (corresponding to a takeoff weight of 5 kg and a wingspan of 1.5 m), the aerodynamic lift of the wings accounts for 30-40% of the total weight. The main quadrotor does not need high-speed trim and switches to a low-power state to focus on fine attitude adjustment, replacing the traditional control surface function. At the same time, the tilt rotors at the wingtips provide the main thrust for forward flight and generate auxiliary pitch / roll moments through vector deflection, forming a redundant trim system of "quadrotor + thrust vector". This aerodynamic coupling design unloads and reduces the main rotor speed, and the drag and induced drag decrease simultaneously, which is the key to achieving a 40-minute long-endurance cruise on pure electric power. When switching to hovering missions, the system switches to a six-rotor vertical mode: the tilt rotors rotate 90° and face vertically upwards, forming a hexagonal layout together with the main quadrotor, and the roll control moment is increased by about 25% compared to conventional quadrotors. By optimizing the rotational speed distribution algorithm, the load on a single motor is reduced, the hovering efficiency is improved by more than 30% compared to a compound wing, and the hovering time can reach 20 minutes, perfectly balancing the energy consumption contradiction between high-speed arrival and long-term observation.

[0079] Specific Implementation Method Six: Combination Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. The flight modes include: a six-rotor low-speed mode, a transitional flight mode, and a quadcopter + vector cruise mode. The different control methods corresponding to the above modes in sequence include differential tilt, one-time / gradual tilt, and thrust vector deflection.

[0080] Specific implementation method seven: Combining Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. The six-rotor low-speed mode is mainly used in the vertical take-off and landing phase and hovering / low-speed operation scenarios. The tilt servos of the two thrust vector power systems are controlled to form a six-rotor layout.

[0081] The transition flight mode is mainly used during the tilt flight phase. This mode allows for a transition in two ways:

[0082] Method 1, One-time tilt transition: After reaching the critical tilt speed through flight in six-rotor mode, the tilt servo of the thrust vector power system is directly controlled at a tilt angle of about 0 degrees.

[0083] Method 2, Gradual Tilting: The tilting motor angle of the thrust vectoring power system is calculated based on the MRAC-ADRC intelligent control system. As the forward speed increases, the thrust vectoring power system gradually tilts to about 0 degrees.

[0084] The quadcopter + vector cruise mode is mainly used in the cruise flight phase. In this mode, the tilt servos of the two thrust vector power systems will be controlled at a tilt angle of about 0 degrees, forming a vector-composite layout of quadcopter + vector propulsion. At the same time, the auxiliary rotors at the two ends of the wing (outer tip) provide the main thrust for forward flight and generate auxiliary pitch / roll moments through vector deflection, forming a redundant trim system of "quadcopter + thrust vector".

[0085] Specific implementation method eight: Combination Figure 1-8 This embodiment describes the energy management and control method for a multi-rotor UAV with a vector-composite layout. It employs an intelligent control system that integrates Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC), combining these two methods for hybrid control. The method includes:

[0086] In the MRAC module, the desired commands are sent to the main controller for control allocation and then executed by the airframe (UAV), including:

[0087] Main controller: Outputs signals after receiving the desired instructions; the main controller can use fuzzy PID, which achieves a balance between the adaptability of fuzzy logic and the stability of PID.

[0088] Control distribution module: converts the signals output by the main controller into output execution commands for the machine body;

[0089] Adaptive law design: Based on the output error between the reference model and the actual machine system, the main controller parameters are dynamically adjusted so that the actual machine system tracks the performance of the reference model as closely as possible;

[0090] The ADRC module estimates the total disturbance in real time online through an extended state observer (ESO). This observer constructs an extended state-space model based on the system's input and output data, observing the disturbance as an extended state. A suitable observation bandwidth is designed to balance noise suppression and dynamic tracking capabilities, achieving disturbance feedforward compensation without relying on a precise aerodynamic parameter model. Simultaneously, the outer control loop introduces an MRAC reference model, selecting a second-order ideal system as the reference model. Appropriate natural frequencies and damping ratios are chosen, and an adaptive law is designed using Lyapunov stability theory to adjust the control gain online, forcing the actual state error to converge asymptotically.

[0091] To address the performance degradation of traditional cascaded PID control under strong wind disturbances and model uncertainties, this invention employs a deeply coupled architecture of Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC). This system treats external wind disturbances, airflow separation, and parameter perturbations as a unified "total disturbance," and performs real-time estimation and dynamic compensation through an Extended State Observer (ESO), achieving more than a 2x improvement in disturbance rejection capability without the need for precise modeling. The outer control loop introduces an MRAC reference model, enabling the actual state to quickly track the ideal dynamic response, maintaining multi-rotor-like self-stabilizing characteristics even in turbulent conditions. To address the inherent problem of insufficient yaw control efficiency in multi-rotors, an innovative "cross-tilt vector differential mechanism" is introduced: through differential yaw of the left and right tilting rotors (e.g., 15° forward left and 15° backward right), a highly efficient yaw torque is directly generated, significantly improving the response speed compared to the traditional speed difference method, thus solving the pain points of precise pointing in hovering and maintaining wind-resistant yaw.

[0092] Specific Implementation Method Nine: Combining Figure 1-8 This embodiment describes the energy management and control method for multi-rotor UAVs with a vector-composite layout. The full-cycle intelligent energy dynamic optimization system is constructed based on the MRAC-ADRC fusion control system, and includes:

[0093] Intelligent mission planning (intelligent mission energy planning is the top-level decision): Receives input information; performs optimal flight profile planning based on a digital twin model;

[0094] Real-time energy optimization (control layer): Combined with the MRAC-ADRC fusion control system, it realizes the switching of flight modes and converts control commands into action commands; Mode 1 is used for low-speed / hovering scenarios; Mode 2 is used for transitional flight, which is the transition state when speed changes; Mode 3 is used for high-speed cruise scenarios to reduce energy consumption.

[0095] Execution layer energy efficiency optimization (execution layer): Based on the unified design of rudderless and power redundancy and the energy management architecture of aero-propulsion coupling, the commands are further optimized to realize the control of the tilt servo angle and the speed control of the power motor (the motor that drives the rotor), so as to achieve energy saving while ensuring the accuracy of execution;

[0096] This invention achieves dynamic energy optimization throughout the entire lifecycle of hovering, cruise, and transition states through adaptive flight mode switching (six-rotor hovering—transitional forward flight—quadrotor + vector cruise), multi-algorithm fusion (MRAC-ADRC), and hardware redundancy reconfiguration. Its core breakthrough lies in precisely targeting the 15-20 m / s cruise speed range, a performance vacuum in traditional technologies due to the deterioration of multi-rotor drag and the stall limitations of compound rotors. This invention, with a balanced performance of 40 minutes of pure electric cruise and 20 minutes of hovering, coupled with double the disturbance rejection capability and full-mode power redundancy, fills the market gap between traditional multi-rotor (short endurance, slow speed) and compound / tilt rotor (weak hovering, complex mode switching, high cost), providing a simple, robust, and low-cost system-level solution for medium- and low-speed long-endurance applications of industrial-grade UAVs.

[0097] Specific Implementation Method Ten: Combining Figure 1-8 This embodiment describes a vector-composite layout multi-rotor UAV and its energy management and control method. In the intelligent mission planning, the input information includes flight path information, inspection point distribution, meteorological information, battery status, and other information about the UAV's own status, surrounding environment, and the mission being executed.

[0098] Example 1:

[0099] Combination Figure 1-8This paper presents a vector-composite multirotor UAV and its energy management and control method. The vector-composite multirotor UAV adopts a rudderless design and consists of a fuselage, wings, a vertical tail, four main rotor power systems, and two thrust vectoring power systems. Each main rotor power system includes a motor, rotor, and connecting mechanism. Each thrust vectoring power system includes a tilt motor, rotor, motor, and connecting mechanism. The four main rotor power systems are symmetrically mounted on the fore and aft sides of the two wings, corresponding to the left front, right front, left rear, and right rear quadrants, respectively, and employ a cross-tilt scheme (the tilt angle is determined through an optimization algorithm). The two thrust vectoring power systems are symmetrically mounted at the wingtips of the outermost parts of the two wings, integrated with the wing structure through connecting mechanisms. The placement at the wingtips can counteract the adverse interference of the rotor downwash on the wings, while simultaneously utilizing wingtip vortices to improve propulsion efficiency. The wingtips can tilt differentially, acting as aileron control surfaces during high-speed forward flight. In the thrust vectoring propulsion system, the rotor is directly driven by a power motor, which is connected to a tilt motor via a connecting mechanism and controlled by the tilt motor to achieve tilting. The flight control system independently regulates the two motors to coordinate the rotor's rotation and tilting movements. The entire aircraft utilizes carbon fiber tubing, aerospace-grade composite materials, and 3D-printed integrated components to achieve lightweight design. The vertical tail features a small-area V-shaped design, used only to improve directional stability and not involved in active control.

[0100] The actuators controlling the multi-rotor UAV with a vector-composite configuration include two tilt motors and six drive motors. The control parameters include: the rotation angle of the two tilt motors and the speed of the two drive motors in the two tilt motor systems, and the speed of the four drive motors in the four main rotor systems, for a total of eight control parameters, which belong to the overdrive system.

[0101] The framework of this vector-composite layout multi-rotor UAV and intelligent energy management and control method is as follows: Figure 2 Through the systematic integration of configuration innovation, algorithm fusion, and mode optimization, a breakthrough in dynamic energy efficiency allocation and robust control under all operating conditions has been achieved.

[0102] Combination Figure 1-3 The unified design of rudderless design and power redundancy shown.

[0103] This unmanned aerial vehicle system adheres to the minimalist actuator design concept of "no control surfaces + thrust vectoring" (such as...). Figure 3This paper presents a systematic reconstruction of the power-control topology of a compound-wing UAV. The redundant and complex nine execution units (four vertical takeoff and landing rotors, four sets of servo-link aerodynamic control surfaces, and one independent propeller) in the traditional scheme are streamlined and optimized into a highly integrated architecture of six efficient rotors and two high-bandwidth tilt servos, fundamentally reducing system complexity and the risk of fault propagation. Specifically, the main quadcopter uses a differential lift control mechanism to directly generate pitch and roll control torques. By precisely adjusting the diagonal rotor speed distribution ratio, it achieves three-axis full-authority control of the airframe attitude, completely eliminating the inherent mechanical backlash, nonlinear hysteresis, and aeroelastic coupling problems of traditional servo-link mechanisms. While achieving a 5-8% reduction in structural weight, it also eliminates typical mechanical fault hazards such as control surface jamming, link breakage, and hinge wear, significantly improving the system's mission reliability in harsh environments such as sandstorms and high humidity. The tilt servos at the wingtips adopt a direct-drive topology, with their output shafts coaxially fixed to the rotor nacelles. This completely eliminates intermediate links such as reduction gears and transmission belts, not only increasing the vector response bandwidth to over 10Hz but also optimizing the transmission efficiency to over 95%, further enhancing the dynamic performance and durability of the execution link. The system's six-power-unit redundant architecture endows it with excellent fault-tolerant reconfiguration capabilities: when any motor causes abnormal thrust due to winding short circuit, ESC failure, or blade damage, the flight control system can complete fault diagnosis and health assessment within 50ms, instantly calculate and reconstruct the control allocation matrix of the five-rotor or four-rotor degraded mode, and ensure the controllability of the three-axis attitude and safe return capability within the full speed envelope of 0-25m / s (covering high-speed forward flight, medium-speed cruise, and zero-speed hovering) by dynamically adjusting the speed limits and torque distribution weights of the remaining motors. This breakthrough solves the inherent bottleneck of single-point failure, i.e. instantaneous loss of control, in traditional four-rotor UAVs, and enables the system's safety level to move from probabilistic fault tolerance to deterministic redundancy, providing unprecedented reliability assurance for long-endurance industrial inspection missions.

[0104] Combination Figure 4 The aerodynamic-propulsion coupled energy management architecture shown

[0105] Vector-composite multirotor UAVs employ a highly efficient aerodynamic-propulsion coupled energy management architecture (such as...). Figure 4This study fully explores the flight performance and application potential of this unmanned aircraft configuration, breaking through the limitations of traditional power decoupling between multi-rotor and fixed-wing aircraft, and constructing a flight state-adaptive "lift sharing-power optimization" mechanism. During cruise, the wings bear 30-40% of the lift, the main quadcopter operates at low speed, and is dedicated to attitude adjustment; the wingtip tiltrotors provide the main thrust while assisting in trim through vector deflection, forming redundant control. This aerodynamic coupling significantly reduces rotor drag and induced drag. In hover mode, the tiltrotors face vertically upwards, forming a six-rotor configuration with a large rolling moment. Combined with optimized speed distribution, the hovering efficiency is more than 30% higher than that of a compound wing, effectively balancing the energy consumption contradiction between high-speed arrival and long-term observation.

[0106] Combination Figure 4 The flight modes shown for the vector-composite layout multi-rotor UAV include: hexacoach low-speed mode, transitional flight mode, and quadcopter + vector cruise mode.

[0107] Combination Figure 5 The illustrated six-rotor low-speed mode is primarily used in vertical takeoff and landing (VTOL) and hovering / low-speed operation scenarios. In this mode, the tilt motors of the two thrust vectoring power systems are controlled at a tilt angle of approximately +90 degrees, forming a six-rotor configuration, such as... Figure 5 Due to the two thrust vectoring systems deployed at the outermost wingtips, the roll control torque is increased by approximately 25% compared to conventional quadcopters. To improve yaw control efficiency in this mode, this invention proposes cross-tilt yaw control. The two thrust vectoring power systems can generate a large yaw torque through differential tilting of the tilting rotors (e.g., 15° forward left and 15° backward right), solving the problems of insufficient yaw control efficiency and slow yaw response in traditional multi-rotor UAVs. Simultaneously, through a speed optimization allocation algorithm, the load on a single motor is reduced, and hovering efficiency is improved by more than 30% compared to compound wings, with a hovering time of up to 20 minutes, perfectly balancing the energy consumption contradiction between high-speed arrival and long-term observation. Combining Model Reference Adaptive MRAC and ADRC active disturbance rejection control, wind and disturbance resistance capabilities can be further improved by more than 2 times (compared to traditional cascade PID control).

[0108] The transitional flight mode is primarily used during the tilt flight phase, and this mode can be completed in two ways. Method one is a one-time tilt transition, where after reaching the critical tilt speed through hexacopter flight, the tilt motors of the vector propulsion system are directly controlled to a tilt angle of approximately 0 degrees. Due to the powerful aerodynamic-propulsion coupling energy management architecture of the vector-composite multi-rotor UAV, this method can be directly adopted, which is convenient and quick. Method two is a gradual tilt, where the tilt motor angle of the vector propulsion system is calculated based on the MRAC-ADRC intelligent control system, and the vector propulsion system gradually tilts to approximately 0 degrees as the forward speed increases. This method results in more stable flight and consumes less energy during flight within the energy management framework.

[0109] Combination Figure 6 The quadcopter + vector cruise mode shown is mainly used during the cruise flight phase. In this mode, the tilt motors of the two thrust vector propulsion systems will be controlled at a tilt angle of approximately 0 degrees, forming a quadcopter + vector propulsion vector-composite layout, such as... Figure 6 This model breaks through the limitations of traditional power decoupling between multi-rotor and fixed-wing aircraft, establishing a "lift sharing-power optimization" mechanism based on flight state adaptation. At a typical cruise speed of 20 m / s (corresponding to a takeoff weight of 5 kg and a wingspan of 1.5 m), the aerodynamic lift of the wing accounts for 30-40% of the total weight. The main quadrotor does not require high-speed trim and switches to a low-power state to focus on fine-tuning attitude, replacing the traditional control surface function. At the same time, the tiltrotors at the wingtips provide the main thrust for forward flight and generate auxiliary pitch / roll moments through vector deflection, forming a redundant trim system of "quadrotor + thrust vector". This aerodynamic coupling design unloads and reduces the main rotor speed, and the drag and induced drag decrease simultaneously, which is the key to achieving a 40-minute long-endurance cruise on pure electric power.

[0110] Combination Figure 7 The illustrated intelligent control system integrates Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC).

[0111] Because this unmanned aircraft adopts a control surface-less design, the shortcomings of traditional cascaded PID control are amplified, such as its inability to effectively cope with wind disturbances. This solution creates a deeply coupled architecture of Model Reference Adaptive Control (MRAC) and Active Disturbance Rejection Control (ADRC), forming an intelligent control system with both strong robustness and high adaptability. The core idea of ​​this system is to unify and abstract the various disturbance factors that need to be handled separately in the traditional control framework, including external disturbances caused by time-varying wind fields, airflow separation disturbances caused by wing-rotor aerodynamic coupling, actuator gain perturbations caused by battery voltage drops, and unmodeled dynamics introduced by the elastic modes of the airframe structure, into a "total disturbance" acting on the system input channel, thereby transforming the complex uncertainty problem into a single disturbance estimation and compensation problem. Specifically, the system performs real-time online estimation of the total disturbance in each control cycle using an Extended State Observer (ESO). This observer constructs an extended state-space model based on the system's input and output data, observing the disturbance as an extended state. A suitable observation bandwidth is designed to balance noise suppression and dynamic tracking capabilities. Disturbance feedforward compensation can be achieved without relying on precise aerodynamic parameter models, improving the system's disturbance rejection capability by more than two times. Attitude angle fluctuations are suppressed to within ±3° under a 10m / s step wind disturbance. Simultaneously, an MRAC reference model is introduced into the outer control loop. A second-order ideal system is selected as the reference model, and appropriate natural frequencies and damping ratios are chosen. An adaptive law is designed using Lyapunov stability theory to adjust the control gain online, forcing the actual state error to converge asymptotically. This ensures that the aircraft maintains the self-stabilizing characteristics unique to multi-rotor platforms in turbulent environments, with pitch response overshoot controlled within 5%.

[0112] In practice, a hierarchical collaborative architecture is adopted to realize the intelligent control system integrating ADRC and MRAC, which is divided into a reference model layer, an MRAC main control layer, and an ADRC disturbance compensation layer, such as... Figure 7The system comprises several layers: The reference model layer defines an ideal trajectory tracking reference model (e.g., a second-order linear time-invariant system) to describe the UAV's desired dynamic response (e.g., position, velocity, attitude); the MRAC main control layer designs an adaptive controller (e.g., a fuzzy PID or fuzzy PD controller) to adjust control parameters based on the errors between the reference model and the actual system (e.g., tracking error, state error), ensuring the system dynamically follows the reference model; the ADRC disturbance compensation layer estimates the total disturbance of the UAV using ESO and feeds the estimated disturbance signal forward to the MRAC output to counteract the disturbance's impact on the system. The MRAC generates the basic control signal to track the reference model, while ADRC enhances the system's disturbance immunity through real-time compensation. In the dynamic allocation mechanism, the system can dynamically adjust the weights of MRAC and ADRC based on the current state (e.g., disturbance intensity or tracking error). For example, in a high-disturbance environment, the ADRC compensation ratio increases to prioritize suppressing disturbances; in a stable phase, the MRAC's tracking performance dominates. Furthermore, the construction of the information feedback closed loop further enhances robustness—the actual system output is not only fed back to the MRAC for error correction but also input into the ADRC's ESO to update the disturbance estimate, forming a dual closed-loop control. To achieve stability, the Lyapunov stability of the fusion system needs to be verified through theoretical analysis, such as constructing a composite Lyapunov function that includes tracking error and parameter error, and proving its negative definite derivative. Meanwhile, parameter constraint design (such as limiting observer bandwidth or adaptive gain) can avoid high-frequency noise amplification or parameter drift problems.

[0113] Furthermore, addressing the industry-wide challenge of insufficient yaw control efficiency inherent in multirotor aircraft, the solution overcomes the limitations of traditional differential speed control to generate counter-torque by innovatively introducing a "cross-tilt vector differential mechanism." In hovering or low-speed states, differential deflection of the tilting rotors at the left and right wingtips creates a spatial cross-thrust vector, directly generating a yaw torque perpendicular to the aircraft plane, increasing the torque coefficient by three times. This mechanism utilizes the principle of vector thrust geometric synthesis to transform the small counter-torque that originally required multi-cycle integration and accumulation into an instantaneous torque output, significantly reducing response time. This significantly improves the fine pointing accuracy and wind-resistant yaw maintenance capability in hovering states, solving the pain points of weak yaw channel control efficiency and slow response in multirotor aircraft, and providing necessary heading control quality assurance for industrial-grade precision inspection tasks.

[0114] Combination Figure 8 The full-cycle intelligent energy dynamic optimization system shown

[0115] Based on the MRAC-ADRC integrated control system, a full-cycle intelligent energy dynamic optimization system is constructed to achieve closed-loop management of energy flow from three levels: intelligent task planning, real-time energy optimization, and execution-level energy efficiency optimization. Figure 8This fully leverages the dual advantages of the aircraft configuration in hovering efficiency and cruise economy.

[0116] The core of this system is the establishment of a four-layer energy management architecture: prediction, feedback, optimization, and execution. The top layer is mission-level intelligent energy planning. Before takeoff, based on flight path distance, inspection point distribution, weather forecasts (especially wind speed and direction), and battery SOC status, a globally optimal flight profile is generated using a vector-composite layout multi-rotor UAV digital twin model. For the UAV's optimal design range, the planner calculates the best combination of altitude and speed for each flight segment: for example, appropriately increasing speed to 22 m / s in a tailwind to shorten mission time, and decreasing to 18 m / s and appropriately lowering altitude in a headwind to utilize ground effect for drag reduction in a headwind. This strategy can reduce total energy consumption by 5%-8%. Combined with aerodynamic derivatives identified online by MRAC, the planner can dynamically update the aircraft's digital twin model, ensuring its accuracy even with age, component wear, or load changes.

[0117] The middle layer is for real-time energy optimization and operates tightly coupled with the MRAC-ADRC controller. The ADRC's extended state observer provides key inputs for energy optimization while estimating aerodynamic disturbances. When persistent strong wind disturbances are observed, the optimizer actively adjusts the propulsion power distribution of the tiltrotor, prioritizing track tracking rather than strictly maintaining the 20m / s set speed to avoid continuous high-load operation of the motors. Real-time force efficiency parameters identified by the MRAC adaptive mechanism (such as the power consumption curves of the rotor at different speeds) are used to correct the energy consumption weight matrix of the control distribution layer. In cruise mode, the optimizer continuously solves for the optimal combination of rotor speed and tilt angle, enabling the main quadrotor to reduce speed as much as possible to minimize drag power consumption while providing just enough attitude control torque, and transferring more thrust demand to the more efficient tiltrotor, which can extend the cruise time by an additional 8%-10%.

[0118] The underlying layer optimizes energy efficiency at the execution level, focusing on minimizing energy consumption through control allocation strategies. In hover mode, although the six-rotor configuration provides an additional 25% roll torque, the optimizer actively allocates commands to the eight actuators (six motors + two servos) to ensure each motor operates within its optimal efficiency range (typically 60%-80% of its rated speed). It also replaces the traditional multi-rotor speed difference yaw with differential yaw control using tilt rotors, reducing additional power consumption caused by yaw maneuvers. In cruise mode, the optimizer utilizes redundancy to implement health-aware energy efficiency management: when it detects aging or decreased efficiency in a motor, it automatically reduces its load weight and transfers the task to other healthy motors. This ensures total thrust requirements are met while preventing inefficient motors from dragging down overall energy consumption and extending the single-flight limit.

[0119] The deep integration of this energy optimization system with MRAC-ADRC is reflected in data sharing and goal alignment: the control layer provides accurate state prediction and disturbance estimation, and the optimization layer adjusts the energy consumption strategy accordingly; the economic setpoints generated by the optimization layer (such as optimal speed and tilt angle) are input into the control layer as reference commands, forming a dual feedback.

[0120] It should be noted that in the above embodiments, as long as the technical solutions are not contradictory, they can be permuted and combined. Those skilled in the art can exhaust all possibilities based on the mathematical knowledge of permutation and combination. Therefore, the present invention will not describe the technical solutions after permutation and combination one by one, but it should be understood that the technical solutions after permutation and combination have been disclosed by the present invention.

[0121] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for energy management and control of a multi-copter unmanned aerial vehicle in a vector-complex layout, characterized by: The vector-composite layout of the multi-rotor UAV includes: main rotor power system and thrust vector power system installed on the wings on the left and right sides of the fuselage, vertical tail on the rear side of the fuselage, main rotor power system installed on the wings arranged in front and behind, and thrust vector power system installed on the outer end of the wings. The main rotor of the main rotor power system adopts a differential lift control mechanism to directly generate pitch and roll control torques. By adjusting the speed distribution ratio of the diagonal rotors, the attitude control of the airframe is achieved. The tilt servo of the thrust vectoring power system adopts a direct-drive topology, and the auxiliary rotor of the thrust vectoring power system tilts. The wingtip is equipped with a tilt servo, the output of which is connected to the drive motor of the auxiliary rotor. During the tilting process, the position of the auxiliary rotor can be adjusted from any position on the path from the vertical plane to the horizontal plane. The MRAC-ADRC integrated intelligent control system includes: The MRAC module includes: Main controller: Outputs signals after receiving the desired command; Control distribution module: converts the signals output by the main controller into the output of the machine body; Adaptive law design: Based on the output error between the reference model and the actual machine system, the main controller parameters are dynamically adjusted to enable the actual machine to track the performance of the reference model; The ADRC module estimates the total disturbance in real time online through an extended state observer (ESO). This observer constructs an extended state-space model based on the system's input and output data, observing the disturbance as an extended state. A suitable observation bandwidth is designed to balance noise suppression and dynamic tracking capabilities, achieving disturbance feedforward compensation without relying on a precise aerodynamic parameter model. Simultaneously, the outer control loop introduces an MRAC reference model, selecting a second-order ideal system as the reference model. Appropriate natural frequencies and damping ratios are chosen, and an adaptive law is designed using Lyapunov stability theory to adjust the control gain online, forcing the actual state error to converge asymptotically. The full-cycle intelligent energy dynamic optimization system is built on the basis of the MRAC-ADRC fusion control system, including: Intelligent mission planning: Receives input information; performs optimal flight profile planning based on a digital twin model; Real-time energy optimization: Combining the MRAC-ADRC fusion control system, it realizes the switching of flight modes and converts control commands into action commands; Execution layer energy efficiency optimization: Based on the unified design of rudderless surface and power redundancy, the command is further optimized by the energy management architecture of aero-propulsion coupling to realize the control of the tilt servo's rotation angle and the speed of the power motor; The six-rotor mode is used in the vertical take-off and landing phase and hovering / low-speed operation scenarios. The tilt servos of the two thrust vector power systems are controlled to form a six-rotor layout. The transition flight mode is applied during the tilt flight phase. This mode employs two methods to complete the transition: Method 1, One-time tilt transition: After reaching the critical tilt speed through flight in six-rotor mode, the tilt servo of the thrust vector power system is directly controlled at a tilt angle of about 0 degrees. Method 2, Gradual Tilting: The tilting motor angle of the thrust vector power system is calculated based on the MRAC-ADRC intelligent control system. As the speed increases, the thrust vector power system gradually tilts to about 0 degrees. The quadcopter + vector cruise mode is applied during the cruise flight phase. In this mode, the tilt servos of the two thrust vector propulsion systems will be controlled at a tilt angle of about 0 degrees, forming a vector-composite layout of quadcopter + vector propulsion. At the same time, while providing the main thrust for forward flight, the auxiliary rotor generates auxiliary pitch / roll torque through vector deflection, forming a redundant trim system of "quadcopter + thrust vector".

2. The vector-composite layout multi-copter drone energy management and control method of claim 1, wherein: Includes the following steps: Configuration design: Through the unified design of rudderless design and power redundancy and the unified design of aerodynamic-propulsion coupled energy management architecture, the two work together to realize the hardware configuration, and the configuration design supports the software framework; Software framework: Through the deep integration of the full-cycle intelligent energy dynamic optimization system and the MRAC-ADRC integrated intelligent control system, the two work together to support the performance of the flight platform.

3. The method of claim 2, wherein: The aerodynamic-propulsion coupled energy management architecture includes: Select the appropriate flight mode through flight mode decision; By controlling the distribution, commands are sent to the main rotor power system and / or thrust vectoring power system to control the rotor speed and tilt angle; This reduces the load on the main rotor and adjusts the direction by tilting the auxiliary rotor.

4. The method of claim 3, wherein: Flight modes include: hexacopter low-speed mode, transitional flight mode, and quadcopter + vector cruise mode. The different control methods corresponding to these modes in sequence include differential tilt, one-time / gradual tilt, and thrust vector deflection.

5. The vector-composite layout multi-copter drone energy management and control method of claim 4, wherein: In intelligent task planning, the input information includes route information, inspection point distribution, weather information, battery status, and other information.

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