Self-adaptive reconfiguration method of reconfigurable load equipment control system

Abstract

The application provides a self-reconfigurable carrying equipment control system adaptive reconfiguration method. According to different configurations of the self-reconfigurable carrying equipment, the internal control system of the cell unit is quickly reconfigured by itself, and the control system of the self-reconfigurable carrying equipment is jointly constituted, so that good control of different configurations of the equipment is realized. The control system reconfiguration adaptive method has an adaptive capability. After the mechanical reconfiguration of the cell unit is completed, the current equipment configuration state is autonomously detected, and adaptive reconfiguration of the control system is performed according to the current equipment configuration state, so that the corresponding hardware architecture and software algorithm are adjusted and matched. In the case of high-frequency reconfiguration of the self-reconfigurable carrying equipment, manual switching and other operations for the control system are not required, the automation degree of the self-reconfigurable carrying equipment is improved, and the time, manpower and other additional costs brought by the reconfiguration process are saved.

Description

Technical Field

[0001] This invention relates to a reconfiguration method, specifically an adaptive reconfiguration method for a self-reconfigurable transport equipment control system, belonging to the field of transport equipment control technology. Background Technology

[0002] Self-reconfigurable delivery systems, capable of autonomous reconfiguration, assembly, and disassembly, hold the potential to become future game-changers. Due to the complexity of the terrestrial environment, the development of self-reconfigurable ground delivery systems is extremely challenging and recognized globally. More revolutionary is the fact that self-reconfiguration technology will make large-scale self-reconfigurable land-based equipment a reality. Large-scale land-based equipment, including airport runways, missile / rocket launchers, electromagnetic railguns / laser weapons, etc., are strategic assets for maintaining national security. Their reconnaissance and counter-reconnaissance, destruction and counter-destruction capabilities are crucial for victory in war. Once self-reconfiguration technology is mastered, allowing large-scale land-based equipment to be composed of reconfigurable cellular units, achieving self-reconfiguration, self-assembly, self-disassembly, and self-concealment—"assembling small units to achieve greater capabilities; dispersing and maneuvering for concealment"—it will become virtually undetectable and indestructible, enabling the development of advanced weapons such as self-reconfigurable aircraft takeoff and landing platforms, self-reconfigurable missile / rocket launchers, and self-reconfigurable electromagnetic railguns / laser weapons.

[0003] Highly efficient, robust, and scalable control systems are among the key technologies for self-reconfigurable large-scale land-based equipment. The autonomous reconfiguration of self-reconfigurable launch vehicles involves not only mechanical system-level reconfiguration but also the integration and disassembly of multiple systems, including control and energy systems, thus presenting new challenges to each system. For the control system, each cell unit possesses a complete and independent system configuration. For the parent equipment formed after the reconfiguration of multiple cell units, both the control system software and hardware become redundant. Therefore, for the control system of a self-reconfigurable parent equipment with complex topological relationships, it is crucial to coordinate the collaborative relationships between controllers, actuators, and other hardware in each cell unit to ensure that the performance of each controller, actuator, and the overall control system reaches its optimal level. Furthermore, after different numbers of cell units are reconfigured into multi-configuration parent equipment, the software parameters such as the equipment dynamics model and control algorithm change accordingly, making it difficult to establish a unified reference model for characterization. Clearly, the control architecture of traditional transport equipment can no longer meet the needs of rapid reconfiguration of the control system of self-reconfigurable transport equipment. Therefore, it is urgent to propose a reconfiguration method to ensure that after the mechanical reconfiguration of different numbers of self-reconfigurable transport equipment cell units, their control system can be adaptively reconfigured in a certain way, thereby improving the robustness and scalability of the self-reconfigurable transport equipment control system and greatly expanding the capability boundaries that self-reconfigurable transport equipment can exert. Summary of the Invention

[0004] In view of this, the present invention provides an adaptive reconfiguration method for a self-reconfigurable transport equipment control system, which enables the control system to autonomously adapt to the current equipment configuration and autonomously complete the matching system reconfiguration while completing mechanical reconfiguration of any number of cell units, thus ensuring the safe and stable operation of self-reconfigurable transport equipment of various configurations.

[0005] Adaptive reconfiguration method for self-reconfigurable vehicle control system: The self-reconfigurable vehicle is formed by splicing together multiple cellular units, the cellular units including motor cellular units and mission cellular units;

[0006] Multiple mobile cell units dock to form a reconfigurable chassis, and the mission cell units are mounted on the reconfigurable chassis.

[0007] Each mobile cell unit's vehicle controller has multiple pre-set general dynamic control models for different equipment configurations, as well as parameters for the corresponding configurations, dynamic control algorithms for different configurations of transport equipment, their control strategies, and parameters.

[0008] When the configuration of the self-reconfigurable transport equipment changes, the control system of the self-reconfigurable transport equipment adaptively adjusts, and the adjustment process is as follows:

[0009] First, the chassis domain master and slave controllers are determined: After the task cell units are installed on the reconfigured chassis, the motor cell unit that is connected to the vertical communication interface on the task cell unit is the master unit, and its internal vehicle controller is the master controller; the vehicle controllers of the other motor cell units are slave controllers.

[0010] Determination and allocation of control algorithms: When the main controller receives the control command sent by the task cell unit, it calls the corresponding dynamic control algorithm according to the current configuration; and when executing the dynamic control algorithm, it determines to adopt hierarchical control logic, that is, the main controller calculates the control information that needs to be allocated to each motor cell unit, and then transmits the control information to be allocated to each slave controller, and each slave controller continues to calculate in order to control itself;

[0011] Control model update: Based on the current equipment configuration, the corresponding dynamic control model is directly called from the vehicle controller of the motor cell unit to update the dynamic control model used in the executed dynamic control algorithm;

[0012] Control algorithm parameter matching: Call the control strategy and parameters of the corresponding dynamic control algorithm pre-existing in the vehicle controller of the motor cell unit to complete the adaptive reconfiguration of the control system.

[0013] In a preferred embodiment of the present invention, when the dynamic control algorithm is layered, the upper-level algorithm is used for planning and allocation, and the lower-level algorithm is used for calculating specific control parameters. After multiple motor cell units are reconstructed to form a reconstructed chassis, the main controller first executes the upper-level algorithm of the dynamic control algorithm to obtain the parameters required by the lower-level algorithm, and then sends them to each slave controller in the reconstructed chassis. The slave controllers then execute the lower-level algorithm to obtain their own control parameters.

[0014] As a preferred embodiment of the present invention, the dynamic control algorithm is divided into the following four levels:

[0015] Motion planning layer: This layer defines the ideal response state parameters; specifically, it includes the definition and selection of state parameters for the transport equipment, such as ideal longitudinal acceleration, ideal yaw rate, ideal center of mass sideslip angle, ideal root mean square vibration value, and ideal wheel slip ratio.

[0016] Motion tracking layer: The control quantity for the actuator to track the ideal state parameters is obtained through the control algorithm;

[0017] Motion allocation layer: Distributes the control quantities obtained from the motion tracking layer to each motor cell unit;

[0018] Motion execution layer: Comprehensive control of actuators, including steering, driving, and braking, in the motor cell unit to achieve the goals of the motion planning layer;

[0019] The first three levels are used as the upper level of the dynamic control algorithm, and the last level is used as the lower level of the dynamic control algorithm.

[0020] In a preferred embodiment of the present invention, in the self-reconfigurable vehicle equipment, the mission cell unit communicates with the internal control system via CANA, and also communicates with the maneuver cell unit via CANA; the maneuver cell units communicate with each other via CAN B; and the maneuver cell unit communicates internally via CAN C.

[0021] The task cell unit is equipped with only one vertical communication docking port connected to CAN A. After the task cell unit is installed on the reconfigurable chassis, the motor cell unit that docks with the vertical communication docking port on the task cell unit is the main unit.

[0022] As a preferred embodiment of the present invention, the scenarios in which the self-reconfigurable vehicle control system performs reconfiguration include, but are not limited to: multiple mutually separate cell units reconfiguring together into a self-reconfigurable vehicle; or a self-reconfigurable vehicle that has already been reconfigured replacing different task cell units or adding or removing maneuvering cell units to perform new tasks.

[0023] As a preferred embodiment of the present invention, the pre-stored equipment configurations include, but are not limited to, 4×4, 6×6, and 8×8 configurations, as well as configurations with different task cell units; the general dynamic control model includes, but is not limited to, a longitudinal vehicle dynamics model for longitudinal control and a two-degree-of-freedom vehicle dynamics model for lateral dynamic control; the parameters of the corresponding configuration model refer to parameters that change with the equipment configuration, including but not limited to: vehicle mass, center of gravity position, and vehicle rotational inertia;

[0024] The pre-stored dynamic control algorithms include, but are not limited to, direct yaw moment control, anti-lock braking control, active steering control, and active suspension control; the control strategies include, but are not limited to, PID control, LQR control, and MPC control.

[0025] Beneficial effects:

[0026] (1) The self-reconfigurable carrier equipment control system adaptive reconfiguration method of the present invention has high scalability and can flexibly adapt to the self-reconfigurable carrier equipment reconfigured by any number of cell units. It is not limited by the number of cell units participating in the reconfiguration and can support the normal operation of the control system of various configurations of the parent equipment, thereby improving the upper limit of the development of self-reconfigurable carrier equipment.

[0027] (2) The self-reconfigurable transport equipment control system reconfiguration adaptive method of the present invention has adaptive capability. After the cellular unit completes mechanical reconfiguration, it can autonomously detect the current equipment configuration state and perform adaptive reconfiguration of the control system accordingly, adjusting the corresponding hardware architecture and software algorithm to match them. This enables high-frequency reconfiguration of the self-reconfigurable transport equipment without requiring manual switching of the control system, improving the automation level of the self-reconfigurable transport equipment and saving the additional costs such as time and manpower incurred during the reconfiguration process.

[0028] (3) The self-reconfigurable vehicle equipment control system reconfiguration adaptive method of the present invention adopts a hierarchical-supervised controller reconfiguration collaborative logic. By setting the master-slave relationship of the vehicle controllers of multiple cell units and reasonably allocating the control algorithms in each controller, the rational utilization of the controller computing power is realized, avoiding the generation of low-load vehicle controllers, which would result in wasted computing power; or the generation of overloaded vehicle controllers, which would result in excessive computing pressure on a single controller, reducing lifespan and efficiency, thus ensuring the stable and efficient operation of the self-reconfigurable vehicle equipment control system under various configurations. Attached Figure Description

[0029] Figure 1 This is a communication architecture diagram for a self-reconfigurable launch vehicle control system.

[0030] Figure 2 Flowchart of the reconfiguration method for the control system of a self-reconfigurable transport vehicle;

[0031] Figure 3 This is a logic diagram of the self-reconfigurable parent equipment controller and execution algorithm. Detailed Implementation

[0032] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. The specific embodiments and descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0033] This embodiment provides an adaptive reconfiguration method for a self-reconfigurable vehicle control system. Based on different configurations of the self-reconfigurable vehicle, the internal control system of the cell unit can be rapidly reconfigured to form the control system of the self-reconfigurable vehicle, thereby achieving good control over equipment with different configurations.

[0034] The method is applied to a self-reconfigurable launch vehicle (full name "self-reconfigurable ground launch vehicle"), which is composed of multiple cell units. The cell units are spliced ​​together by docking mechanisms to form launch vehicles with different configurations.

[0035] Cellular units are divided into two types: motorized cellular units and task cellular units.

[0036] The mobile cell unit is a two-wheeled mobility unit, comprising a chassis frame and mounted on it drive, steering, braking, control, sensing, positioning, assembly, and battery modules. Mobile cell units can be docked in pairs along the longitudinal direction of the vehicle body via a docking mechanism to form reconfigurable chassis with varying numbers of wheels, supporting the self-reconfigurable transport equipment in its driving functions. Task cell units, with their built-in mechanisms, support the self-reconfigurable transport equipment in performing different tasks. They can be vertically docked and fixed to the reconfigurable chassis to form a complete transport equipment, and different task units with built-in mechanisms can be swapped out to perform different tasks required by the transport equipment.

[0037] Cellular units are mechanically connected via vertical and horizontal docking mechanisms, and energy and information exchange between them is achieved through vertical and horizontal energy and information interfaces. For example... Figure 1 As shown, the upper part of the image shows a 4×4 configuration vehicle consisting of two maneuvering cell units and one mission cell unit, a 6×6 configuration vehicle consisting of three maneuvering cell units and one mission cell unit, and an 8×8 configuration vehicle consisting of four maneuvering cell units and one mission cell unit.

[0038] Figure 1This diagram illustrates the basic components and topology of the communication architecture for a self-reconfigurable launch vehicle control system. The architecture is composed of the reconfigured control systems of various cellular units, with the main body consisting of three CAN buses. Cellular units connect via horizontal and vertical interfaces through these CAN buses, enabling information transmission between them. The three CAN buses are CAN A, CAN B, and CAN C.

[0039] Specifically: CAN A is used for communication within the internal control system of the mission cell unit and enables communication between the mission cell unit and the motor cell unit. The actuators in the mission cell unit include, but are not limited to, the cockpit, battery, sensors, and other components. The cockpit includes, but is not limited to, control mechanisms such as the steering wheel, accelerator pedal, and brake pedal. The CAN A between the mission cell unit and the motor cell unit is connected via a vertical communication interface to a vertical communication interface on one of the motor cell units on the reconfigurable chassis, enabling information exchange between the mission cell unit and the motor cell unit.

[0040] CAN B is used for control communication between motor cell units. When two or more motor cell units are longitudinally docked to form a reconfigurable chassis, the CAN B of each motor cell unit is connected through the longitudinal communication docking ports at both ends, forming a bus that runs through the reconfigurable chassis, thereby enabling communication between the motor cell units.

[0041] CAN-C is used for internal control communication within the motor cell unit. It enables information exchange between the vehicle controller module within the motor cell unit and various actuators. The actuators within the motor cell unit include, but are not limited to, the power battery, the execution system, and various sensors. The execution system includes, but is not limited to, the drive system, the steering system, and the braking system.

[0042] To simplify the communication architecture of the self-reconfigurable transport vehicle, regardless of the number and order of the mobile cell units participating in the reconfiguration, one of the mobile cell units will be designated as the master unit. The selection of the master unit depends on the position of the vertical communication docking port of the mission cell unit. Only one vertical communication docking port connected to CAN A is set on the mission cell unit. After the mission cell unit is installed on the reconfiguration chassis, the mobile cell unit that docks with the vertical communication docking port on the mission cell unit is the master unit. The master unit receives driver commands from the mission cell unit through the connection with CAN A of the mission cell unit.

[0043] Based on the communication architecture of the self-reconfigurable vehicle control system, this adaptive reconfiguration method can achieve the following functions: After multiple cell units complete mechanical reconfiguration to form a self-reconfigurable vehicle, the overall vehicle configuration and control architecture change due to the change in the number and type of cell units involved in the reconfiguration; Based on the proposed method, its control system can perform adaptive reconfiguration to quickly match the current configuration of the vehicle, so as to meet the actual needs of frequent reconfiguration of the self-reconfigurable vehicle and achieve good control of the multi-configuration self-reconfigurable vehicle.

[0044] The main application scenarios for reconfigurable launch vehicle control systems include, but are not limited to: ① multiple separate cellular units that need to be reconfigured together into a single self-reconfigurable launch vehicle; ② a self-reconfigurable launch vehicle that has already been reconfigured needs to have different task cellular units replaced or maneuver cellular units added or removed to perform a new task. In other words, whenever the configuration and / or control system parameters of a self-reconfigurable launch vehicle change, its control requirements need to be reconfigured.

[0045] Figure 2 This diagram illustrates the adaptive reconfiguration process of the control system for self-reconfigurable transport equipment, comprising two stages: hardware reconfiguration and software reconfiguration. Hardware reconfiguration refers to the process of recombining the hardware of each cellular unit control system to form a new configuration, including mechanical reconfiguration and communication reconfiguration. Software reconfiguration occurs after hardware reconfiguration and mainly refers to the adaptive adjustment of the control algorithm within the controller, including four steps: determining the master and slave controllers in the chassis domain, determining and allocating the control algorithm, switching the equipment control model, and matching the control algorithm parameters.

[0046] In addition, in order to realize the software reconfiguration of the control system, when designing the vehicle controller of the cell unit, it is necessary to pre-set the general dynamic model and dynamic parameters (control algorithm and its parameters) of the multi-configuration vehicle equipment in the vehicle controller of the motor cell unit for use in the process of software reconfiguration of the control system.

[0047] The process of pre-programming within the vehicle controller of each motor cell unit is the offline reconfiguration process, while the hardware and software reconfiguration processes of the control system are the online reconfiguration processes. The offline and online reconfiguration processes will be described in detail below.

[0048] The offline reconfiguration process consists of two steps: first, pre-setting a general control model for different configurations of transport equipment in the vehicle controller of the motor cell unit; second, pre-storing control algorithms, control strategies, and parameters for different configurations of transport equipment.

[0049] In the offline reconfiguration process, it is first necessary to pre-design a general control model and corresponding configuration model parameters for different configuration vehicles to facilitate direct use during online reconfiguration. These vehicle configurations include, but are not limited to, 4×4, 6×6, and 8×8 configurations, as well as configurations with different mission cell units. The general control model includes, but is not limited to, a longitudinal vehicle dynamics model for longitudinal control and a two-degree-of-freedom vehicle dynamics model for lateral dynamics control. The parameters of the corresponding configuration model refer to parameters that change with different configuration vehicles, including but not limited to: vehicle mass, center of gravity position, and vehicle rotational inertia. It is necessary to experimentally measure commonly used equipment configuration parameters in advance and store multiple sets of parameters in the vehicle controller of each maneuvering cell unit so that the parameters of the current configuration can be matched promptly after switching equipment control models.

[0050] Secondly, there are the dynamic control algorithms and their control strategies and parameters. The dynamic control algorithms include, but are not limited to, direct yaw moment control, anti-lock braking control, active steering control, and active suspension control. First, the control algorithm in each controller changes under different configurations, and different algorithms will be activated. Second, the control strategies used in the algorithms include, but are not limited to, PID control, LQR control, and MPC control. The optimal parameters of these control strategies will change with the configuration, including but not limited to kp, ki, and kd for PID control, Q and R matrices for LQR control, and prediction time domain for MPC control. Therefore, it is necessary to save the control algorithms and optimal parameters of the control algorithms and control strategies that may be used by each controller under different configurations in advance during the offline reconstruction process, so as to facilitate direct calling in the online process and ensure the best control effect.

[0051] The online refactoring process can be divided into two processes: hardware refactoring and software refactoring.

[0052] The control system hardware reconfiguration can be divided into mechanical reconfiguration and communication reconfiguration, both of which are performed simultaneously. First, multiple motorized cell units are driven remotely from a distance, approaching each other within a certain range. They then dock with each other through a docking mechanism. After that, the communication docking interfaces between the motorized cell units are connected. Finally, a locking mechanism is used to lock the various motorized cell units together into a rigid structure, forming the reconfiguration chassis. Second, using reconfiguration auxiliary equipment, including but not limited to cranes and hydraulic supports, the task cell units are placed on top of the reconfiguration chassis. Similarly, the task cell units are connected to the communication docking interfaces of the main module in the reconfiguration chassis, and locked and fixed using a vertical locking mechanism, forming the final self-reconfigurable transport equipment.

[0053] After the hardware reconfiguration of the control system is completed, the vehicle controllers of each cell unit of the self-reconfigurable vehicle automatically acquire the current configuration information and guide the control system to perform adaptive software reconfiguration. The software reconfiguration process does not require manual intervention and can be completed adaptively after the hardware reconfiguration. It includes four steps: chassis domain master-slave controller determination, controller execution algorithm determination, equipment control model update, and equipment dynamic parameter matching.

[0054] (1) Determination of master-slave controller in chassis domain: After the hardware reconfiguration of the control system, the reconfiguration chassis of the self-reconfigurable vehicle equipment is connected to the vehicle controllers of multiple cell units. In order to make proper use of the computing power of all vehicle controllers and avoid generating low-load vehicle controllers, which would waste computing power, or generating overloaded vehicle controllers, which would cause excessive pressure, a hierarchical-supervisory controller collaboration logic is adopted to determine the master-slave relationship between each vehicle controller of the motor cell unit.

[0055] The following rules apply to the master-slave relationship between motor cell units: Regardless of the number and order of motor cell units participating in the reconfiguration, one of the motor cell units will become the master unit. The selection of the master unit depends on the position of the vertical communication docking port of the task cell unit. After the task cell unit is installed on the reconfiguration chassis, the motor cell unit that docks with the vertical communication docking port on the task cell unit becomes the master unit. The master unit directly receives control commands from the task cell unit via CAN A.

[0056] like Figure 3 As shown, taking a 6×6 configuration self-reconfigurable vehicle control system consisting of three motorized cell units and one task cell unit as an example, A is the vehicle controller of the task cell unit, and B1, B2, and B3 are the vehicle controllers of the three motorized cell units respectively; C1, C2, and C3 are the controlled drive motors of the three motorized cell units. It can be seen that, based on the connection position of the vertical communication interface between the task cell unit and the reconfigurable chassis, the second motorized cell unit is determined to be the master unit, and its internal vehicle controller B2 is designated as the master controller, while the vehicle controllers of the remaining motorized cell units (i.e., B1 and B3) are slave controllers.

[0057] The hierarchical-supervised controller collaborative logic works as follows: First, the vehicle controller of the task cell unit receives control commands from the cockpit, such as steering, throttle, and braking, and parses them before passing them to the main controller in the reconfigurable chassis. The main controller, in addition to receiving control commands, also receives feedback information on the overall motion status of the self-reconfigurable vehicle. Based on this information, it calculates the control information to be allocated to each motor cell unit and then transmits this information to the slave controllers of all motor cell units. The slave controllers continue to perform lower-level calculations (the main controller and all slave controllers are connected to the same CAN bus; the main controller sends all information, and the commands sent to several slave controllers correspond to different ID numbers, which each slave controller can then look up on the CAN bus). After receiving the control information allocated by the main controller, each slave controller distributes it to its own unit's various execution controllers, power batteries, and other components to control them to complete the corresponding actions.

[0058] (2) Determination and Allocation of Control Algorithms: To ensure versatility, the algorithms within the vehicle controllers of each motor cell are identical during the design process. Each motor cell's vehicle controller is pre-programmed with various dynamic control algorithms for controlling its motion, including but not limited to direct yaw moment control algorithms, anti-lock braking system (ABS) control algorithms, active steering control algorithms, and active suspension control algorithms. When the main controller receives a control command from a task cell, it executes the corresponding control algorithm. For example, when the main controller receives a lateral stability control command, it executes the direct yaw moment control algorithm; when the main controller receives a steering command, it executes the active steering control algorithm.

[0059] To ensure optimal computing power for the vehicle controller in each motor cell unit, a hierarchical design is implemented for each dynamic control algorithm. The upper-level algorithm is used for planning and allocation, while the lower-level algorithm is used for calculating specific control parameters. Specifically, the dynamic control algorithm is divided into the following four levels: (1) Motion planning layer: the ideal response state parameter formulation layer; specifically, it includes the formulation and selection of state parameters such as ideal longitudinal acceleration, ideal yaw rate, ideal centroid sideslip angle, ideal root mean square value of vibration, and ideal wheel slip ratio. (2) Motion tracking layer: through various control algorithms, the control quantities for the actuator to track the ideal state parameters are obtained, such as generalized driving force, generalized yaw moment, generalized braking force, and generalized roll moment. (3) Motion allocation layer: the generalized forces obtained in the previous step are allocated to each wheel or each module unit. (4) Motion execution layer, which is how to comprehensively control the actuators such as steering, driving and braking to achieve the motion planning layer goals; specifically including the control of the vehicle's longitudinal drive motor, the control of the braking mechanism, the adjustment of the stiffness and damping of the suspension system, and the adjustment of the active yaw moment.

[0060] The first three levels require the state feedback of the entire equipment, while the last level only requires the state of its own unit. Therefore, the first three levels are used as the upper level of the dynamic control algorithm, and the last level is used as the lower level of the dynamic control algorithm.

[0061] Although each motor cell unit's vehicle controller has a complete dynamic control algorithm pre-set inside, after it is reconstructed to form a reconstructed chassis, the main controller first executes the upper-level algorithm of the dynamic control algorithm to obtain the parameters required by the lower-level algorithm, and then sends them to each slave controller in the reconstructed chassis via CAN B. The slave controllers then execute the lower-level algorithm to obtain their own control parameters (the main controller also executes the lower-level algorithm to obtain its own control parameters). Thus, the main controller executes both the upper and lower levels of the dynamic control algorithm, while the slave controllers only execute the lower-level algorithm.

[0062] Taking the direct yaw moment control algorithm (lateral stability control) as an example:

[0063] First, the vehicle controller of each motor cell unit has a complete direct yaw moment control algorithm pre-set inside: the direct yaw moment control algorithm is divided into upper and lower layers. The upper layer control algorithm includes a motion tracking algorithm and a motion distribution algorithm. The motion tracking algorithm calculates the generalized force based on the deviation of the motion control target, and the motion distribution algorithm distributes the generalized force to the driving force of each wheel. The lower layer control algorithm is a slip ratio control algorithm, which controls the magnitude of the driving force distributed to the wheels to keep the tire slip ratio within the optimal range.

[0064] like Figure 3 As shown, taking a 6×6 configuration of the parent equipment consisting of three maneuvering cell units and one task cell unit as an example, the numbers 1, 2, and 3 inside the vehicle controller of each maneuvering cell unit represent the motion tracking algorithm, motion allocation algorithm, and slip ratio control algorithm, respectively. When the main controller receives the lateral stability control command, the main controller first executes the motion tracking algorithm and motion allocation algorithm to obtain the parameters required for the slip ratio control algorithm, and then sends them to the two slave controllers. The slave controllers and the main controller then execute the slip ratio control algorithm to control their own slip ratio.

[0065] (3) Control Model Update: After determining the algorithms executed within each equipment controller, the dynamic control model of the transport equipment used in the executed algorithms needs to be updated according to the architecture of the currently reconstructed chassis to match the input and output of the control model under the current configuration. Multiple general equipment control models have been established during the offline reconstruction process. When updating the transport equipment control model, only the corresponding equipment control model needs to be called to quickly complete the control model switching and match the required model for the current model control algorithm.

[0066] (4) Control algorithm parameter matching. After the control model is updated, the parameters, control strategies and parameters of different configuration equipment stored in the vehicle controller during the offline reconfiguration process are called to complete the software reconfiguration process.

[0067] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. 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. An adaptive reconfiguration method for a self-reconfigurable transport equipment control system, characterized in that, The self-reconfigurable vehicle is formed by splicing together multiple cellular units, which include motorized cellular units and mission cellular units. Multiple mobile cell units dock to form a reconfigurable chassis, and the mission cell units are mounted on the reconfigurable chassis. Each mobile cell unit's vehicle controller has multiple pre-set general dynamic control models for different equipment configurations, as well as parameters for the corresponding configurations, dynamic control algorithms and control strategies for different configurations of transport equipment, and parameters. When the configuration of the self-reconfigurable transport vehicle changes, the control system of the self-reconfigurable transport vehicle adaptively adjusts, and the adjustment process includes: Chassis domain master-slave controller determination: After the task cell unit is installed on the reconfigured chassis, the motor cell unit that is connected to the vertical communication docking port on the task cell unit is the master unit, and its internal vehicle controller is the master controller; the vehicle controllers of the other motor cell units are slave controllers. Determination and allocation of control algorithms: When the main controller receives the control command sent by the task cell unit, it calls the corresponding dynamic control algorithm according to the current configuration; and when executing the dynamic control algorithm, a hierarchical control logic is adopted, that is, the main controller calculates the control information that needs to be allocated to each motor cell unit, and then transmits the control information to be allocated to each slave controller, and each slave controller continues to calculate in order to control itself; Control model update: Based on the current equipment configuration, the corresponding dynamic control model is directly called from the vehicle controller of the motor cell unit to update the dynamic control model used in the executed dynamic control algorithm; Control algorithm parameter matching: Call the control strategy and parameters of the corresponding dynamic control algorithm pre-existing in the vehicle controller of the motor cell unit to complete the adaptive reconfiguration of the control system.

2. The adaptive reconfiguration method for a self-reconfigurable transport equipment control system as described in claim 1, characterized in that, When the dynamic control algorithm is layered, the upper-level algorithm is used for planning and allocation, while the lower-level algorithm is used for calculating specific control parameters. After multiple motor cell units are reconstructed to form a reconstructed chassis, the main controller first executes the upper-level algorithm of the dynamic control algorithm to obtain the parameters required by the lower-level algorithm, and then sends them to each slave controller in the reconstructed chassis. The slave controllers then execute the lower-level algorithm to obtain their own control parameters.

3. The adaptive reconfiguration method for a self-reconfigurable transport equipment control system as described in claim 2, characterized in that, The dynamic control algorithm is divided into the following four levels: Motion planning layer: This layer defines the ideal response state parameters; specifically, it includes the definition and selection of state parameters for the transport equipment, such as ideal longitudinal acceleration, ideal yaw rate, ideal center of mass sideslip angle, ideal root mean square vibration value, and ideal wheel slip ratio. Motion tracking layer: The control quantity for the actuator to track the ideal state parameters is obtained through the control algorithm; Motion allocation layer: Distributes the control quantities obtained from the motion tracking layer to each motor cell unit; Motion execution layer: Comprehensive control of actuators, including steering, driving, and braking, in the motor cell unit to achieve the goals of the motion planning layer; The first three levels are used as the upper level of the dynamic control algorithm, and the last level is used as the lower level of the dynamic control algorithm.

4. The adaptive reconfiguration method for a self-reconfigurable transport equipment control system as described in claim 1, 2, or 3, characterized in that, In the self-reconfigurable launch vehicle, the mission cell unit communicates with the internal control system via CAN A, and also communicates with the maneuver cell unit via CAN A; the maneuver cell units communicate with each other via CAN B; and the maneuver cell unit communicates internally via CAN C. The task cell unit is equipped with only one vertical communication docking port connected to CAN A. After the task cell unit is installed on the reconfigurable chassis, the motor cell unit that docks with the vertical communication docking port on the task cell unit is the main unit.

5. The adaptive reconfiguration method for a self-reconfigurable transport equipment control system as described in claim 1, 2, or 3, characterized in that, The scenarios in which a self-reconfigurable launch vehicle control system can be reconfigured include, but are not limited to: multiple separate cell units reconfiguring together into a single self-reconfigurable launch vehicle; or a self-reconfigurable launch vehicle that has already been reconfigured replacing different task cell units or adding or removing maneuvering cell units to perform a new task.

6. The adaptive reconfiguration method for a self-reconfigurable transport equipment control system as described in claim 1, 2, or 3, characterized in that, The pre-stored equipment configurations include, but are not limited to, 4×4, 6×6, and 8×8 configurations, as well as configurations with different task cell units; the general dynamic control model includes, but is not limited to, a longitudinal vehicle dynamics model for longitudinal control and a two-degree-of-freedom vehicle dynamics model for lateral dynamic control; the parameters of the corresponding configuration model refer to the parameters that will change with the equipment configuration, including but not limited to: vehicle mass, center of gravity position, and vehicle rotational inertia. The pre-stored dynamic control algorithms include, but are not limited to, direct yaw moment control, anti-lock braking control, active steering control, and active suspension control; the control strategies include, but are not limited to, PID control, LQR control, and MPC control.

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