365 results about "Backstepping" patented technology

The invention discloses a six-rotor unmanned aerial vehicle control method and system with disturbance and performance constraints. The method comprises the steps that 1, a six-rotor unmanned aerial vehicle power model is built; 2, errors are determined based on the dynamic model, functions are combined, and a finite time scheme is determined; step 3, based on the dynamic model, establishing an observer, and knowing a disturbance state; step 4, a performance control scheme and an unknown disturbance state are stipulated in finite time, an error dynamic model is established, and the error dynamic model is established based on reinforcement learning; 5, setting a base scheme, setting a virtual controller and an actual controller, and setting an adaptive law for the base neural network; 6, the controller follower can track the leader, and tracking control is completed; establishing a controller by adopting a backstepping method, establishing a disturbance observer, and compensating negative effects; a reinforcement learning algorithm and a backstepping method technology are combined, and a controller is arranged to realize control; according to the method, the stability is proved by using a Lyapunov judgment stability theory, and the feasible effectiveness is verified by a simulation example.

The invention relates to the technical field of injection molding pressure control, in particular to a multi-stage pressure closed-loop compensation system and method for high-precision double-color injection molding, and the system comprises an interface gradient positioning module, a flow resistance state recognition module, a fitting function reconstruction module, a time sequence deviation triggering module and a gain reverse correction module. According to the method, the high-density measuring point data is collected, the interface radial pressure gradient change is extracted through the finite difference method, the stably-arranged nodes at the material intersection can be accurately locked, and the flow resistance state of the flow channel is judged according to the slope difference value of the screw speed and the pressure intensity change. A linear boosting or index slow increasing strategy is automatically switched to reconstruct a pressure function form, local high-pressure accumulation characteristics of a product sensitive area are accurately matched, the coincidence degree of a time window drift trend and a slope sudden change window is monitored, historical displacement and pressure errors are converted into backstepping factors through an iterative learning model, and the backstepping factors are calculated. And a driving gain curve is initialized and revised, so that forming deviation caused by thermal drift of equipment is eliminated.

The invention relates to a non-linear multi-unmanned vehicle system self-triggering time-varying formation control method, which comprises the following steps: constructing a second-order dynamic model for a non-linear multi-unmanned vehicle system, and describing communication between unmanned systems through a directed topological structure; a backstepping method is adopted, a virtual controller is introduced, and a leader-follower formation error system under the triggering condition is constructed; designing influence weights of communication resources and control performance, and respectively constructing an optimization model based on virtual input and formation distributed position errors and an optimization model based on real input and tracking formation speed errors; solving an approximate solution of a corresponding Hamiltonian-Jacobi-Bellman equation through a simplified reinforcement learning method, and sequentially obtaining an optimal virtual control protocol and an optimal reality control protocol; similarly, determining a self-triggering prediction condition; and finally, under the condition of self-triggering prediction, the multi-unmanned vehicle system not only realizes time-varying formation, but also balances communication resources and control performance.

A system, computer readable storage medium and method for controlling a trajectory of coordinated time-varying maneuvers of a geometric formation of unmanned vehicles is disclosed. The system includes unmanned vehicles, each configured with communication circuitry to communicate between the vehicles. A subset of the unmanned vehicles function as leader vehicles, with the remaining vehicles functioning as follower vehicles for leader-follower maneuvering. The system further includes an actuator suite configured to adjust the direction and orientation of each vehicle, a sensor suite for stabilization and navigation, and a flight controller for maintaining stable maneuvering, even in the presence of actuator faults and sensor deception attacks. Processing circuitry is configured with a reinforcement learning neural network that includes identifier, actor, and critic radial basis function neural networks to estimate movement, adjust control actions, and assess vehicle performance based on feedback signals, including corrupted signals from the sensor suite due to deception attacks.

The invention discloses an unmanned agricultural machine path tracking preset performance control method and system, and the method comprises the steps: collecting the pose information of an unmanned agricultural machine, building an unmanned agricultural machine path tracking error kinematic model, and designing a finite time preset performance function based on the unmanned agricultural machine path tracking error kinematic model. The constraint is converted through nonlinear mapping; based on the Lyapunov stability theory, adopting a backstepping method to recursively design an actual control law, and according to the actual control law, performing inverse transformation on the input of the unmanned agricultural machine tracking control system in the error kinematics model of the unmanned agricultural machine tracking control system to obtain the front wheel steering angle of the unmanned agricultural machine. According to the method, convergence is completed within finite time, and transient control performance and steady control performance of a path tracking control system are considered.

The invention relates to a system inertia boundary backstepping method based on frequency dynamic indexes and distributed node equivalent inertia analysis, and belongs to the field of power optimization. The method comprises the following steps: dividing a frequency response process into an inertia response stage, a primary frequency modulation stage and a secondary frequency modulation stage; constructing a multi-source frequency response unified equivalent model; an equivalent inertia boundary inversion method based on RoCoF and Nadr dual constraints is provided, a frequency safety boundary is converted into a constraint expression for the equivalent total inertia of a system, and an inertia boundary required under given power disturbance is reversely deduced; the method further comprises the steps of introducing static load voltage characteristic correction during inertia boundary inversion; the method further comprises the step of constructing a frequency support-oriented regionalization control strategy. According to the method, the safety support boundary of the low-inertia emergency power supply system is researched from the overall level and the regional level, and a theoretical basis is provided for refined frequency control and resource optimization layout.

The invention relates to the technical field of robot control, and discloses a mechanical arm specified performance fault-tolerant control method based on a fuzzy logic system, and the method comprises the steps: building a kinematics and dynamics model and a fault model of an agricultural robot; establishing a relative error dynamic equation between the actual position and the expected position; designing a specified performance function, and constraining the tracking error within an expected range by using the specified performance function; on the basis, designing a virtual control law by using a backstepping method under the condition of meeting error constraints; designing an adaptive control law by adopting a fuzzy logic system based on an uncertain item, unknown environment interference and a fault model in the kinetic model; a specified performance controller is designed based on a virtual control law, fuzzy logic adaptive control and full-state feedback agricultural robot, and specified performance fault-tolerant control of the agricultural robot is realized. The stability proves that the tracking error of the agricultural robot converges to any small neighborhood near zero within fixed time.

The invention provides an ocean current interference resistant fault-tolerant control method and system for a robot multi-motor propulsion system, and the method comprises the steps: inputting the actual and expected position error and speed error of an underwater robot into a self-adaptive backstepping sliding mode path tracking controller, and obtaining the thrust needed by tracking motion; introducing a propeller weight matrix representing the fault degree of the propeller into a weighted pseudo-inverse method, optimizing the propeller weight matrix by adopting an intelligent algorithm to obtain an optimal propeller weight matrix, and performing thrust distribution on thrust required by tracking motion through the weighted pseudo-inverse method to obtain a thrust distribution result; according to the operation and thrust distribution results of the multiple motors, the parameters of all the motors are adjusted in a self-adaptive mode through a multi-motor fault-tolerant control strategy; and each motor remotely controls the underwater robot based on the parameters after self-adaptive adjustment, and obtains the actual position and speed of the underwater robot at the current moment for loop closing.

The invention relates to the technical field of cooperative control, in particular to an adaptive event triggering fixed time consistency control method for a multi-agent system, which comprises the following steps of: S1, constructing a nonlinear high-order multi-agent system mathematical model with uncertain dynamics; s2, constructing a Lyapunov function containing an uncertain parameter lower bound based on coordinate transformation; s3, designing an adaptive event trigger controller with a positive bounded function by using a backstepping control method, wherein the adaptive event trigger controller comprises a virtual controller, an adaptive law and an event trigger mechanism; and S4, through stability analysis, it is proved that the high-order nonlinear multi-agent with the uncertain dynamic state can achieve actual fixed time output consistency, Zeno behaviors are avoided, and the self-adaptive event triggering fixed time consistency control method of the multi-agent system has the advantages of being high in practicability and easy to popularize. The problem of actual fixed time output consistency of a high-order nonlinear multi-agent system is solved, and an existing actual fixed time output consistency result is popularized.

The invention provides a heterogeneous motorcade prediction control method based on a path information protection mechanism, and relates to the technical field of network connection unmanned vehicle cooperative control and intelligent traffic. Firstly, a path information protection mechanism is provided for preventing an alien invading vehicle from tracking a motorcade and ensuring the safety of motorcade path information. In addition, a predictor model is established to improve the estimation performance of the adaptive law, and a variable gain nonlinear expansion state observer is designed to approach and compensate the total disturbance. Then, by introducing a variable-gain hyperbolic tangent tracking differentiator, the problem of'complexity explosion 'caused by repeated derivation of a virtual controller in a backstepping method is avoided; and finally, a distributed prediction cooperative controller is constructed, and stable and safe driving of the whole heterogeneous network connection fleet is ensured.

The invention discloses an electro-hydraulic system adaptive neural network preset time control method, which integrates a neural network real-time learning technology, innovatively introduces a preset time performance function, and designs an adaptive neural network preset time performance controller. For the electro-hydraulic system position tracking control problem, it can be ensured that system output transient performance and steady-state performance converge to a specified performance index range within a preset time, safe and reliable operation of the system is ensured, the unknown dynamic state of the system can be learned in real time through a neural network, high-precision motion control performance is achieved, and the control precision is improved. And the problem of differential explosion in traditional backstepping control of the electro-hydraulic system can be avoided, and the influence of measurement noise on the control precision is reduced.

The invention discloses an event-triggered adaptive fixed time control method for a random nonlinear switching system. The method comprises the following steps: constructing a model of the random nonlinear switching system; introducing an event triggering mechanism; designing a fixed time control strategy; and designing an event-triggered fixed-time adaptive controller based on a backstepping method design framework. According to the event-triggered adaptive fixed time control method for the random nonlinear switching system, an event-triggered control strategy is adopted to reduce the communication burden of the system. A new controller is stably constructed by using fixed time, and the upper bound of convergence time is irrelevant to initial conditions; meanwhile, by introducing nonlinear mapping, a random nonlinear system with symmetric and asymmetric output constraints is converted into a new unconstrained system, and random switching of the control system is realized by using a switching signal.

The invention discloses a control method for ultra-low-altitude flight of a large unmanned aerial vehicle, and the method comprises the following steps: building a kinetic model of the unmanned aerial vehicle, the kinetic model comprising dynamic equations of position, speed, attitude control and control input; performing error tracking control on the attitude and the speed of the unmanned aerial vehicle by adopting a Backstepping nonlinear control method based on the dynamic model; estimating external disturbance and dynamic parameters of the unmanned aerial vehicle in real time by combining an L1 adaptive control method, and adaptively adjusting control input to compensate wind speed change; predicting a future flight state by using a model prediction control algorithm, optimizing a flight path and compensating wind speed disturbance; a safe trajectory is planned in real time through a dynamic window method, and obstacles are avoided in combination with dynamic constraints. According to the invention, through organic combination of Backstepping control, L1 adaptive control, MPC and DWA algorithms, the complex problems of wind speed disturbance, obstacle avoidance, high-precision operation and the like in ultra-low-altitude flight can be solved.

The invention relates to the technical field of data processing, and discloses a motor controller research and development method and system based on an intelligent algorithm. The method comprises the steps that after parameter identification is carried out on a motor, PID parameters are optimized through an adaptive differential evolution algorithm; constructing a double-loop control structure according to the optimal PID parameters; designing a virtual sensor based on the optimized double-loop structure and obtaining a health index; fusing the multi-source signal to obtain a fusion speed signal; therefore, a backstepping sliding mode controller is realized and system verification is completed. The motor control system with high fault-tolerant capability is constructed by fusing various intelligent algorithms and virtual sensor technologies, the basic operation performance of the motor can be kept even if the sensor is abnormal or fails, and the reliability and the safety of the system are improved.

According to the cooperative control method and system of the non-linear multi-agent system, under the condition that communication link faults are considered, a non-linear dynamic model of each single-connecting-rod mechanical arm is established, and unknown uncertain non-linear dynamic states in the single-connecting-rod mechanical arms are fuzzified through a fuzzy logic system; a mixed event triggering mechanism is introduced, so that state information of a leader is estimated, and the communication frequency is effectively reduced; and constructing a virtual controller and an actual controller by utilizing a backstepping method based on the estimated state information, so as to control the position of the following mechanical arm to be synchronous with the expected trajectory of the leading mechanical arm under the condition of being influenced by the communication link fault. According to the method, the state of the multi-single-connecting-rod mechanical arm system can be kept consistent and stable tracking control can be achieved under the condition that communication link faults and nonlinear uncertainty exist without global information.

The invention discloses a hydraulic system preset time dynamic surface position control method, which is based on a dynamic surface control framework, innovatively introduces a preset time-varying function, and designs a nonlinear robust position controller with preset time. Aiming at the position control problem of the hydraulic cylinder of the hydraulic system, the differential explosion problem frequently occurring in the classic backstepping control design of the hydraulic system is avoided, the influence of measurement noise on the control precision is reduced, the controller design is simplified, and the excellent transient performance of the system within the preset time is guaranteed; and the convergence time can be clearly determined and does not depend on initial conditions of the system, so that the method has high-precision tracking performance.

The invention belongs to the technical field of EL system control, and discloses a preset performance control method considering dynamic and constraint of an execution mechanism. The method comprises the following steps: firstly, establishing a system dynamics model considering dynamic and input saturation constraints of an executing mechanism; then, designing an asymmetric tubular performance boundary to restrain a system tracking error, and defining a conversion error according to the system tracking error; meanwhile, a disturbance observer based on immersion and invariance is designed, and composite disturbance is estimated. Furthermore, a tubular preset performance controller is designed by adopting a backstepping method, a virtual control law and an expected torque are constructed, and a multi-state auxiliary system is introduced to compensate the input saturation influence. And finally, a control instruction is generated by integrating the auxiliary system state, the virtual control law, the expected torque and the interference estimation value, and the control instruction acts on the system after being processed by a saturation function. According to the method, actuator dynamics, input saturation and external disturbance can be processed at the same time, and tracking errors are ensured to strictly follow a preset performance boundary.

The invention relates to a self-adaptive backstepping fault-tolerant control method for a transportation airfoil surface fault. The method comprises the following steps: establishing a six-degree-of-freedom equation of an airplane; in combination with a six-degree-of-freedom equation, determining a relationship between different types of faults and aerodynamic coefficients according to an airfoil fault mode; the wing surface fault mode comprises wing damage, control surface damage and control surface jamming; designing an angular velocity loop adaptive backstepping control law according to a nonlinear dynamic item about a state variable and a control input matrix about a control variable in a fault mode based on a relationship between different types of faults and aerodynamic coefficients; and performing control distribution on the angular velocity loop by using a weighted pseudo-inverse method, combining the adaptive backstepping control law of the angular velocity loop with the weighted pseudo-inverse method, and performing valuing on a weight matrix of the control distribution of the angular velocity loop according to an airfoil fault mode to obtain an adaptive backstepping fault-tolerant angular velocity control law with control distribution. According to the method, the fault-tolerant control efficiency after the airplane breaks down is optimized, and the fault-tolerant flight capability of the airplane is improved.

The invention provides a double-butterfly valve linkage anti-interference control method for a large air supply test device, which belongs to the technical field of aviation power devices and comprises the following steps of: simplifying inflow and outflow of an air supply adjusting system according to air mass flow into a one-way air inlet and three-way air exhaust structure; a slope pressure given signal and a pressure differential given signal are obtained based on a first discrete tracking differential module, and a filtering output signal and a differential extraction signal are obtained based on a second discrete tracking differential module; obtaining a total disturbance estimated value of the butterfly valve control loop by using the parameters based on a nonlinear discrete expansion state observation module; on the basis of the backstepping control module, the actual control quantity of the butterfly valve is obtained through the parameters; and adjusting the input gain estimation value of the butterfly valve control loop in real time based on a parameter self-adaptive adjustment module, and repeating the steps to realize the double-butterfly valve linkage anti-interference control of the large-scale gas supply test device. The method does not need manual intervention, and is fast in transient response, strong in anti-interference capability and high in robustness.

The invention provides a self-adaptive fixed time tracking control method based on event triggering, which is used for solving the technical problem that a virtual control law is easy to generate singularity in the traditional backstepping method design. The method comprises the following steps: establishing a mathematical model of a non-strict feedback nonlinear system with input time delay, and introducing an auxiliary system to counteract delay influence; an error dynamic system is obtained through coordinate transformation; according to system fixed time convergence, designing a piecewise function, introducing a backstepping method to design a controller and an adaptive law, using an RBFNN to approach an unknown function therein, designing a virtual control signal corresponding to each error signal, and obtaining an actual controller and an adaptive law; according to the actual self-adaptive controller, event triggering conditions are designed, when the event triggering moment is reached, the event triggering conditions containing input are triggered, and information transmission and response are carried out. An event triggering mechanism is designed, the number of times of control instruction transmission is reduced, communication resources are saved, and rapid convergence and safe operation of the system state are achieved.

The invention discloses an unmanned ship adaptive optimal interference control method based on reinforcement learning, and particularly relates to the technical field of unmanned ship automatic control, and the method comprises the steps: building an unmanned ship trajectory kinematics model based on the position information and heading angle information of an unmanned ship under a geodetic coordinate system, and the corresponding speed information under an unmanned ship appendage coordinate system; the method comprises the following steps: establishing an unmanned ship trajectory dynamics model by considering the control operation of the unmanned ship and the time-varying environment interference problems of wind, waves, flow, unmodeled dynamics and the like in a marine environment in which the unmanned ship is located; introducing a radial basis function neural network based on a set unmanned ship trajectory mathematical model; designing a self-adaptive interference observer to estimate and offset time-varying environment interference in unmanned ship trajectory tracking; based on a radial basis function neural network and an interference observer, an unmanned ship adaptive interference suppression controller is designed by using an adaptive vector backstepping method.

Disclosed in the present invention is a gain self-learning position axis control method for an electro-hydraulic proportional servo valve. In the axis control method, a nonlinear robust position axis controller with a gain self-learning mechanism is designed on the basis of a constructed gain self-learning mechanism and by incorporating the concept of dynamic surface control. For the position axis control problem of an electro-hydraulic proportional servo valve, the present invention can not only realize autonomous learning of a system gain, thereby simplifying the complexity of actual gain adjustment, but can also prevent the problem in respect of differential explosions in the traditional backstepping control of an axis control system of the electro-hydraulic proportional servo valve, thereby reducing the impact of measurement noise on control accuracy and achieving a high-precision tracking performance.

The invention discloses a performance control method of a limited nonlinear information physical system, which belongs to the technical field of intrusion tolerance control of information physical systems, and comprises the following steps of: establishing a control-oriented dynamic model of the limited nonlinear information physical system with external disturbance under spoofing attack; mathematical characterization is carried out on bounded multiplicative and additive spoofing attacks; a Lyapunov function based on a preset performance control method is constructed, and a system stability determination method based on a Nusb inequality is given; and coordinate change is introduced to meet full-state constraint, and a fixed time controller is designed by using a backstepping method, so that preset performance control of the limited nonlinear information physical system under spoofing attack and external disturbance is realized. The invention develops a fixed time intrusion tolerance controller based on a preset performance method, which can ensure the stable operation of a limited nonlinear information physical system under a spoofing attack with a small tracking error.

The invention discloses a finite time preset performance fault-tolerant control method for a two-degree-of-freedom rigid mechanical arm. The method mainly solves the problems that according to a conventional trajectory tracking control scheme, unknown disturbance in the external environment of a system cannot be estimated, disturbance cannot be reduced, and the stability of the system is affected. The method comprises the steps of constructing dynamical models of partial failure and complete failure of an actuator, designing a finite time preset performance function constraint tracking error, constructing a virtual controller and an actual controller based on a backstepping method, introducing an adaptive disturbance observer to compensate unknown external disturbance, and proving system stability through a Lyapunov function. According to the method, high-precision trajectory tracking of the mechanical arm under the actuator fault condition can be achieved, it is ensured that tracking errors converge to a steady-state area within the set time, and meanwhile dependence on external disturbance and system parameter priori knowledge is reduced.

The invention provides a quadrotor unmanned aerial vehicle fault-tolerant control method and system considering random disturbance, and belongs to the field of unmanned aerial vehicle flight control. The method comprises the steps that a random control system model fusing Wiener process random disturbance, actuator faults and input saturation is established, a six-degree-of-freedom control problem is decoupled into a position and attitude tracking sub-problem, and an expected attitude angle is inversely solved; applying constraints to the state variables by adopting a mixed constraint strategy fusing a delay state conversion function and nonlinear state dependence mapping; based on a self-adaptive backstepping method control framework, a controller is designed for six-degree-of-freedom sub-channels of the four-rotor unmanned aerial vehicle, and final input control signals of the degree-of-freedom sub-channels are obtained; and constructing a comprehensive Lyapunov function covering six degrees of freedom of the unmanned aerial vehicle, and proving that all signals of a closed-loop system are finally consistent and bounded. According to the invention, multiple complex factors can be coped with synchronously, the flight stability and reliability of the unmanned aerial vehicle in a complex environment are improved, and the method is suitable for multi-scene quadrotor unmanned aerial vehicle control.

The invention provides a hypersonic flight vehicle control method based on adaptive dynamic programming, and relates to the technical field of hypersonic flight vehicle control. The method specifically comprises the following steps: building an actual performance model of the hypersonic flight vehicle, and simplifying the actual performance model of the hypersonic flight vehicle; converting the simplified actual performance model of the hypersonic aircraft into a hypersonic aircraft model in a strict feedback form; designing a state feedback controller according to the thought of a backstepping method and a feedback linearization method, and then carrying out optimization compensation on the state feedback controller by utilizing a self-adaptive dynamic programming algorithm, namely, dynamically updating network weights on line by designing weight updating laws of an execution network and an evaluation network, so as to obtain a mathematical control surface angle control quantity; and converting the obtained mathematical control surface angle control quantity into an actual physical control surface angle control quantity, and inputting the actual physical control surface angle control quantity into an actual hypersonic aircraft model to realize a state tracking control closed loop of the whole hypersonic aircraft.

The invention relates to a self-adaptive fault-tolerant generalization control method for an autonomous underwater vehicle, which comprises the following steps of: considering primary and quadratic term damping effects of water, unknown constant matrixes of a mass matrix and an inertia matrix of the autonomous underwater vehicle and external interference factors; an actuator effectiveness index matrix is introduced to model the autonomous underwater vehicle into an under-actuated model, and meanwhile it is ensured that the resultant force of gravity and buoyancy is zero, and kinematics and dynamics equations of the autonomous underwater vehicle are obtained; a controller is designed based on a backstepping method, a position error and a saturation function are defined, a Lyapunov function is selected, the position error is driven to be within a preset fixed constant range, an estimation rule and a projection function are introduced for solving the problem of unknown parameters to calculate thrust and control input, and high-precision trajectory tracking control over the autonomous underwater vehicle is achieved. Compared with the prior art, the method does not need linearization or conversion dynamics, can solve the problems of fault tolerance and time-varying interference, is better in performance, and effectively improves the control precision and stability of the autonomous underwater vehicle.

The invention discloses an aircraft attack angle protection control method based on dynamic instruction correction, belongs to the field of flight control methods, and is used for solving the tracking control problem under the condition that the aircraft attack angle is limited. Firstly, based on an aircraft dynamics model, a backstepping method is utilized to design an adaptive controller to ensure stable tracking of a system, a virtual attack angle instruction part needs to be limited by adopting a saturation function, and a limited boundary value is provided by a subsequent protection system. And then, designing a prediction model representing correlation between the attack angle and the attack angle instruction and dynamics based on the designed closed-loop control system, reversely deducing a complex function relationship between the attack angle instruction and the system state and dynamics through the prediction model, and constructing an attack angle protection system. And finally, calculating an attack angle instruction boundary value through the prediction model and a system motion state trend under the current input, and correcting an original virtual attack angle instruction boundary so as to realize attack angle protection. According to the method, stable tracking of the system under attack angle constraint can be ensured, the residual attack angle in the envelope can be fully utilized, the maneuverability of the aircraft is improved, and the method has an engineering application reference value.

The invention discloses an unmanned ship event triggering adaptive tracking control method based on an improved optimization backstepping technology. The method comprises the following steps: S1, establishing a motion mathematical model of a three-degree-of-freedom unmanned ship considering external interference; s2, designing a fixed time disturbance observer based on the motion mathematical model, and estimating external marine environment disturbance without depending on velocity derivative information; s3, designing an event triggering mechanism based on the position error of the unmanned ship so as to measure a control input signal without depending on an additional sensor; and S4, adopting an improved optimal backstepping control strategy based on actor-commentator reinforcement learning, and directly estimating a cost function gradient by using a neural network so as to generate a final control law, thereby eliminating complex matrix differential operation required in a traditional method. The invention also discloses a system for realizing the method. According to the invention, the control precision, robustness and real-time performance of trajectory tracking of the unmanned ship in a complex marine environment are improved.

The invention provides a speed-measurement-free unmanned ship tracking control method and system based on absolute position sensing. Aiming at the problem that a following boat cannot acquire speed information due to failure of a pilot boat speed sensor or communication failure, a distributed finite time state observer is designed, and the speed of a pilot boat is estimated in real time by combining an absolute position and positioning information. And designing an auxiliary controller by adopting a backstepping method based on the observation speed, and constructing a stability constraint. And a model prediction control framework based on a distributed Lyapunov function is further proposed, so that the multi-unmanned ship system can realize expected formation trajectory tracking and attitude consistency only depending on self-sensing and positioning information, and meanwhile, the formation stability is ensured. According to the method, under the condition that the speed of the pilot ship cannot be obtained, the speed can still be accurately estimated, and the control strategy can be optimized online, so that the intelligent sensing, positioning precision, control performance and robustness of the unmanned ship formation system are remarkably improved.