221 results about "Actuator fault" patented technology

The invention discloses an intelligent automobile cooperative cruise safety control method under Dos attacks and physical faults, and relates to automobile intelligent safety and automatic driving. A hierarchical control framework is adopted and comprises an observer layer and a tracking layer. The method comprises the following steps: establishing a vehicle longitudinal dynamics model and a DoS attack model for DoS attack in a V2X communication network and the problems of sensor and actuator faults and parameter isomerism of a vehicle; a completely distributed self-adaptive preset time observer based on event triggering is designed for each following vehicle in the observer layer, and rapid and accurate estimation of the state of the pilot vehicle is achieved; the method comprises the following steps: constructing an augmentation system at a tracking layer, designing a distributed intermediate observer, carrying out online estimation and compensation on faults of a sensor and an actuator, designing a distributed active fault-tolerant controller based on a fault estimation value and a pilot vehicle state estimation value, and calculating a wheel driving torque to realize safe cruise control. Multiple threats of coexistence of network attacks and physical faults are effectively handled, and the stability and safety of the cooperative cruise system are ensured.

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 a distributed anti-interference fault-tolerant control method and a distributed anti-interference fault-tolerant control system for a multi-six-rotor unmanned aerial vehicle attitude system. The control method comprises the following steps: constructing a multi-six-rotor unmanned aerial vehicle attitude model based on a multi-six-rotor unmanned aerial vehicle attitude system model and interference uncertainty; designing a disturbance observer which is used for estimating the degree of external disturbance and actuator faults; and based on the output of the multi-six-rotor unmanned aerial vehicle attitude model and the degree of external interference and actuator fault, constructing a Lyapunov function by using a backstepping recursion technology, and designing a distributed anti-interference fault-tolerant controller for generating a control output signal to the multi-six-rotor unmanned aerial vehicle attitude model. According to the method, the Lyapunov function is constructed, so that output signals of all followers and leaders are synchronous, and errors are converged. Meanwhile, the general approximation characteristic of the neural network is utilized, the nonlinear term and the unmodeled dynamic are approximated online, and the model complexity is reduced.

The invention discloses a quadruped robot anti-disturbance motion control method based on reinforcement learning and application, and belongs to the field of robot motion control. Firstly, a self-adaptive propulsion control frame is provided, and a propeller and a leg movement system of the quadruped robot are deeply fused. And secondly, through cooperative training of a double-encoder system (a teacher encoder and a student encoder) and a predictor, hidden state extraction and environment disturbance reconstruction are realized, so that the robot adjusts a motion strategy in real time under complex scenes such as actuator faults and water flow interference. And finally, in combination with multi-stage reinforcement learning training and privilege information utilization, strategy network output is optimized, and a speed and trajectory tracking task is completed. The motion robustness of the robot under unknown interference and damage conditions is remarkably improved through cooperative control of the propellers and the legs, anti-disturbance decision of hidden state driving and dynamic reward function design. The method is suitable for amphibious environments, can adapt to diversified disturbance scenes without additional fine adjustment, and has high practicability and reliability.

The invention relates to the technical field of mechanical equipment fault diagnosis, and particularly discloses an attention mechanism CNN-based electric actuator fault feature extraction method and system. The method comprises the following steps: through a mode of combining simulation modeling and field acquisition, obtaining a fault feature of an electric actuator; obtaining multi-source data of the electric actuator in a normal state, a known fault state and an unknown fault state, and preprocessing and enhancing the multi-source data; and constructing a lightweight convolutional neural network model containing a cross-modal attention mechanism. According to the method, multi-source signals such as current, voltage and displacement can be effectively fused, weights of different modes and characteristics are automatically distributed, and the extraction capability of key fault characteristics is enhanced; accurate distinguishing between known faults and unknown faults is realized through multi-scale feature complexity measurement and a dynamic discrimination mechanism; in combination with domain self-adaption and an incremental learning mechanism, the model can migrate between simulation and real working conditions, and has self-expansion capability for a novel fault mode.

The invention discloses a modular mechanical arm actuator additive fault optimal fault-tolerant control method and device of a zero sum differential game, and relates to the field of robot control algorithms, and the method comprises the steps: representing a nonlinear damping characteristic through a joint friction torque, describing the dynamic interaction of multiple joints through a cross-linking coupling item, and determining the optimal fault-tolerant control of the additive fault of the modular mechanical arm actuator; a dynamical model containing faults is constructed. And uncertain items in the model are updated online by adopting a radial basis function neural network identifier, so that the model precision is improved. A performance index function is constructed based on position errors, actuator faults and controller input are regarded as two opposite parties of a zero and differential game, the performance index function is approximated through a single evaluation neural network, a Hamiltonian-Jacobi-Axaxi equation is approximately solved, and an optimal fault-tolerant control strategy is obtained. According to the method, the game theory is combined with the neural network, the dynamic unknown fault problem of the modular mechanical arm is effectively solved while the system energy consumption integration is reduced, and real-time optimal control over the modular mechanical arm is achieved.

The invention relates to an automobile finite time path tracking fault-tolerant control method considering steering actuator faults. The method comprises the following steps: firstly, establishing a vehicle dynamics model and a steering execution mechanism dynamics model, designing a path tracking control strategy by applying a model prediction control method, and establishing an upper-layer path tracking controller; then, on the basis of a differential driving auxiliary steering principle, a preset performance control method of finite time convergence and a nonsingular fast terminal sliding mode control theory are combined, and a steering actuator fault-tolerant controller is established; and finally, designing a torque distribution controller by adopting an optimal control theory, and solving an optimal four-wheel driving torque control quantity through quadratic programming. According to the method, the influence caused by the failure of the steering actuator can be effectively compensated, the safety and the stability of the vehicle are remarkably improved, and a feasible solution is provided for the fault-tolerant control of the steering actuator in a future intelligent vehicle path tracking scene.

The invention discloses a quadrotor unmanned aerial vehicle attitude fault-tolerant control method. The method comprises the following steps: S1, establishing a tracking error dynamic model of a quadrotor unmanned aerial vehicle attitude system; s2, designing a reduced-order fixed-time expansion state observer; s3, constructing an adaptive preset performance function; s4, designing a fast nonsingular terminal sliding mode surface and a fixed time reaching law based on an adaptive preset performance function and the lumped disturbance estimated value, and generating a posture virtual control quantity; and S5, according to the mapping relation between the attitude virtual control quantity and the attitude loop control moment, performing inverse solution to obtain the attitude loop control moment, and inputting the control moment into an attitude actuator to enable the attitude angle tracking error to converge to be near a balance point within a fixed time. Compared with the prior art, the four-rotor unmanned aerial vehicle attitude fault-tolerant control method has the advantages that strict constraint on attitude system response under the actuator fault condition is provided, it is ensured that unmanned aerial vehicle tracking errors meet preset transient state and steady state performance constraints, and meanwhile the vulnerability problem of preset performance is effectively avoided.

The invention discloses a distributed adaptive fault-tolerant formation tracking control method. The method comprises the following steps: constructing a longitudinal dynamic model of the intelligent agent and decomposing the longitudinal dynamic model into a speed subsystem and an attitude subsystem; constructing an actuator fault model, and reconstructing lumped uncertainty items in combination with the uncertainty of a longitudinal dynamic model and external disturbance; self-adaptive laws of a speed subsystem and an attitude subsystem are determined respectively, so that active compensation is carried out on lumped uncertainty items through an RBF neural network; and respectively determining control protocols of the speed subsystem and the attitude subsystem through a recursive backstepping method in combination with a general obstacle Lyapunov function. According to the method, under the harsh conditions that uncertainty and actuator faults exist, the key state safety boundary is continuously met, meanwhile, the high-quality time-varying formation tracking performance is kept, and the implementation complexity of a control system is effectively reduced.

The invention provides a self-adaptive dynamic programming self-triggering fault-tolerant control method for a flexible mechanical arm, and particularly relates to a flexible joint mechanical arm with a non-affine fault and an unknown control direction. The method comprises the following steps: firstly, designing a self-adaptive observer, and estimating a non-affine actuator fault and an unknown item caused by an unknown control input direction; constructing an evaluation neural network considering unknown terms by using the approximation capability of the neural network so as to approach a system cost function; then solving a Hamiltonian-Jacobian-Bellman equation to obtain approximate optimal control input for realizing ideal trajectory tracking and vibration suppression; meanwhile, a self-triggering mechanism is adopted, the next triggering moment is calculated according to the current system state, hardware requirements are reduced, and communication resources are saved. According to the method, control performance, energy consumption and information transmission constraint are considered, resource consumption can be reduced while quick response is achieved, and trajectory tracking and vibration suppression tasks of the flexible joint mechanical arm are safely and reliably achieved.

The invention discloses an electric actuator fault diagnosis method and system, and belongs to the technical field of fault diagnosis, and the method specifically comprises the steps: collecting the current, voltage, displacement, temperature rise and electromagnetic noise signals of an electric actuator in the operation process, and forming a multi-dimensional operation data set, performing time-frequency domain fusion processing on the multi-dimensional operation data to obtain a feature vector, constructing a health state track of the electric actuator, introducing an electromagnetic noise coupling factor into the health state track, performing evolutionary analysis on the health state track, extracting trend information related to a fault, and when the trend information exceeds a set threshold value, determining that the electric actuator is in a fault state. Comparing with a pre-stored actuator fault evolution sample, and judging the fault type and severity; according to the method, advanced identification and classification discrimination of potential faults can be realized through trend extraction and adaptive comparison, so that the comprehensiveness and accuracy of diagnosis are improved.

The invention relates to a mechanical arm actuator fault tolerance control method based on sliding mode control and a neural network, and belongs to the field of industrial robots. The method comprises the steps that modeling is conducted on the fault condition of a mechanical arm actuator, and a fault model is established; defining a joint angle tracking error, designing a sliding mode controller, and establishing a sliding mode surface of the sliding mode controller as linear sliding; designing a mechanical arm dynamic form according to the linear sliding surface and the fault model; estimating a total dynamic item by adopting an RBFNN neural network to obtain an estimated value of a system dynamic item, and taking the estimated value as an output quantity of the RBFNN neural network; designing a control law; calculating and generating a corresponding control input quantity according to a control law by adaptively updating a fault matrix of the weight matrix; and the mechanical arm actuator controls the mechanical arm according to the control input quantity so as to achieve fault compensation. According to the method, high-precision trajectory tracking is achieved under the condition that dynamics and actuator faults are unknown, and an accurate fault model or a fault detection system is not needed.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses a fault-tolerant control method, system and device for an unmanned aerial vehicle cluster and a medium. The method comprises the following steps: establishing a first dynamic model of a leader and a second dynamic model of each follower; designing a distributed expansion observer, and estimating state information of each follower and lumped interference formed by external disturbance of the follower and an actuator fault by using relative state information between each follower and a neighbor follower; determining the state information of the leader, and designing an event triggering mechanism according to a first error between the state information of each follower and the state information of the leader and a second error between the state information of each follower; and when the first error is greater than a first preset threshold value or the second error is greater than a second preset threshold value, determining a triggering event triggering mechanism, and controlling each follower in the unmanned aerial vehicle cluster according to the relative state information between the followers and the estimated lumped interference.

The invention provides a preset time adaptive fuzzy cooperative formation control method for a multi-water-surface-robot system, and the method comprises the steps: building a motion model containing uncertainty and actuator faults based on a speed state vector, and approaching the uncertainty through a fuzzy logic system; constructing a fuzzy logic expansion state observer containing a time-varying gain function to estimate an unmeasurable speed and compensate interference and uncertainty; based on observer output, distributed errors are defined, a barrier Lyapunov function constraint boundary is introduced, and uncertainty and faults are compensated in combination with fuzzy and multiplicative fault adaptive laws. According to the method, the multiple water surface robots can form and keep the expected formation within the preset time, the tracking error is converged to the small neighborhood of the original point, the method does not depend on initial conditions, and the control precision and robustness are improved.

The invention discloses an automobile engine multi-mode electronic control system and a control method thereof, and particularly relates to the technical field of automobile engine multi-mode electronic control, the system comprises a sensor module, a mode switching module, an execution control module and a diagnosis module, the sensor module collects parameters such as rotating speed and air inlet pressure in real time; the mode switching module judges four working conditions of idling, cruising, accelerating and pressurizing based on threshold logic; the execution control module calls strategies such as PID (Proportion Integration Differentiation) control and EGR (Exhaust Gas Recirculation) rate calculation aiming at different modes to realize accurate adjustment of parameters such as throttle opening and boost pressure; the diagnosis module monitors faults of the sensor and the actuator in real time through voltage out-of-limit detection, position deviation comparison and temperature correlation analysis.

The invention discloses an unmanned aerial vehicle rotor fault tolerance control method based on micro simulation optimization, and relates to the technical field of unmanned aerial vehicle rotor control, and the method comprises the steps: constructing a high-fidelity micro four-rotor fault simulation platform, building an unmanned aerial vehicle four-rotor dynamic model, and simulating a single-rotor fault of any severity through fault injection; passive fault-tolerant controller training based on learning is carried out, a quad-rotor hovering stability control test is carried out through a high-fidelity micronizable quad-rotor fault simulation platform, and a controller is trained through micronizable simulation and BPTT; and training a selector through a Selector-Controller strategy network, carrying out rapid learning of a fault-tolerant control strategy, outputting a control instruction, and carrying out high-precision adaptive control in a quadrotor fault scene. According to the method, switching of a controller is not needed, any actuator fault scene can be covered, and it can be ensured that multiple rotors can stably fly in the whole actuator fault process.

The invention discloses a large-scale wind turbine generator power load cooperative fault-tolerant control method. The method comprises the following steps: establishing a unit load and rotating speed control model considering a variable pitch actuator fault; according to the load and rotating speed control model, a fault-tolerant independent variable-pitch controller composed of a centralized variable-pitch ring, an independent variable-pitch ring and a fault-tolerant compensation ring is constructed for the three-blade variable-pitch actuator; and the fault-tolerant independent variable pitch controller inputs variable pitch given instructions corresponding to the blades to the corresponding variable pitch actuators, and the variable pitch actuators implement fault-tolerant variable pitch with the variable pitch given instructions as reference, so that power and load cooperative control under the fault working condition is achieved. According to the method, the optimization effect and the application capability boundary of pneumatic unbalanced load suppression of the wind wheel of the unit can be improved under the combined action condition of multi-source disturbance and variable-pitch actuator faults, meanwhile, the high stability of power output is guaranteed, and high-performance power-load cooperative control is achieved.

The invention provides an actuator fault diagnosis method and device based on a graph convolutional network and a medium, which are used for solving the problem of fault diagnosis of an actuator in an electromechanical system. According to the method, on the basis of a vibration signal, a CWRU data set is adopted as training and verification data, sliding window sampling and normalization processing are performed on the data set, and the generalization ability of a model is improved through a data enhancement technology. A graph construction method for vibration signals is designed, the signals are divided into nodes, edges between the nodes are constructed according to a time sequence and feature similarity, and mapping of the signals to a graph structure is achieved. And based on the constructed graph structure, designing a graph convolutional network (GCN) model to perform fault feature learning and classification. And finally, performing validity verification on the CWRU data set by using an actuator fault diagnosis method based on the graph convolutional network. The method has excellent diagnosis performance, can effectively identify faults, and shows relatively high robustness and accuracy under complex working conditions and noise environments.

This invention provides a method for reconstructing actuator faults in a heterogeneous multi-agent integrated energy system, relating to the field of fault diagnosis. The invention establishes a unified dynamic model for the agents; defines intermediate variables and constructs their dynamic equations; builds a global error dynamic system for distributed intermediate observers and agents; derives the stability criterion for the global error system based on Lyapunov stability theory, obtaining the state observer gain matrix for state estimation; loads the state observer gain matrix and the gain matrix for state estimation into each agent; and during the real-time operation of the agents, obtains the current state vector estimate and intermediate variable estimate, and calculates the reconstructed actuator fault value. This invention utilizes an output space coupling mechanism, enabling distributed collaboration between different energy networks without requiring a unified model dimension, thus breaking down the physical barriers to actuator fault reconstruction in integrated energy systems.

The application discloses a kind of high-temperature forging dynamic three-dimensional measurement-oriented sliding mode fault-tolerant control methods, and specific implementation steps include: establishing the discrete-time singular perturbation Markov jump state space model of high-temperature forging measurement system;Design probability dynamic event trigger mechanism, utilize internal dynamic variable intelligent judgment data transmission time to save bandwidth resources;For possible fraud attacks and actuator failure, build the corresponding attack model and fault model;Sliding surface and sliding control rate function are constructed;Deduce the sufficient condition for guaranteeing system reachability and closed-loop system finite time boundedness;Iterative solution controller gain and dynamic trigger parameters.The application considers network security, resource-constrained and actuator degradation and other multiple constraints under the high-temperature forging dynamic three-dimensional measurement scene, while guaranteeing the system finite time stability, significantly improves the robust cooperative control ability and operation safety of measurement system.

According to the fault-tolerant control method for the actuator fault in the urban sewage treatment process, stable control over the dissolved oxygen concentration and the nitrate nitrogen concentration in the urban sewage treatment process under the influence of the actuator fault is achieved. Firstly, a nonlinear observer is designed to accurately estimate an actuator fault; secondly, constructing a radial basis function neural network to accurately characterize the time-varying nonlinear dynamic characteristics of the sewage treatment process; a fault-tolerant controller based on self-adaptive dynamic programming is designed, and the problem that the dissolved oxygen concentration and the nitrate nitrogen concentration deviate from set values due to actuator faults is solved jointly by constructing an evaluation network and an execution network, training a neural network by adopting a strategy iterative algorithm, solving an approximate optimal control law and fusing a prior classical controller. Experimental results show that the method can realize fault-tolerant control of the dissolved oxygen concentration and the nitrate nitrogen concentration, and ensures stable operation of the urban sewage treatment process.

This invention discloses a distributed adaptive fault-tolerant control method and system for nonlinear inline systems, relating to the field of distributed control technology for nonlinear inline systems. The method includes: for each subsystem in the nonlinear inline system, constructing the actual output of each actuator in the subsystem based on the fault type of the actuator; the nonlinear inline system includes several subsystems; for each subsystem, constructing a local objective function, an error optimizer, an auxiliary system, high-gain parameters, and a control law, and generating an optimal error trajectory based on the local objective function and the error optimizer. At the upper level, this invention designs an error optimizer to generate the optimal error trajectory based on a local objective function that converges to zero; at the lower level, it designs a trajectory tracking fault-tolerant controller with the help of an auxiliary system, employing a dynamic high-gain approach to adaptively handle the effects of uncertain parameters, actuator faults, and unknown strong inline coupling.

A method of operating a vehicle includes receiving brake sensor data indicative of measured actuator outputs of a decentralized brake system's brake actuators. For each brake actuator, a vehicle controller calculates: a normalized corner output using the measured actuator output and a commanded target output for that brake actuator, and a weighted average using the normalized corner output of that brake actuator and a vehicle-calibrated weight value determined from the vehicle's current speed and steering angle. The controller calculates an actuator error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators, and detects an actuator fault when the actuator error percentage exceeds a vehicle-calibrated fault deviation threshold determined from the vehicle's current speed and steering angle. Responsive to the error percentage exceeding the fault deviation threshold, the controller commands the brake system to execute a brake action to remediate the actuator fault.

This invention discloses a fault-tolerant and vibration suppression control method for rigid-flexible coupled robots based on synchronous disturbance observation and dynamic event triggering. The method includes: establishing a large-deformation dynamic model of the rigid-flexible coupled robot mechanism and constructing rigid coordinates, flexible modal coordinates, and control targets; establishing an actuator effectiveness decay fault model and transforming the original underactuated system into an equivalent fully actuated model oriented towards trajectory tracking; designing a fixed-time synchronous disturbance observer based on error dynamics to estimate external disturbances and composite uncertainties online; constructing a dynamic event triggering mechanism and a time-synchronous fault-tolerant sliding mode control law to achieve synchronous convergence of the system state to the sliding surface within a fixed time; introducing a hybrid reference trajectory and virtual input to establish an augmented state model and designing a robust linear quadratic state feedback controller. This invention achieves coordinated control of trajectory tracking and flexible vibration suppression under conditions of external disturbances, actuator failures, and limited communication resources.

This application discloses a refined fault-tolerant cooperative control method for swarm aircraft based on dual-event triggering. First, considering the constraints of limited communication resources, an event-triggered communication mechanism is constructed to reduce the communication frequency between swarm aircraft. Second, a distributed observer is designed to estimate the aircraft reference command signal using discontinuous neighbor state information. Then, a Nussbaum function and an adaptive neural network method are employed to handle actuator faults and parameter uncertainties. Finally, a fractional-order sliding mode fault-tolerant control strategy based on the event-triggered control mechanism is designed, reducing the number of controller updates and achieving refined control of the swarm aircraft. This invention can be applied to fault-tolerant cooperative control of swarm aircraft formations under conditions of limited communication and computing resources.

This invention discloses a distributed fault detection method for large-scale industrial processes based on subspace identification. A fault detection unit is established on each subsystem of the large-scale system. Local residual generators are directly identified using process data from local and neighboring industrial subsystems, and the residual covariance matrix under healthy conditions is estimated. Actuator faults in neighboring industrial subsystems are decoupled, enabling the detection of faults in both local and neighboring industrial subsystems. Using this invention, a fault detection unit can be constructed within each industrial subsystem using only local and neighboring data, achieving high-performance fault detection for both local and neighboring industrial subsystems. This method boasts high detection rates, low false alarm rates, and low false negative rates, reducing computational and data transmission burdens and making it suitable for dynamic industrial processes.

The invention discloses an integrated control system for electric modification of an electric tractor, and belongs to the technical field of agricultural machinery. The system comprises a signal processing module, a health state evaluation module, a control decision module, an execution module and an optimization module, all the modules realize data interaction through the Ethernet, and the system is adaptive to heterogeneous hardware integration requirements after electric modification of a traditional fuel tractor. According to the invention, the health state evaluation module and the prediction model realize quick response and graded protection of high-voltage insulation, battery overheating and actuator fault scenes through clear quantification, and realize quantitative scoring of the health degree in the limitation of temperature, load and attitude coupling complex scenes; meanwhile, the time domain and frequency domain characteristics of the signals are extracted to provide a quantitative basis for evaluation, different actions of power reduction, speed limiting and emergency shutdown are triggered according to the health degree state, the situation that operation efficiency is affected by excessive protection is avoided, early warning can be conducted in the early stage of a fault, rapid protection can be conducted when the fault occurs, and the running safety and reliability of the tractor are improved.

The invention provides a distributed fault-tolerant control method and device for a multi-robot system, and relates to the technical field of robots, and the method comprises the steps: constructing a system dynamics model containing an actuator fault and a sensor fault, designing an intermediate observer for each follower robot, and carrying out the fault-tolerant control of the robot. The joint real-time estimation of the system state, the actuator fault, the sensor fault and the intermediate variable is realized, the estimation process does not need to know the boundary information of the fault amplitude and the change rate in advance, and does not need to meet the matching condition depended by a traditional observer, so that the adaptability and robustness of fault estimation are remarkably improved; on the basis, external state information of a leader and a neighbor robot is obtained from a communication network, a distributed cooperative fault-tolerant controller is constructed to generate an action control instruction, and the adverse effect of faults of an actuator and a sensor on the cooperative performance of the system is effectively compensated. And finally, all follower robots can stably and consistently track the motion state of the leader.

The application discloses a fault-tolerant control method for a permanent magnet synchronous motor with intermittent actuator faults, which adopts a fuzzy logic system to process unknown nonlinear dynamics. Through a fuzzy state observer, states that cannot be directly measured can be estimated. In addition, under the framework of dynamic surface technology and backstepping recursive technology, a fuzzy fault-tolerant control method for a permanent magnet synchronous motor system with intermittent actuator faults is proposed. By using Lyapunov stability theory, it is proved that all signals in the closed-loop system remain bounded. Finally, the effectiveness and feasibility of the method are verified through simulation results.

This invention discloses a path adaptive replanning control method and system for unmanned aerial vehicles (UAVs) based on actuator health status estimation. The method includes: acquiring the current position, velocity, and environmental information of the UAV; estimating the actuator health status based on the command acceleration output by the controller and the UAV's motion response; updating path planning parameters based on the actuator health status; determining whether a replanning trigger condition is met; generating a new local trajectory if the replanning trigger condition is met, and continuing to execute the current local trajectory if the replanning trigger condition is not met; generating a control layer reference position and reference velocity based on the current local trajectory; outputting a command acceleration based on the reference position and reference velocity, and obtaining the actual acceleration input through actuator efficiency, bias, and constraint effects; updating the UAV's motion state based on the actual acceleration input and entering the next cycle. This invention improves the safety, stability, and executability of the system in the event of actuator failure.