20 results about "Tracking error convergence" patented technology

The invention discloses a fast output feedback control method for a networked nonlinear system triggered by a dynamic event. By designing the dynamic gain, the dynamic gain is bounded, tracking error coupling is avoided, and meanwhile, the influence of a nonlinear term containing an unknown quantity and external disturbance on the system is compensated. In addition, a dynamic event triggering mechanism is provided based on the dynamic gain, and dynamic compensation of a triggering threshold value is achieved. And constructing a composite Lyapunov function by recursively constructing a virtual control quantity, and enabling the Lyapunov function to meet a fast finite time stability criterion in combination with parameter design of dynamic gain and nonlinear term power. Therefore, tracking errors are converged to a tight set, and the states of all closed-loop systems and observers are globally bounded. According to the method, rapid finite-time dynamic event triggering output feedback actual tracking control of a non-strict feedback system can be realized, and the method has urgent engineering application requirements and is of great significance in promoting the development of a networked nonlinear system control theory and an engineering technology.

The invention relates to a mobile robot preset performance safety tracking control method with state constraint and input time delay, and belongs to the technical field of mobile robot intelligent control. Aiming at the problems of control singularity, state overrun risk, time delay sensitivity and uncontrollable tracking performance in the prior art, a dynamic modeling method based on a car-like coordinate system is provided, and a kinematics-dynamics hierarchical controller is constructed by combining a constraint safety reference signal generation mechanism and a Hermite interpolation smoothing technology. Error dynamic constraint is realized by designing a preset performance function and a barrier Lyapunov function, an auxiliary signal is adopted to compensate an input time delay effect, and reinforcement learning is fused to optimize an anti-interference strategy. The method effectively eliminates the control singularity, strictly guarantees the state safety boundary, improves the time delay robustness, achieves the high-precision tracking error convergence, and is suitable for the safe and stable control of the mobile robot in a complex environment.

The invention discloses a fault-tolerant control method and device for a complex dynamic network system and a storage medium, and belongs to the technical field of fault-tolerant control research, and the method comprises the steps: obtaining a measurement output signal and a control input signal of each node in the complex dynamic network system; inputting the measurement output signal and the control input signal into a pre-designed adaptive sliding mode observer to generate a system state estimation value, and driving a state estimation error to be converged to zero through the system state estimation value; and based on the system state estimation value, solving a controller gain matrix through a pre-designed adaptive fault-tolerant controller, and driving the tracking error of the system state estimation value and the target node state to be converged to zero through the controller gain matrix. Through fault-tolerant control research of a complex network system, under the condition that the system is stable at the present stage, the system performance is further improved, the system performance is improved, and a correct value can be output under the condition that external attacks exist.

The invention relates to the technical field of underwater vehicle control, in particular to an underwater vehicle trajectory tracking method and system based on polynomial noise compensation. The method comprises the following steps: acquiring a theoretical trajectory, an actual trajectory and a velocity vector of an underwater vehicle; constructing a tracking constraint condition and a quadratic programming objective function; obtaining a time-varying linear equation through a Lagrange function and a KKT condition; introducing a logarithmic mapping activation function and a polynomial anti-noise compensation item to construct a continuous time DRZNN model; discretizing the model to obtain an iterative formula; solving a velocity vector sequence according to an iterative formula, and tracking the trajectory of the underwater vehicle according to the velocity vector sequence; the high-order time-varying noise is structurally counteracted through the polynomial anti-noise compensation item, the convergence direction is stabilized through the logarithm mapping activation function, the trajectory tracking error is converged to the preset precision in the complex disturbance environment, and the tracking precision and robustness of the underwater vehicle in the deep sea scene are remarkably improved.

The application discloses a kind of complex dynamic network system fault-tolerant control method, device and storage medium, belong to fault-tolerant control research technical field, its method includes obtaining the measurement output signal and control input signal of each node in complex dynamic network system;The measurement output signal and control input signal are input into the adaptive sliding mode observer designed in advance, generate system state estimation value, and through system state estimation value, drive state estimation error to converge to zero;Based on system state estimation value, through the adaptive fault-tolerant controller designed in advance, solve controller gain matrix, and through controller gain matrix drive system state estimation value and the tracking error of target node state converges to zero.The application is improved further to system performance under the condition that system is stable at present stage, improves the performance of system, and can output correct value under the condition that there is external attack.

The invention discloses a self-adaptive optimization control method of a direct current motor system with state constraint, which belongs to the field of automatic control design and application, and comprises the following steps: establishing a direct current motor mechanism model comprising key parameters such as motor armature resistance, inductance and rotational inertia through mechanism analysis; converting the direct current motor system with the state constraint into an unconstrained system; under a backstepping recursion technical framework, a feedforward virtual controller is designed to ensure tracking error convergence and ensure that system operation is always in a safety boundary, and stable operation of a direct current motor system is realized. And based on the reinforcement learning strategy and the approximation capability of the neural network, designing a feedback optimal controller so as to realize the target of energy consumption optimization of the direct current motor system. And a new technical path is provided for efficient and reliable control of the direct current motor under complex working conditions.

The invention discloses a time-varying self-adaptive asymptotic temperature control method for a fuel cell thermal management system, and the method comprises the following steps: S1, building a control-oriented multiple-input multiple-output thermal management system model based on the inlet and outlet temperatures of an electric pile, the double-circulation temperature dynamics and the internal heat exchange process of the system; s2, designing a novel time-varying command filter and introducing the novel time-varying command filter into a backstepping control framework in order to achieve a target of presetting temperature tracking error convergence time; s3, environment and system parameter perturbation are considered, a time-varying error compensator based on a smoothing sign function is combined, and a dual-channel time-varying self-adaptive asymptotic temperature tracking controller is provided to process unknown perturbation and compensate filtering errors; s4, selecting a proper Lyapunov function to prove that a closed-loop system is stable, and the temperatures at the inlet and the outlet of the galvanic pile can be gradually tracked to a reference value; according to the method, the problems of non-uniform temperature distribution and severe fluctuation of the electric pile caused by dynamic load change, parameter uncertainty and the like are solved, the operation efficiency of the battery is improved, and the service life of the battery is prolonged.

The application provides a multi-hydraulic-cylinder asymptotic tracking pre-determined performance adaptive control method of a digging-anchor integrated machine, which comprises the following steps: establishing a multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine, obtaining parameters of the multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine, and obtaining a state space expression of the multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine based on the parameters; setting a limited time pre-determined performance function to constrain tracking errors of the multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine; using an adaptive technology to estimate unknown parameters of the multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine and internal disturbances and external disturbances of the multi-hydraulic-cylinder position servo system of the digging-anchor integrated machine; and recursively obtaining a final controller by using a backstepping control theory, introducing an inequality and an integral bounded function, and realizing asymptotic tracking control. The final controller obtained by the application can make the tracking error converge in a limited time and stabilize more quickly.

This invention discloses a time-delay compensation control method for wave energy converters, belonging to the field of wave energy converter control technology. Based on the physical model of the wave energy converter, this method establishes the dynamic equations of the wave energy converter system. After defining the maximum power control problem of the wave energy converter, the dynamic equations of the wave energy converter system are transformed into a second-order linear system form, obtaining the system state variables, system parameters, and input time delay. After constructing an auxiliary system, an error variable is defined. Based on the error variable, a virtual control law is designed, and then an actual control law is constructed. By constructing the characteristic equation, the critical time delay threshold of the wave energy converter system is calculated. Lyapunov stability analysis proves that the system tracking error converges to a preset small neighborhood, thus completing the time-delay compensation control method for the wave energy converter. This invention can ensure that the critical time delay threshold of the system is always greater than the actual input time delay by adjusting the control parameters, guaranteeing system controllability.

The invention discloses an underwater robot self-adaptive control method based on a static-dynamic high-gain observer. The underwater robot self-adaptive control method comprises the following steps: establishing a six-degree-of-freedom nonlinear dynamic model of an underwater robot; performing model simplification through coordinate transformation and motion hypothesis to obtain a vertical plane dynamic model; abstracting the simplified model into a second-order random uncertain nonlinear system; designing a static-dynamic hybrid high-gain observer to estimate an unmeasurable state, wherein the gain of the static-dynamic hybrid high-gain observer is composed of a static gain and a dynamic gain which is adaptively updated according to an output tracking error; designing an output feedback controller based on the state estimation value; stability analysis is carried out through a Lyapunov It method, and it is proved that a closed-loop system is globally bounded and tracking errors are converged. According to the method, through collaborative design of dynamic and static gains, the problems of insufficient state estimation precision and random disturbance adaptability are effectively solved, and the trajectory tracking precision, the anti-interference capability and the system stability of the underwater robot in a complex marine environment are improved.

The invention discloses a robust adaptive trajectory tracking control method based on a nonlinear extended observer, and belongs to the technical field of intelligent control and nonlinear adaptive robustness. The method comprises the following steps: establishing a kinetic model of a nonlinear system and obtaining tracking error dynamics; constructing a mixed performance function; mapping the constrained trajectory tracking error into an equivalent unconstrained conversion variable; the nonlinear extended state observer performs real-time estimation and feed-forward compensation on system lumped disturbance; designing an adaptive evaluation neural network weight updating law and an optimal control strategy under the nominal system in combination with the nominal system; and constructing a time-varying gain mechanism with a preset time characteristic, and constructing a composite optimal controller. According to the method, it can be guaranteed that the disturbed nonlinear system converges the tracking error to the steady-state limit within the preset time, the whole process meets the preset transient performance envelope, and the trajectory tracking precision and robustness under complex disturbance are remarkably improved.

A kind of unmanned aerial vehicle (UAV) pre-scheduled time fault-tolerant cooperative formation control method under full state constraints is provided. A nonlinear dynamic model of UAV with external unknown disturbance is established, and the model is generalized as a general expression considering the actuator fault condition. A time-varying nonlinear conversion function is used to convert the UAV cluster system under full state constraints into an unconstrained system. Then, based on the converted unconstrained system, the UAV cluster system is divided into an attitude subsystem and a position subsystem based on the adaptive backstepping control algorithm according to the topological structure between the UAV leader and the follower, and a tracking error is defined. A virtual control law is designed to stabilize the corresponding subsystem, so that the tracking error converges, and a cooperative formation controller is designed to track the leader trajectory within a predetermined time. Under the premise that all states do not violate the specified constraints, the UAV follower can track the leader trajectory well, and the feasibility condition limitation on the first virtual control law is eliminated.

The application discloses a sliding mode control method based on fixed time control theory, comprising the following steps: obtaining a strict feedback system expression of a motor servo system, designing a fixed time non-singular terminal sliding mode surface based on an auxiliary switching function, recursively deriving a sliding mode controller based on the strict feedback system expression and the fixed time non-singular terminal sliding mode surface, and finally converging the tracking error time of the motor servo system to a preset range according to the obtained sliding mode controller. The application designs a novel fixed time non-singular terminal sliding mode surface, so that the recursively derived sliding mode controller can converge the tracking error of the motor servo system to the preset range, effectively improves the convergence speed, effectively avoids the singularity phenomenon, and guarantees the convergence precision.

The present application belongs to the field of quadrotor unmanned aerial vehicle tracking control technology, and specifically discloses a height and attitude tracking control method and system for quadrotor unmanned aerial vehicle. In the height and attitude tracking process of the quadrotor unmanned aerial vehicle, the present application converges the tracking errors of the height subsystem and the attitude subsystem of the aircraft in the desired neighborhood by designing a virtual controller, a first-order low-pass filter, an error compensation system, and an actual control signal. The present application can not only avoid the problem that continuous-time control is affected by the computer sampling time, but also ensure that the attitude and height tracking errors of the quadrotor unmanned aerial vehicle converge to any desired neighborhood in the presence of external disturbances and system uncertainties, and all signals in the closed-loop system are bounded. In addition, the present application also provides specific examples, which well verify the effectiveness of the tracking control method.

The invention discloses a data guide type expert knowledge learning tracking control method for an unmanned autonomous vehicle and an unmanned autonomous vehicle control system, and belongs to the technical field of unmanned driving and intelligent control, and the method comprises the steps: based on expert knowledge, i.e., the expected value and standard deviation of key physical parameters of the vehicle, utilizing a statistical three-sigma criterion to obtain a data guide type expert knowledge learning tracking control system; constructing a high-confidence feasible interval for the uncertain parameters; designing a smooth projection operator based on expert knowledge, and embedding the smooth projection operator into an iterative learning updating law to ensure that the parameter estimation value is always kept in the high confidence interval; under an instruction filtering backstepping control framework, a self-adaptive iterative learning controller is designed, and transverse and longitudinal dynamic accurate control over the vehicle is achieved; through continuous learning and optimization in repeated tasks, the tracking error convergence of the vehicle is ensured, and the convergence speed and the control robustness are remarkably improved. According to the invention, a stable and reliable technical scheme is provided for realizing high-precision and high-efficiency path tracking of the unmanned vehicle.

The present invention discloses a sliding mode control method based on an improved reaching law, which relates to the field of numerical control technology. The method comprises obtaining a position spline reference trajectory, establishing a feed system degree of freedom model, obtaining a sliding mode surface, combining the sliding mode surface with a power reaching law with a hyperbolic tangent function term to control a sliding mode controller, inputting the position spline reference trajectory into the sliding mode controller to obtain a control law, inputting the control law into the ball screw feed system to obtain the true value of the disturbance and the output of the system, negatively feeding back the output of the system to the input of the sliding mode controller, and obtaining the control law, the true value of the disturbance, and the output of the system. The disturbance estimate is calculated through a nonlinear disturbance observer, and the sliding mode controller is adjusted to converge the tracking error to zero. The sliding mode control method based on an improved reaching law provided by the present invention achieves higher tracking performance, accurately compensates for external disturbances, improves system robustness, and solves the problem of observation errors caused by system chattering in the prior art.

The application discloses a UAV fault-tolerant control method and device based on preset performance, a terminal and a medium. When it is detected that any one execution mechanism of a UAV fails, the current expected lift direction parameter of the UAV is determined according to the deviation between control target data and real-time operation parameters; the deviation between the expected lift direction parameter and the actual lift direction parameter is taken as a system tracking error, when the tracking error does not satisfy a preset stability threshold condition, the control law parameter of the UAV is determined according to a preset control law parameter calculation formula and a terminal sliding mode surface control model, the flight state of the UAV is adjusted until the system tracking error satisfies the preset stability threshold condition, and the preset performance theory and the terminal sliding mode control are combined in the inner loop attitude loop controller to ensure that the main shaft tracking error converges to a preset neighborhood within a limited time, so that the flight stability of the UAV under the condition that the execution mechanism fails is improved.

The invention relates to the technical field of multi-agent system control, solves the technical problem of lack of an effective active compensation mechanism for unknown nonlinear dynamics and actuator fault problems in an underlying physical system in the traditional technology, and particularly relates to an adaptive fault-tolerant control method for heterogeneous multi-agent distributed Nash equilibrium optimization. By constructing a hierarchical game control framework, hierarchical decoupling is carried out on high-level game strategy optimization of a decision-making layer and bottom-layer trajectory tracking of a control layer; and establishing an adaptive fault-tolerant control law, and configuring adaptive update law parameters based on a Lyapunov stability theory, so that a control layer can track a Nash equilibrium reference strategy. According to the method, distributed game control of the heterogeneous multi-agent system can be realized under the condition that nonlinear uncertainty and actuator faults exist, so that tracking errors are converged to a small tight set, accurate tracking of an optimal strategy is realized, and the fault-tolerant capability and robustness of the system are improved.

The present invention discloses an adaptive neural specified time trajectory tracking control method for an under-actuated ship with input saturation. By combining a preset performance control method with finite time theory and introducing an additional control method and a saturation compensation mechanism, the offline customization of tracking convergence time, position error and speed error is guaranteed, and the under-actuated vector design is realized; the virtual control law is designed by designing an auxiliary dynamic filter to avoid the differential inflation phenomenon; by considering internal and external disturbances and actuator saturation conditions, the ship longitudinal control law and the ship steering control law are designed for the under-actuated ship based on an adaptive neural network and a single parameter learning algorithm, and the defects in design and control performance between the adaptive neural network, actuator saturation compensation technology and specified performance control are coordinated. In addition, the present invention can ensure that the ship tracking error is limited to a predefined range within the specified time, overcome the influence of input saturation on the tracking error convergence performance, and make the position error and speed error in the tracking control reach the specified range within the predefined convergence time.

The invention discloses an under-actuated water surface unmanned ship trajectory planning method and system capable of reducing output redefinition errors. According to the method, aiming at the tracking error problem caused by changing a controlled object from a centroid to an offset point by using output redefinition, each point of an expected trajectory is translated, and sideslip angle compensation is introduced in the translation direction, so that a new compensation offset point expected trajectory is generated. When the deviation point of the unmanned ship tracks the new trajectory, the mass center of the unmanned ship can accurately move along the original expected trajectory. The system comprises a trajectory acquisition module, a kinematics parameter calculation module, a compensation trajectory generation module and a tracking control module which are used for implementing the method. According to the method, geometric tracking errors caused by output redefinition and a sideslip effect can be eliminated from the source, tracking error convergence of the mass center of the unmanned ship is ensured, and the precision and robustness of trajectory tracking are remarkably improved.