407 results about "Tracking error" patented technology

The invention relates to the technical field of multi-axis servo systems, and discloses a synchronous control method, device and equipment for a multi-axis servo system, and the method comprises the steps: measuring a mechanical coupling relation parameter, a motor dynamic characteristic parameter and a sampling delay time parameter of the multi-axis servo system, and substituting the parameters into a state equation modeling formula, calculating to obtain a discrete time system state matrix; performing Z transformation processing on the discrete time system state matrix and calculating frequency response characteristics to obtain a transfer function matrix and a target coupling axis pair set; executing hierarchical optimization to obtain a preliminary control instruction; a trajectory tracking error and an inter-axis synchronization error are calculated and substituted into the optimization objective function for sampling delay compensation processing, and a compensation control instruction is obtained; the compensation control instruction is processed in real time, synchronous control signals are output to the servo shafts to achieve multi-shaft coordinated movement, and the synchronous control precision in the multi-shaft servo system is improved by accurately recognizing the key coupling shaft pairs and the sensitive frequency points.

The invention discloses a data-based predefined time heterogeneous multi-agent formation collision avoidance method. The method comprises the following steps: establishing a nonlinear heterogeneous multi-agent system; designing a bimodal artificial potential field function to perform dynamic obstacle avoidance and prevent regional escape; establishing a self-adaptive robust controller used for generating an obstacle avoidance safety motion trail of the root leader; designing a self-adaptive formation zooming mechanism of the leader, and constructing a predefined time affine observer of the follower based on the self-adaptive formation zooming mechanism; designing a unified obstacle function; constructing a virtual control law for processing tracking errors based on the unified obstacle function; designing a neural network estimator; designing controllers of the leader and the follower according to the virtual control law; and forming a collision avoidance decision of the heterogeneous multi-agent formation based on a self-adaptive robust controller, a predefined time affine observer, a neural network estimator and controllers of the leader and the follower. According to the method, safe, efficient and robust cooperative control of the formation in a complex environment is realized, and the safety and task execution efficiency of the heterogeneous multi-agent formation in a limited and unknown environment are remarkably improved.

The invention discloses a self-adaptive logarithmic terminal sliding mode control method and device based on observation, and relates to the technical field of sliding mode control. According to the method, the terminal attractors are nested into the natural logarithmic function, terminal sliding mode control and logarithmic sliding mode control are effectively combined, rapid convergence can be achieved near and far away from the balance point, the global dynamics of the sliding mode surface is improved, and the sliding mode control efficiency is improved. Meanwhile, a self-adaptive logarithmic terminal sliding mode controller is constructed on the basis of super-spiral sliding mode control and self-adaptive gain, the self-adaptive gain is updated according to a self-adaptive law, the self-adaptive law is constructed on the basis of a preset nonlinear obstacle function, intelligent self-adaption of the super-spiral sliding mode control gain is achieved, and therefore sliding mode variables are restrained within a preset boundary; and the interference estimation error is quickly converged based on the estimation of the observer on the interference, the global quick convergence of the state tracking error is realized under the constraint of the sliding mode variable, the steady-state precision is high, the chattering phenomenon is weakened, and the convergence efficiency and the control precision are improved.

The invention discloses a self-adaptive safety control method of a nonlinear MIMO system under intermittent DoS attack, which comprises the following steps: establishing a nonlinear MIMO system model suffered from intermittent DoS attack, and the system model is in a strict feedback form and comprises an unknown nonlinear function and bounded external disturbance; the DoS attack causes periodic interruption of a communication link from a sensor to a controller, so that actual measurement data is unavailable in an attack activation period; designing a switching type adaptive state estimator; coordinate transformation is carried out by introducing a filter, and a system error is decomposed into a tracking error and a dynamic surface filtering error; a Lyapunov function is constructed; performing stability analysis in stages; designing an adaptive law to update unknown parameter estimation values of the FLS; and a final event triggering controller is designed, and the event triggering controller is combined with a virtual controller to track an error compensation term and an FLS approximation term. The problem that the state cannot be measured is solved.

The invention relates to the technical field of mechanical arm control, in particular to a self-adaptive fuzzy fixed time control method based on an output-limited mechanical arm, and the method comprises the following steps: S1, constructing a mechanical arm dynamic model; s2, setting constraint conditions of an output state of the mechanical arm dynamic model; s3, defining a tracking error and a virtual control law of the mechanical arm dynamic model; s4, on the basis of output state limitation and fixed time control, an actual control law is designed to serve as input of the mechanical arm dynamic model, and an adaptive law is constructed; and S5, a three-level logarithmic obstacle Lyapunov function is constructed, the three-level logarithmic obstacle Lyapunov function is combined with the virtual control law, the actual control law and the self-adaptive law step by step and substituted into the virtual control law, the actual control law and the self-adaptive law, and then it is guaranteed that the output state of the mechanical arm dynamic model does not exceed the preset safety boundary according to the actual fixed time control lemma. According to the invention, high-precision trajectory tracking can be realized on the premise of ensuring safe operation of the mechanical arm.

The invention discloses an intelligent numerical control machine tool contour error prediction compensation system and a control method thereof, and belongs to the technical field of industrial control and intellectualization, the intelligent numerical control machine tool contour error prediction compensation system comprises a parameter setting module used for setting system parameters and processing parameters of a numerical control machine tool and importing external planning data and configuration files; the online planning module is used for acquiring planning data online; the core control module is used for controlling the executing mechanism to realize multiple motion modes; the data monitoring module is used for dynamically collecting real-time monitoring data in the machining process of the executing mechanism; the neural network prediction module is used for performing tracking error prediction on the plurality of processing single axes based on a neural network model; and the error intelligent control module is used for carrying out iterative optimization on the processing track. Through modular design, all links of numerical control machining are integrated into a unified system, so that the technical problems that a control system of a traditional numerical control machine tool is poor in function expansibility, low in resource utilization rate, high in development threshold, tedious in process and the like are solved.

The invention discloses a non-cooperative target-oriented ocean robot cluster tracking optimization control method, which comprises the following steps of: firstly, respectively establishing a linearized ocean robot cluster dynamic model and a non-cooperative target dynamic model for an ocean robot system working in a water surface environment; then constructing a state tracking error system; designing a finite time sliding mode control protocol, and solving an equivalent state tracking error system moving on a sliding mode surface; a performance index function of the ocean robot cluster system is defined, a distributed state feedback nominal optimization control protocol is designed, and it is ensured that the performance index function meets global Nash equilibrium; and finally proving that the distributed state feedback nominal optimization control protocol can ensure the asymptotic stability of the equivalent state tracking error system by utilizing a Hurwitz stability theory. According to the method disclosed by the invention, the optimal tracking control of the ocean robot cluster system on the non-cooperative target with an uncertain control strategy can be realized under the interference of water surface storm waves in a complex ocean environment.

The invention discloses a double-capacity water tank control method based on multi-target reward Q learning, and belongs to the technical field of machine learning and automatic control. The method comprises the following steps: firstly, establishing a discretization mathematical model of a double-capacity water tank liquid level control system, and designing a multi-target reward function; secondly, empirical data are stored only when the liquid level tracking error exceeds the limit or the control quantity suddenly changes, and sampling weights are distributed according to award absolute values; and finally, updating the Q table based on the time difference error, and performing closed-loop real-time control on the double-tank water tank according to the dynamically adjusted PID parameter. According to the method, a five-dimensional reward function is designed, and multi-index dynamic balance is realized through linear weighting; the empirical tuple is stored only when the liquid level tracking error exceeds the limit, and the quick response requirement of the dynamic time-varying scene of the double-capacity water tank is met; dimensionality reduction is performed on a continuous state space by adopting a non-uniform grading strategy, so that the calculation complexity is remarkably reduced; a perception-decision-execution integrated framework is constructed, and the dependence of a traditional control method on a mathematical model of the water tank is abandoned.

The invention relates to a trajectory tracking optimization control method for a two-connecting-rod mechanical arm with an incomplete measurable state, and belongs to the technical field of control engineering. The method utilizes a preset performance function and an event triggering mechanism to implement event triggering model prediction optimization control: establishing a mathematical model of a two-connecting-rod mechanical arm system, and obtaining a state-space equation of the system according to the mathematical model; designing an extended state observer, setting a preset performance function, adjusting parameters of the preset performance function to meet transient performance requirements, and performing error conversion on an output tracking error according to the transient performance requirements; designing an event triggering model predictive controller based on a preset performance function; solving an optimization problem to obtain an optimization control input variable and a state variable; and designing a self-adaptive time-varying trigger mechanism to reduce the optimization times of predictive control. The method integrates the advantages of a preset performance control method, an event triggering mechanism and a prediction control method, has the advantages of high response speed, high positioning precision, small calculation amount and the like, and has relatively good tracking performance and control flexibility.

The invention discloses a preset performance asymptotic control method for a hydraulic servo system with control signal unknown dead zone compensation. The preset performance asymptotic control method comprises modeling of the hydraulic servo system with the control signal unknown dead zone and the preset performance asymptotic control method with the dead zone compensation. Firstly, in order to weaken the influence of an unknown dead zone, a smooth inverse dead zone model is introduced, and parameterization processing is carried out to facilitate control design; secondly, a decreasing constraint is applied to the tracking error by defining a preset performance function; a parameter adaptive law is further designed, and in combination with a robust technology based on interference upper bound estimation, it is ensured that the system has presettable performance and asymptotic stability under bounded time-varying disturbance. According to the control method, the preset performance and the asymptotic stability of the hydraulic servo system containing the control signal unknown dead zone under the time-varying interference are achieved for the first time.

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 the technical field of optimal tracking control, and provides an optimal tracking control method, device and equipment based on adaptive dynamic programming. Constructing an augmented system according to a tracking error and a reference trajectory of the system (the system is constrained by part of unknown disturbance), and designing a corresponding value function; based on the designed value function, the H infinity tracking problem is converted into a zero sum game, and a corresponding Hamilton-Jacobi-Isaacs (Hamilton-Jacobi-Isaacs, HJI) equation is constructed; and the evaluation-execution-disturbance network approximates the HJI equation, the optimal control strategy and the worst disturbance strategy are solved, and the optimal control strategy is applied to the controller. According to the method, the control input and the disturbance input during neural network training are updated by using a double-event triggering mechanism, and the resource utilization efficiency is improved. According to the optimal control input data, external disturbance factors suffered by the controlled system are considered, so that the robust performance of the obtained optimal control input data is improved.

The invention discloses a VSG control method for oscillation instability, and relates to the technical field of wind power control, and the method comprises the steps: determining the sequence impedance of a VSG grid-connected system according to a VSG inverter structure and a control circuit model; generating and analyzing a Bode diagram according to the sequence impedance of the VSG grid-connected system and the equivalent impedance of the power grids with different intensities to obtain a phase margin set; when at least one phase margin which is corresponding to the power grid intensity meeting the first preset condition and is a negative value exists, voltage and current tracking errors are calculated; calculating a current inner loop control rate according to a sliding mode surface function corresponding to the integral sliding mode surface, the voltage and current tracking errors and an exponential reaching law; when it is judged that the sliding mode surface function meets a second preset condition, an actual current measurement value is obtained; when the actual current measurement value does not conform to a third preset condition, the VSG grid-connected system sequence impedance is deduced again until no negative phase margin exists in the phase margin set; the steady-state error can be effectively eliminated, and the control performance is improved.

The invention provides a three-order hydraulic servo position control system active-disturbance-rejection control method based on friction compensation, and relates to the technical field of fluid transmission and control, and the method comprises the steps: S1, building a state space model of a three-order hydraulic servo position control system, building a linear expansion state observer, and obtaining a linear active-disturbance-rejection controller of the three-order hydraulic servo position control system; s2, nonlinear time-varying disturbance compensated by the third-order hydraulic servo position control system is converted into a tracking error compensation item controlled by a friction compensation algorithm; s3, verifying the stability of the closed-loop third-order hydraulic servo bit control system through error convergence before and after feed-forward compensation; and S4, the control voltage of the third-order hydraulic servo position control system is input, and nonlinear friction feedforward compensation control of the third-order hydraulic servo position control system is achieved. According to the method, a model-free control strategy is adopted, an innovative solution path is provided for friction suppression and self-adaptive friction compensation, and the control precision and robustness of the hydraulic servo system are improved.

The invention discloses a permanent magnet synchronous motor control method of an adaptive fractional order fast terminal sliding mode. The method comprises the following steps: firstly, constructing a mathematical model of the permanent magnet synchronous motor in a d-q axis rotor rotating coordinate system; then designing a fractional order fast terminal sliding mode surface, and solving an equivalent control law of sliding mode control based on the designed fractional order fast terminal sliding mode surface; performing adaptive design on the switching control gain and the boundary layer thickness to obtain an adaptive switching control law; and integrating the equivalent control law and the adaptive switching control law to obtain a total control law. Compared with existing surface-mounted permanent magnet synchronous motor sliding mode control, the surface-mounted permanent magnet synchronous motor sliding mode control method introduces a fractional order fast terminal sliding mode surface on the basis of a traditional integral sliding mode so as to reduce system buffeting and ensure that tracking errors converge in finite time, and meanwhile designs a self-adaptive control law of switching control rate gain and boundary layer thickness. The uncertainty influence of external disturbance is counteracted, and the robustness of the system is improved.

The invention belongs to the field of automatic control, and particularly relates to a nonlinear system dynamic gain global trajectory tracking control method based on a self-adaptive neural network observer, which comprises the following steps: converting an uncertain nonlinear system model with unknown interference according to the requirement of output feedback control to obtain a first nonlinear system model; enabling an unknown nonlinear continuous function in the first nonlinear system model to be expressed as a function only containing an output signal and other system state estimation values; performing approximate approximation on an unknown nonlinear continuous function in the first nonlinear system model by using the first radial basis function neural network vector to obtain a second nonlinear system model; designing a second radial basis function neural network vector to construct a dynamic gain state observer of the second nonlinear system model, and obtaining an estimated value of a system state and an estimated value of an unknown nonlinear continuous function in the model; according to an inversion control method, defining a dynamic system tracking error index containing an intermediate virtual control signal, designing a Lyapunov function, and obtaining a change rate of a dynamic gain, a weight adaptive update rate of a second radial basis function neural network vector, and a control rate of the intermediate virtual control signal and a system input signal; different from most existing nonlinear system control methods, the method combines a novel dynamic gain neural network observer with an inversion controller with dynamic gain, and provides a robust global trajectory tracking control solution for a dynamic system operating under uncertain conditions.

The invention relates to an iterative learning control method for a non-repetitive time-varying system average operator, and the method comprises the steps: constructing a discrete dynamic model which allows system parameters to change in a non-repetitive manner along with the time and the number of iterations, and generating an expected trajectory and a tracking error of dynamic truncation; performing dynamic truncation processing on the randomly changed track length through random variables of Bernoulli distribution to generate an optimization correction error signal; constructing a variable track length average operator based on weighted average and correction error signals of historical control input, designing an iterative learning control law, and verifying the convergence of the iterative learning control law; and finally, the tracking precision and robust stability of the system under the variable trajectory length and variable initial state are verified through simulation. The method breaks through the limitation of traditional iterative learning control on hypotheses such as a fixed system model and a fixed test length, solves the problem of tracking failure of a non-repetitive time-varying system caused by parameter drift and trajectory abrupt change, does not need to depend on an accurate model or a large amount of data training, and has algorithm conciseness, real-time performance and interpretability.

The invention belongs to the technical field of unmanned ship control, and particularly discloses a control method of a fixed time event triggering terminal sliding mode with preset performance constraints. The control method comprises the following steps: S1, establishing an all-drive model of a multi-under-actuated unmanned ship system; s2, designing a fixed time disturbance observer; s3, constructing a cooperative tracking error system according to the cooperative control target and the interactive topological structure; s4, restraining and converting the cooperative tracking error by using a preset performance function, and updating a cooperative tracking error system; and S5, constructing a relative threshold event triggering mechanism, designing a distributed event triggering-fixed time terminal sliding mode controller, generating an actuator control instruction, and realizing cooperative tracking control of the system through an output instruction of an actuator. According to the method, the problem of fixed-time cooperative tracking control under the preset performance constraint is solved, two indexes of'rapid cooperative control 'and'communication resource saving' are realized at the same time, and the method is applied to a cluster scene of multiple unmanned ships.

The invention discloses an electro-hydraulic servo system finite time accurate tracking control method and system. The method specifically comprises the steps that a mathematical model of a single-rod electro-hydraulic position servo system is established; based on a multilayer feedforward neural network, constructing a finite time neural network extended state observer, and estimating matching and non-matching unknown function disturbances and system states suffered by the single-rod electro-hydraulic servo system; constructing a finite time accurate tracking control algorithm of the single-rod electro-hydraulic servo system for model uncertainty compensation, and designing a finite time multilayer neural network adaptive law with a fractional order; and an initial value of a neural network weight parameter, an adaptive law matrix and a controller parameter are selected to realize the compensation of the uncertainty of a system model, so that the output of the system tracks an expected control target. According to the method, the steady-state tracking error of the single-rod electro-hydraulic servo system controller is reduced in finite time, the uncertainty compensation capability of the model is improved, and the tracking precision and the tracking speed of the single-rod electro-hydraulic servo system are improved.

A finite time dynamic mechanical arm control method based on a speed reconstruction strategy comprises the steps that firstly, a mechanical arm system physical model containing joint torque is constructed, joint tracking errors are defined, and a mechanical arm system state space model is obtained; 2, constructing a finite-time high-bandwidth gain speed estimator, defining a state estimation error, and obtaining an estimation error dynamic equation; 3, defining an auxiliary state to obtain an auxiliary state dynamic equation; 4, constructing a finite time non-recursive adaptive controller; and 5, obtaining a final input torque of the controlled system, and outputting the final input torque as a joint torque. According to the method, through the processes of error modeling, state estimation, auxiliary conversion, control law design and closed-loop feedback, the dynamic tracking problem of the mechanical arm is converted into the finite time convergence problem of the error state, meanwhile, dynamic gain and robust compensation are introduced, the adaptability of a system to parameter uncertainty and external disturbance is improved, and the system reliability is improved. And a high-precision and high-robustness control target is realized.

The invention discloses a two-degree-of-freedom prediction control method of an LCL filtering type three-phase grid-connected inverter system, and belongs to the field of power electronic converter control. A prediction control reference instruction is obtained by sampling parameters of inverter side current, capacitor voltage, network side current and power grid voltage at the moment k, and a continuous and discrete model of an LCL filtering type three-phase grid-connected inverter system is established; designing a control function based on a grid-side current reference tracking error and a gradient thereof, and establishing a prediction model; constructing a prediction cost function based on a control function, and obtaining a prediction control reference instruction by using a minimum value of the prediction cost function; and determining an optimal voltage vector and an action duty ratio according to the prediction control reference instruction, generating a control pulse signal according to a symmetrical five-section pulse mode, and acting on each switching tube in the inverter to realize prediction control of the LCL filtering type three-phase grid-connected inverter system. The method is simple in step, convenient to use, constant in switching frequency and good in stability.

The invention discloses a numerical control system feed-forward compensation method based on an edge controller, and the method comprises the steps: enabling the edge controller to obtain a machine tool instruction and a machine tool reality of a numerical control system in real time, calculating a tracking error, calculating a feed-forward compensation amount through an algorithm, transmitting the feed-forward compensation amount to the numerical control system, and installing a PLC function module in the numerical control system. And transmitting the received feed-forward compensation quantity to a servo feed-forward channel through a functional block, thereby realizing the feed-forward compensation function of the numerical control system. Through cooperation of edge calculation and a numerical control system, a feed-forward compensation algorithm is decoupled from a main controller, and high-precision real-time compensation is achieved through the parallel calculation capacity of an edge module. The design not only solves the contradiction between computing power and delay of a traditional system, but also supports multi-source data fusion and adaptive algorithm deployment through an open architecture, and provides a brand new path for performance improvement of a numerical control system.

The invention discloses a multi-agent-based virtual power plant layered voltage coordination control system and method, and relates to the technical field of coordination control, and the method comprises the steps: obtaining the original operation data of a distributed energy unit in a virtual power plant, and constructing a dynamic mapping model representing the relation between node voltage and control input; decomposing the dynamic mapping model into a fast dynamic sub-model and a slow dynamic sub-model; generating a fast loop control law based on the fast dynamic sub-model, and performing residual calculation and online correction on the slow dynamic sub-model according to the fast loop control law; establishing a global optimization objective function according to the corrected slow dynamic sub-model, and solving a reference value of each node through a distributed algorithm; issuing the node reference value to a local inverter, and generating a control input signal in combination with a fast loop control law; according to the method, the problems of voltage oscillation, tracking errors and slow convergence caused by virtual power plant fast and slow control conflicts are solved through fast and slow dynamic layering cooperative control.

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 discloses a traction-type AGV robust adaptive path tracking method considering trailer drift suppression, and belongs to the field of intelligent transportation AGV path tracking control. First, a path tracking control system of a towed AGV is modeled, where an articulation angle and an articulation angular velocity are introduced into a control system state to suppress drifting behavior of a trailer. Then, a robust adaptive path tracking control method combining feedforward control and feedback control is developed to improve tracking performance and robustness. In feed-forward control, a feed-forward controller capable of minimizing a tracking error in advance is designed. In feedback control, an H-infinity robust feedback controller based on observation is designed to weaken the influence of random disturbance. Wherein the preview distance model and the fuzzy algorithm are introduced into the feedback controller so as to improve the tracking precision and the adaptive capability of the path tracking control system. According to the invention, the tracking precision, robustness and stability of the traction-type AGV in a path tracking scene can be effectively improved.

The invention discloses a steer-by-wire vehicle trajectory tracking control method based on learning enhancement MPC. The method comprises the following steps: establishing a tracking error model combined with vehicle dynamics; a trajectory tracking controller based on MPC is designed, a tracking error model is used as a prediction model of an MPC algorithm, a prediction sequence matrix is constructed, a target trajectory is tracked, the tracking error approaches 0, and the optimal control quantity is obtained through optimization and solution; the MPC algorithm is enhanced by using a depth deterministic strategy gradient algorithm, a terminal cost function of the MPC algorithm is replaced, and an MPC trajectory tracking controller enhanced by using a DDPG algorithm is obtained through training. According to the method, the DDPG algorithm is utilized, the enhanced MPC trajectory tracking controller is obtained through pre-training and combined training, the vehicle can better track a target trajectory in a complex dynamic scene, the transverse instability risk is reduced, and the driving safety and the riding comfort are improved.

The invention discloses a performance testing device and method for a fine tracking system based on coarse tracking error driving, and relates to the field of composite axis tracking control. Comprising a light source, an off-axis reflection type collimator, a target simulation fast reflecting mirror, a fine detector, a fine tracking fast reflecting mirror, a fine tracking controller, a coarse tracking platform dynamics simulation computer, a coarse tracking platform management unit, a collimator holder mechanism, a primary mirror and a secondary mirror. The method comprises the following steps: driving a target simulation fast reflecting mirror to move by using an error of a coarse tracking system, coupling a target to a fine tracking system through an off-axis reflective collimator, extracting by a fine detector to obtain a miss distance, and finishing image closed-loop control by using the miss distance fine tracking fast reflecting mirror. And meanwhile, the fine tracking system outputs the unloading amount to the coarse tracking simulation system to complete unloading of the coarse and fine two-stage system. According to the method, key function and performance verification of the fine tracking system can be completed in an environment without a real coarse tracking platform, the test cost is effectively saved, and practical engineering application is facilitated.

The invention belongs to the technical field of airplane nonlinear system control, and discloses a deicing vehicle hierarchical control method and system under an airplane idling condition. According to the method, a deicing vehicle overall dynamic model under incomplete constraint is constructed based on a Lagrange equation, a vehicle-arm combined trajectory tracking error state model is constructed, a cost function of a model prediction controller is designed according to a control target of deicing vehicle combined trajectory tracking, a quadratic programming problem is constructed on an upper layer to solve an optimal virtual control quantity, and the optimal virtual control quantity is calculated. And the lower layer analyzes the virtual control quantity into control input which can actually act on an execution mechanism by designing a self-adaptive fuzzy logic strategy so as to realize trajectory tracking control. According to the invention, a hierarchical control strategy is provided by combining model predictive control and an adaptive fuzzy logic system (FLS), the stability and high efficiency of system operation are ensured, and the deicing vehicle is ensured to always maintain a stable operation state in a complex and changeable operation environment.

The invention discloses a layered direct trajectory planning method for an unmanned special vehicle in a complex non-structural environment. The method comprises the following steps: 1, acquiring perception information such as obstacles and road boundaries in the non-structural environment and a vehicle starting point state; 2, aiming at anti-rollover and efficient driving requirements in a virtual space, planning and modeling a long sight distance trajectory into an off-line constraint optimal control problem based on pseudo-spectral method numerical solution, and obtaining a global reference trajectory; 3, aiming at tracking error elimination and dynamic obstacle avoidance requirements in a real space, planning and modeling a short-sight-distance trajectory into an online optimal control problem based on model prediction control, and obtaining a local actual trajectory; and 4, inputting the local actual track into a bottom layer control system, and obtaining an end point state as a subsequent planning starting point state. On the basis of meeting common track planning requirements such as obstacle avoidance, the special vehicle can be prevented from rolling over under aggressive working conditions, and meanwhile the passing efficiency is improved.

The present invention discloses a preset time tracking and synchronization control method, system, device and medium for a four-motor drive system. It belongs to the field of four-motor drive system control technology. The present invention introduces a command filter to obtain the differential of the virtual control law to avoid the problem of calculation explosion, and at the same time constructs a filter error compensation signal to clear the filter error to improve the control accuracy. In the backstepping method, the present invention designs a preset time controller so that the tracking error and the synchronization error converge within the preset time, improves the position tracking accuracy, and reduces the mechanical damage caused by inconsistent motor speeds. The present invention uses a fuzzy logic system to approximate nonlinear friction, so that the controller still has good tracking performance under the influence of friction nonlinearity.