280 results about "Performance function" patented technology

The invention relates to the technical field of injection molding, and discloses a plastic part injection mold regulation and control system and method based on a complex curved surface and a thin-wall structure, and the plastic part injection mold regulation and control system based on the complex curved surface and the thin-wall structure comprises a mold modeling module, a temperature modeling module, a control modeling module, a control optimization module and a control execution module; the plastic part injection mold regulation and control method based on the complex curved surface and the thin-wall structure comprises the steps that a mold three-dimensional model and thermal control area mapping are built, a heat conduction model is built, modal dimensionality reduction is conducted, a target temperature field and a performance function are combined, optimal temperature regulation and control are achieved through a predictive control algorithm, real-time feedback is matched, and a heating and cooling unit is driven. And dynamic closed-loop control of the mold thermal field is realized. According to the method, thermal control precision and energy consumption efficiency are optimized through Galerkin modal dimension reduction, model predictive control and a weighted performance function, global closed-loop temperature control is achieved by combining mapping of a three-dimensional area and a heating and cooling unit of the mold, and system safety and stability are enhanced.

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 a rigid spacecraft attitude control method and system based on finite time constraint, and belongs to the technical field of spacecraft attitude control. Comprising the following steps: respectively constructing a spacecraft attitude control system model and a finite time convergence performance function containing a preset time constant; according to the finite time convergence performance function, dynamic attitude constraint is applied to the system state of the spacecraft attitude control system model; converting the attitude constraint into differential homeomorphic mapping of an unconstrained space; obtaining an error conversion variable according to differential homeomorphic mapping; and designing a virtual control law and constructing an error compensation module according to the error conversion variable, and designing an actual control input law according to the virtual control law and the error compensation module. According to the method, rapid convergence of the spacecraft attitude within the preset time is ensured, the dynamic response precision of the spacecraft in the rapid attitude maneuver process is remarkably improved, the control period delay is effectively avoided, and the power consumption is reduced.

The invention provides a non-probabilistic time-varying reliability analysis method based on ellipsoid correlation modeling. The method comprises the following steps: carrying out interval modeling on uncertainty input parameters; constructing a multi-dimensional ellipsoid uncertain domain based on correlation information among parameters; a system time-varying performance function is established, and an interval process of output response changing along with time is obtained through uncertainty propagation solution; identifying the maximum value point of the upper boundary and the minimum value point of the lower boundary in the interval process as reliability key points; respectively calculating non-probability reliability indexes based on the ellipsoid model at the moments of the two key points; and taking the smaller value of the two indexes as the non-probability time-varying reliability index of the system in the target time interval. According to the method, the problem that the evaluation result is conservative due to the fact that variable correlation is ignored in a traditional non-probability method is effectively solved, time-varying evolution of system performance can be accurately quantified, and an accurate and practical dynamic safety evaluation tool is provided for a complex engineering system with scarce data.

The invention relates to an unmanned aerial vehicle trajectory tracking control method based on model prediction and preset performance constraint, and the method proposes to introduce Lyapunov stability constraint into a model prediction control framework and integrate a preset performance control mechanism, thereby achieving the unification of performance constraint and system stability analysis. Comprising the following steps: establishing a nonlinear system model based on unmanned aerial vehicle dynamics; position errors and attitude errors are defined, a preset performance function is constructed, and errors with performance constraints are converted into unconstrained errors through error normalization and nonlinear transformation; establishing a model prediction optimization problem on the premise of considering input saturation and stability constraints; designing an auxiliary control law based on the transformation error to construct a stability constraint; it is proved that the control strategy can ensure that errors meet preset performance constraints and system local asymptotic stability. According to the invention, stable and reliable trajectory tracking control of the unmanned aerial vehicle system can be realized, and the method has high tracking precision and good dynamic performance.

The invention provides a multi-objective optimization method fusing a classifier and an active learning strategy, and belongs to the technical field of artificial intelligence and optimization design, and the method specifically comprises the steps: obtaining a sample data set containing a plurality of target performance function values; performing non-dominated sorting on the sample data set to extract a Pareto frontier point set, and extracting geometric features from the point set as a geometric feature vector sequence; using the geometric features and the corresponding convex marks to train a classifier model of a Transform architecture, wherein the classifier model supports a multi-head attention mechanism and a position coding structure; judging the convex confidence coefficient of the current Pareto front by using a classifier model, and obtaining a candidate scheme; and inputting the candidate scheme into a double-attention mechanism prediction model based on context reasoning, and predicting the multi-target performance of the candidate scheme. According to the method, the experiment frequency can be reduced, the target performance can be accelerated to be achieved, and the intelligence and efficiency of the multi-target optimization process are improved.

The invention discloses a method and a system for evaluating the toughness of an oversized-diameter shield undercrossing airport runway based on a differential settlement and dynamic settlement rule, terminal equipment and a medium, and relates to the technical field of shield engineering. The method comprises the following steps: acquiring engineering information and post-construction settlement and post-construction differential settlement control standards; constructing a three-dimensional finite element model which comprises a plurality of simulation working conditions and a plurality of key characteristic sections and reflects interaction of soil and a structure; simulating sequential tunneling of the shield, obtaining dynamic settlement data and a final settlement value, and calculating a differential settlement amount; substituting the dynamic settlement data into the toughness performance function to obtain a dynamic toughness value and an evolution curve; and calculating a final-state toughness index based on the dynamic toughness value, and judging the toughness grade in combination with a control standard and a preset grade division standard. According to the method, dynamic and final-state quantitative evaluation and grade judgment of runway toughness are realized, a structural performance attenuation rule is clarified, and a scientific basis is provided for construction control optimization and engineering decision.

The invention provides a heterogeneous multi-agent system control method under a DoS attack based on an event triggering strategy. Robust cooperative control under a complex attack environment is realized through the following steps: S1, performing state description and topological structure modeling on a heterogeneous multi-agent system; s2, carrying out approximation on an unknown nonlinear function in the system; s3, restraining the error dynamic state through a performance function, and ensuring that the system response meets the preset precision; s4, designing a time-varying threshold function, and dynamically adjusting a trigger condition to reduce communication burden; s5, designing an anti-attack controller in combination with event triggering and a Lyapunov theory; s6, designing an adaptive law to carry out online estimation on disturbance; and S7, testing synchronization precision, communication efficiency and anti-attack performance based on a physical platform. According to the method, deep fusion of the event triggering mechanism and the preset performance constraint is realized for the first time, and the self-adaptive dynamic threshold strategy is introduced, so that malicious interference of DoS attacks on a communication link is effectively dealt with, and it is ensured that the heterogeneous nodes can still meet preset performance indexes in an attack scene.

The invention discloses a reconfigurable robot control method and system for a zero-sum game optimization event triggering mechanism. The method comprises the steps that a reconfigurable robot dynamic model based on joint torque feedback is established, an error dynamic state space is established, and a preset performance function is set to restrain the transient performance of the error dynamic state space; the error dynamics state space constraining the transient performance is mapped to the unconstrained error dynamics augmented system state space, and an event triggering mechanism is introduced, so that the unconstrained error dynamics augmented system state space meets the zero-sum game of maximizing the event triggering interval and minimizing the control input; setting a performance index function based on a zero-sum game, and obtaining an optimal control law under an event triggering mechanism through the performance index function; according to the invention, the precision and stability of robot system control are improved through the predetermined performance function; the zero-sum game of an event triggering mechanism is introduced to obtain an optimal control law under a Nash equilibrium condition, so that communication resources and calculation burdens are effectively reduced; and the control torque of each subsystem is smoother under the action of the optimal control law, so that the energy consumption is reduced and the service life of the motor is prolonged.

This application discloses a system and method for federated collaborative machine learning model development using local training datasets that are not shared. An adaptive and evolutionary approach is used to select local training nodes that are most fit from one training round to the next training round to optimize an overall cost and performance function for the federated learning, to cross-over model architecture between local training nodes, and to perform model architecture mutation within local training nodes. The local training nodes are further clustered to account for the inhomogeneity in the local datasets. Such adaptive, evolutionary, and collaborative federated learning thus provides cost-effective and high-performance model development.

The invention discloses an unmanned ship target tracking constraint control method based on an exponential time-varying performance function, and relates to the technical field of state tracking control, in particular to the technical field of performance constraint control, comprising the following steps: step (1), establishing an unmanned ship motion three-degree-of-freedom mathematical model; step (2): constructing an exponential time-varying function; (3) constructing an exponential time-varying performance function; (4) introducing a time-varying auxiliary function; (5) designing a transfer function; (6) designing a fixed time performance constraint heading controller based on an exponential time-varying performance function; (7) designing a fixed time performance constraint surging controller based on an exponential time-varying performance function; and (8) performing simulation verification. According to the method, mainly starting from the design of a novel time-varying performance function, the problem that the state error of the traditional performance function constraint control at the initial moment is limited by the performance boundary is solved, so that the transient performance and the steady-state performance of the state tracking error of the unmanned ship are remarkably improved; and the overall control performance of unmanned ship target tracking control is further improved.

The invention provides a preset performance fault-tolerant control method under motor failure of a tendon-driven mechanical arm. The preset performance fault-tolerant control method comprises the following steps: constructing a tendon-driven mechanical arm system model with actuator fault, external interference and system parameter uncertainty; designing a tendon-driven mechanical arm trajectory tracking error model and a fixed time sliding mode observer; an improved preset performance function is constructed, so that the trajectory tracking position error of each joint of the mechanical arm meets a preset performance boundary; and a fixed-time preset performance fault-tolerant controller is designed, so that trajectory tracking errors of all joints of the mechanical arm are converged to a preset performance boundary within fixed time. According to the method, non-singular terminal sliding mode control is combined with the preset performance function, so that the performance boundary constraint of the tracking error is realized while the stability of the fixed time of the system is ensured; by dynamically adjusting the boundary of the performance function, the problem of control precision degradation under the actuator fault working condition is effectively solved, and the robustness and trajectory tracking precision of the system are remarkably improved.

The invention provides a UWB anchor point deployment method and system based on multi-objective optimization and dynamic hotspot prediction. The method comprises the following steps: initially installing a UWB positioning system; constructing a dynamic hot area prediction model; predicting a candidate area of the dynamic hot area; constructing a multi-target performance function, and evaluating the candidate region of the dynamic hot region; performing anchor point position search by adopting a hybrid optimization algorithm; performing feedback adjustment based on a state monitoring result; outputting a result; according to the system, a multi-source data acquisition module is used for acquiring multi-source target data; the dynamic hot area prediction module is used for predicting a dynamic hot area candidate area; the multi-target performance evaluation module is used for screening high-value candidate regions; the optimal deployment module is used for searching an optimal UWB anchor point deployment position; the state feedback module is used for feedback adjustment; and the result output module is used for outputting the optimal UWB anchor point deployment scheme. According to the method and the system, the optimal UWB anchor point deployment scheme can be efficiently and accurately obtained, and the positioning accuracy under the underground complex working condition can be ensured.

The invention belongs to the field of distributed system control, and particularly relates to a vehicle system distributed control method, system and device based on reinforcement learning. Cooperative and competitive dynamic characteristics of a multi-vehicle system are described through a second-order nonlinear dynamic model in combination with a signed directed graph, unknown nonlinear dynamic and external disturbance existing in the vehicle system are considered, and the whole system is modeled as a second-order strict feedback nonlinear system. In order to get rid of dependence of convergence time on initial conditions and optimize transient performance, a preset time performance function is introduced, and a three-part neural network architecture is constructed; and designing a control law cooperating with a preset time parameter, and ensuring the actual preset time boundaries of the multi-vehicle system under the unknown dynamic and external disturbance influence. According to the method, the convergence time can be accurately set, the calculation complexity of a control algorithm is remarkably reduced, and the transient performance and robustness of a vehicle system are improved.

The invention relates to a multi-agent adaptive cooperative fault-tolerant tracking method, device and equipment, and the method comprises the steps: estimating the current state of a navigator through employing a distributed high-order sliding-mode observer according to interaction data and historical state data of the navigator, and obtaining a current state estimation value of the navigator, a tracking error is calculated according to the current state estimation value, the constrained tracking error is converted into an equivalent unconstrained tracking error by adopting an error conversion function, and a self-adaptive cooperative fault-tolerant controller is adopted according to the current state estimation value of the navigator, the unconstrained tracking error and the current state data of the follower; and under the constraint of a fixed time preset performance function, obtaining a current control signal meeting the preset tracking precision under the preset error convergence time, and executing the current control signal to realize tracking control under the composite constraint. By adopting the method, accurate control can be carried out under composite constraints.

The invention belongs to the technical field of multi-agent cooperative intelligent control, and particularly relates to a multi-mechanical-arm cooperative control method under unknown disturbance, which comprises the following steps: establishing a dynamic model of a strict feedback nonlinear multi-mechanical-arm cooperative system; constructing a communication topological structure of the system through a virtual coupling mechanism; constructing a unified system collaborative error model; introducing a preset time function and a global preset performance function, mapping errors to an adjustable constraint performance space, and ensuring that all error signals are dynamically converged in a performance range set by a user; a task layer shape control force and a pose control force are designed under a distributed gradient descent method framework, a task layer overall control force is constructed, and multiple mechanical arms are driven to move cooperatively and keep a stable formation in a task space; designing a joint layer distributed adaptive control law under unknown disturbance through passive characteristics of a nonlinear system; according to the method, cooperative convergence and stable control of the multi-mechanical-arm system within the preset time can be achieved under unknown disturbance.

The invention discloses an underwater control system based on a multi-modal neural network large model, the system comprises an underwater robot and the multi-modal neural network large model, the underwater robot is used for collecting environmental data, and is also used for decomposing a received functional control instruction into an action execution signal, and sending the action execution signal to the multi-modal neural network large model; completing a set task target based on the action execution signal; the multi-modal neural network large model is used for generating prompt information based on received environment data, underwater domain knowledge and a task target sent by the underwater robot, and extracting prediction performance function sequence information capable of realizing the task target from a robot performance function library through the prompt information, and converting the performance function sequence information into a functional control instruction. According to the system, the underwater robot has high sensing ability, and a large model has understanding and reasoning ability facing the underwater environment, so that autonomous decision and accurate control of the intelligent agent with the body are realized.

The invention discloses a zero-sum game-based two-degree-of-freedom helicopter safety controller design method, which relates to the technical field of two-degree-of-freedom helicopter control, and comprises the steps of constructing a system equation, introducing an attack signal and a preset performance function, decomposing into two stages of subsystems, and designing a virtual controller, an adaptive law and a self-triggering mechanism. And solving a Hamiltonian-Jacobian-Exophone equation by using a zero-sum game theory, and finally verifying the stability of the system through a Lyapunov function. According to the invention, it can be ensured that the tracking error converges to the steady-state error interval within the predetermined time, and the transient and steady-state performance of the system is significantly improved; and meanwhile, a Nussbaum function and a zero-sum game strategy are introduced to improve the attack resistance, the communication burden and actuator abrasion are reduced through a self-triggering mechanism, and the sesame effect is avoided.

The invention discloses a piezoelectric micro-positioning platform preset performance control method based on an extended state observer, and the method mainly comprises the steps: firstly, building a piezoelectric micro-positioning platform system model considering input hysteresis and unknown disturbance; secondly, designing an extended state observer based on a radial basis function neural network to estimate an unmeasurable state of the system and lumped disturbance containing input hysteresis; then, a preset performance function is used, so that the overshoot performance of the system is effectively improved; thirdly, in combination with a preset performance function, a first-order sliding mode differentiator and an expansion state observer, providing a virtual control law and an adaptive control law; and finally, a preset performance controller is utilized, a Lyapunov stability theory is combined, proper parameters are selected to ensure that the closed-loop system is kept stable within preset time, and tracking errors are controlled within a set error range.

The invention provides a cooperative anti-swing control method and system for double marine cranes based on preset performance, and relates to the technical field of crane control. Comprising the following steps: establishing a marine crane dynamical model considering double-ship rolling disturbance by using a Lagrange method; determining a drivable variable, and establishing a tracking error of the drivable variable; introducing an exponential preset performance function, constraining the convergence rate, overshoot and steady-state value of the tracking error, and converting the constrained tracking error into an unconstrained variable by using a hyperbolic tangent function; a performance index function considering tracking errors and energy consumption is constructed, a Hamiltonian equation minimization performance index function is constructed, the Hamiltonian equation is solved through a reinforcement learning algorithm, and the optimal control rate is obtained. According to the invention, the convergence speed of the error of the system variable is limited in a preset interval, the steady-state and transient-state performance of error convergence is improved, and accurate control and anti-swing of the load are realized.

Provided are a method and a system for cooperative airborne meteorological perception with multiple aircraft. The method includes: determining a training set based on a spatial position, motion data, weather, an observation image, and static information of each of multiple aircraft; determining a fusion performance function based on an objective of a cooperative perception network; generating a fusion model based on the training set and the fusion performance function; generating a perception result image based on the fusion model; determining flight risk information based on the perception result image; determining a route alarm command and sending the route alarm command to a management user interface and an interactive device of a target aircraft; after receiving the route alarm command, generating, by the management user interface, a route adjustment parameter; in response to obtaining the route adjustment parameter, performing at least one of the following operations: adjusting an engine velocity, adjusting an aileron pressure, adjusting an elevator deflection, and adjusting a rudder deflection.

The invention relates to the technical field of multi-agent control, in particular to a method and a system for realizing preset performance to control multiple agents based on a barrier function. The non-linear state observer is designed to estimate the unmeasurable state in the system in real time, the dependence of a traditional control strategy on full-state information is broken through, and the adaptability and robustness of the system are improved. Besides, the inclusion error is constrained through the obstacle function, and the inclusion error is limited in a limit range, so that a preset performance constraint problem is converted into a bounded problem of the obstacle function. Explicit constraint is carried out on convergence time and range including errors through a preset performance function, and the dual requirements for rapidity and precision in an actual task are met. And a filter is introduced to replace a high-order virtual controller for derivation, so that the design complexity of the controller is effectively reduced, and the engineering implementability of the algorithm is improved.

The invention discloses a sliding mode control method for spacecraft attitude tracking with preset performance, and belongs to the technical field of process control. On the basis of an all-drive system method and preset performance control, for a spacecraft attitude tracking system with inertia uncertainty, external disturbance and actuator saturation, the method comprises the following steps of: firstly, restraining an attitude tracking error of a spacecraft by utilizing a preset performance function with finite time convergence, and converting a system state through a conversion function; and constructing a constrained attitude tracking system model. The method comprises the following steps of: firstly, converting the model into an all-drive system model, introducing a self-adaptive disturbance observer, estimating inertial uncertainty and external disturbance values, and finally designing an anti-saturation sliding mode controller with preset performance by combining an anti-saturation compensation system on the basis of an all-drive system method, so as to control the attitude of a spacecraft. And stable tracking of the target attitude by the spacecraft is realized.

The invention provides a self-adaptive performance safety control method for a flexible joint mechanical arm, and relates to the technical field of mechanical arm control. According to the method, state transformation is carried out on the kinematics model of the flexible joint mechanical arm, and then the preset time performance function is constructed, so that the flexible joint mechanical arm connecting rod tracking error can be converged to a specified range within the preset time under any initial condition. In order to ensure that the flexible joint mechanical arm always operates in a safe range, function transformation is constructed for a constraint function boundary and the state of the flexible joint mechanical arm, and a fuzzy logic system is used for approximating a coupling part of the state, so that the flexible joint mechanical arm operates safely. And a high-precision and high-efficiency tracking control target is realized.

The invention provides a preset performance control method and system under saturation of a train actuator, and relates to the technical field of train control, and the method comprises the following steps: building a train longitudinal motion kinetic equation based on the Newton second law; defining actual control input under saturation constraint of a train actuator, and establishing a dynamic compensation function in combination with a train longitudinal motion kinetic equation; designing a tracking error in the train operation process, and defining a filtering error in combination with a power compensation function; designing a preset performance function based on the train longitudinal motion kinetic equation and the filtering error, and defining an error conversion mechanism; constructing a preset performance control law based on the error conversion mechanism, and designing a parameter adaptive law to update the preset performance control law; and verifying the stability of the updated preset performance control law, and controlling the train operation by using the updated preset performance control law. Under the actual working condition of saturation constraint of the actuator, the tracking precision, the response speed and the overall stability of train operation control are remarkably improved.

The invention provides a parameterized three-dimensional modeling method and system based on natural language and database driving, and belongs to the technical field of civil engineering modeling. According to the method, a performance function library (comprising a structure creation unit, a section operation unit and a parameter management unit) is constructed, a natural language dialog box is used for receiving a user instruction, the instruction is analyzed into modeling parameters by means of a natural language processing technology, and corresponding performance functions in the performance function library are automatically called. And then, according to a performance function calling result, generating information such as node coordinates, a geometric topological relation and section attributes, storing the information into a database, and finally, generating a three-dimensional model based on the database. According to the parameterized three-dimensional modeling method and system based on the natural language and database driving, professional software operation is not needed, the learning and modification cost is remarkably reduced, manual input errors are reduced, the modeling efficiency and the team cooperation ability are improved, and the parameterized three-dimensional modeling method and system can be widely applied to building, bridge, tunnel and steel structure engineering.

The application provides a performance function self-adjusting control method for improving the performance of a quad-rotor flight, first constructs a global performance function with self-adjusting capability, sets an infinite initial value to adaptively constrain the tracking error of the quad-rotor unmanned aerial vehicle; then sets a performance indicator function as a dynamic feasibility monitoring benchmark of the quad-rotor unmanned aerial vehicle, monitors and judges the current flight state of the unmanned aerial vehicle in real time; then constructs a segmented continuous auxiliary system to adjust the boundary parameters of the performance function; for the position control layer of the quad-rotor unmanned aerial vehicle, a control law is designed and deployed based on the self-adjusting performance function; in an indoor obstacle environment, the autonomous flight task of the quad-rotor unmanned aerial vehicle is executed in combination with multiple modules, the performance function is automatically adjusted, and the dynamic balance between safety and precision of the trajectory tracking of the quad-rotor unmanned aerial vehicle is realized.

The invention provides a universal downhole tool instrument testing system, and relates to the technical field of instrument testing, and the system comprises an acquisition module which is used for measuring the performance function parameters of a to-be-tested downhole tool instrument; the detection module is used for monitoring the working state signal characterization quantity of the to-be-measured downhole tool instrument; the storage module is used for storing the performance function parameters and the working state signal characterization quantity; and the control module is used for controlling the acquisition module, the detection module and the storage module. The testing system provided by the invention can be used for testing under the testing conditions of high-temperature and high-pressure simulation wellbores, full-size testing wells and the like along with various types and specifications of underground tools and instruments, and related parameters in the testing process are measured and stored in real time in the whole process; and the downhole tool instrument can be driven or controlled in the testing process so as to verify the function of the downhole tool instrument.

This invention provides a low-computational-complexity, pre-set performance-tolerant control method for steer-by-wire systems. The control method includes: determining the control objective based on a pre-set performance control method; subsequently designing a new pre-set performance function and error transformation function; designing virtual control laws and control laws in the controller using a robust control method; establishing a dynamic model of the steer-by-wire system based on system dynamics; establishing a dead-zone model and a fault model based on the impact of dead zones and faults in the vehicle actuators on the control performance of the steer-by-wire system; simultaneously obtaining the input nonlinear model of the steer-by-wire system; subsequently establishing a state-space model of the steer-by-wire system; and finally, verifying the controller's control effect and optimizing its internal parameters using the state-space model. This invention considers fault and dead-zone issues, improving the robustness of the controller; and considers the limited computational resources of the vehicle, with a simple controller structure that improves the overall computational efficiency of the vehicle.