50 results about "Barrier lyapunov function" patented technology

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 relates to an optimal safe formation collision avoidance control method for multiple unmanned surface vessels under DoS attack. The method comprises the following steps: constructing an input saturation model; constructing a multi-unmanned surface vessel dynamic model with unknown nonlinear terms; in the obstacle avoidance control design, an integral multiplication tangent obstacle Lyapunov function is designed by using the tangent obstacle Lyapunov function; establishing an attack compensator; carrying out approximation on the unknown nonlinear term by utilizing a fuzzy logic system to obtain an approximation result; combining the approximation result with an attack compensator, constructing a fuzzy state observer with switching gain, and obtaining an observation error; an optimal performance index function is designed according to the consistency formation error, and then a Bellman residual error is constructed; and constructing a weight updating law, and designing an optimal safe formation collision avoidance controller based on a judgment-execution structure according to the weight updating law and an integral multiplication tangent obstacle Lyapunov function. According to the technical scheme, the problem that collaborative optimization of obstacle avoidance and formation control is difficult is solved.

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

The invention discloses a fixed time ship trajectory tracking control method considering state limitation. The method comprises the following steps: S1, establishing an under-actuated ship mathematical model considering input saturation; s2, limiting the actual position of the ship based on the set first obstacle Lyapunov function; limiting the expected position of the ship based on a set second obstacle Lyapunov function; s3, defining a ship position tracking error, and designing a longitudinal expected speed and a transverse expected speed which can enable the ship position tracking error to converge; s4, defining a ship speed tracking error, and designing a first fixed time sliding mode surface and a second fixed time sliding mode surface according to the ship speed tracking error; and S5, designing a longitudinal control force and a yawing control moment which can enable the first fixed time sliding mode surface and the second fixed time sliding mode surface to converge so as to enable the ship speed tracking error to realize fixed time convergence and solve the problem that the convergence rate of the speed tracking error is low.

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

The invention discloses an underwater manipulator trajectory tracking finite time sliding mode controller design method, a sliding mode controller and a control system, and belongs to the technical field of underwater robot control. Comprising the steps that a nonsingular terminal sliding mode surface control framework is constructed, the framework fuses factors such as system model uncertainty, external disturbance, output constraint and input saturation, and a foundation is laid for accurate control; in order to ensure that a system state is always in a time-varying constraint boundary in a complex marine environment, a time-varying barrier Lyapunov function is combined with sliding mode control, tracking error constraint is converted into sliding mode surface constraint through mathematical conversion, and effective constraint on the system state is realized through strict derivation and analysis; besides, a finite time auxiliary control system with a dynamic compensation strategy is designed for the problem of input saturation caused by physical limitation of the actuator, trajectory errors can be rapidly restrained, and the accuracy and stability of trajectory tracking of the underwater manipulator are remarkably improved.

The application discloses a kind of anti-network attack's multi-vehicle safety platoon control method and system, the method first establishes multi-vehicle queue dynamics model;Second, design fuzzy state observer to estimate vehicle state and unknown nonlinear dynamics;Then, introduce funnel function to build time-varying performance boundary, and the double constraints of vehicle anti-collision and keep communication are converted into funnel constraints of spacing tracking error;Then, based on backstepping method and funnel performance error, design virtual controller and adaptive law, and obtain adaptive safety controller to obtain control input;Finally, through Lyapunov stability analysis, the tolerance threshold condition that system can still maintain final consistent bounded stable after suffering replay attack is quantitatively obtained.The application simplifies design through funnel control, avoids complex barrier lyapunov function, and for the first time clearly provides quantified anti-interference ability to replay attack, enhances the network security and practicality of multi-vehicle queue system.

The invention discloses a piezoelectric driving system constraint control method based on a predetermined time observer, and the method comprises the steps: designing a predetermined time interference observer in combination with a predetermined time performance function, and guaranteeing that an interference estimation error is converged to a bounded range within a predetermined time; a state conversion function is designed based on the obstacle Lyapunov function, so that the system output can also realize preset time output constraint under the condition that the initial state does not meet the constraint condition; a predetermined time adaptive controller is designed by using a neural network approximation technology, a dynamic surface control technology, a constraint control technology and a predetermined time interference observer technology, so that a closed-loop system realizes predetermined time stability. The problem that an existing disturbance observer cannot be used for preset time control is solved, and the assumption that initial conditions of constrained variables need to meet constraint conditions in constraint control is avoided.

The application discloses an adaptive tracking control method for a random nonlinear system based on output feedback, comprising the following steps of S1, constructing a mathematical model of a random nonlinear system with hysteresis input, unknown control direction, arbitrary switching and output constraint; S2, designing a linear state observer, and reconstructing unmeasurable states of the random nonlinear system by using output and control input of the random nonlinear system; S3, introducing a Nussbaum type function to process the unknown control direction, and constructing a barrier Lyapunov function to ensure that the output constraint is not violated; and S4, designing a framework based on a backstepping method, combining a radial basis neural network to approximate unknown nonlinear functions, designing a virtual control law, an adaptive law and an actual control law, and realizing adaptive tracking control of the output of the random nonlinear system on a reference signal.

The invention relates to a PCB circuit of a three-degree-of-freedom Duffing type MEMS resonator and an event-triggered fuzzy neural network inversion control method, and belongs to the technical field of MEMS resonator control, and the method comprises the steps: constructing an electrostatic coupling three-degree-of-freedom Duffing type MEMS resonator based on a series mode, and building a mathematical model; the method comprises the following steps: designing an analog circuit of a three-degree-of-freedom Duffing type MEMS resonator, and constructing a PCB experiment platform; designing an inversion controller based on a logarithmic obstacle Lyapunov function, an acceleration function, an acceleration exponential integral tracking differentiator and a type-2 fuzzy wavelet neural network; and a switching threshold event triggering mechanism is introduced into the inversion controller.

The application relates to the field of intelligent operation unmanned planes, and discloses a plant protection unmanned plane cooperative operation spraying area control method, which constructs a multi-unmanned plane cooperative hanging type spraying system; a Lagrange method is used to establish an underactuated dynamics model of a single plane hanging load system, and mutual constraints among the multi-unmanned planes are considered under the multi-unmanned plane framework; a barrier Lyapunov function (BLF) is designed, and full-range constraints are applied to single plane load displacement and relative distances among the multi-unmanned planes; RBF neural network is used to compensate system nonlinearity and external disturbance on line; an adaptive thrust control law of multi-plane coordination is designed, high-precision trajectory tracking of each unmanned plane, strict constraints of load displacement, and collision-free guarantee among the medicine boxes are realized; the application can effectively eliminate the collision risks among the unmanned planes and among the medicine boxes by pre-planning reasonable trajectories, and can avoid medicine waste caused by repeated spraying.

This invention relates to the field of automatic control technology, and in particular to a method and system for asymmetric preset performance control of a cascade continuous stirred reactor without initial conditions. The method includes establishing a mechanistic model of the cascade continuous stirred reactor, transforming it into an error equation for the cascade continuous stirred reactor, pre-specifying that the change in reactant concentration error at the output of the cascade continuous stirred reactor satisfies a banded constraint space, converting the banded constraint space into a symmetric constraint space, constructing a radical-type algebraic saturation function to map the symmetric constraint space into a bounded symmetric constraint space, superimposing an exponential finite-time decay function on the bounded symmetric constraint space to construct a bounded symmetric constraint space without initial conditions, constructing a barrier Lyapunov function based on the bounded symmetric constraint space without initial conditions, and designing an asymmetric preset performance controller without initial conditions using the backstepping method. This invention enables the stable, safe, and rapid operation of the cascade continuous stirred reactor.

The application discloses a kind of upper limb rehabilitation robot discrete neural network control method and system, the method includes: each joint module of upper limb rehabilitation robot is regarded as a subsystem, adaptive neural network controller is constructed based on discrete barrier lyapunov function;Determine weight update rate, according to discrete determination learning theory, experience-based learning controller is constructed;On the basis of experience-based learning controller, the fusion of knowledge is realized using least square method based on space constraint, and experience-based learning controller based on knowledge fusion is constructed;Variable admittance control model is constructed, and the output of variable admittance control model is used as the reference trajectory of experience-based learning controller based on knowledge fusion, and the training of corresponding rehabilitation action is executed according to the rehabilitation demand of user.The application realizes the intelligentization and safety high-performance control of upper limb rehabilitation robot in different individuals and different recovery periods.

The application discloses a design method of a global tracking controller based on an integral barrier Lyapunov function, comprising the following steps: constructing a strict feedback system model, setting a constraint condition, dividing a global time into one or more time segments according to a preset convergence time, adopting a time scale coordinate translation mapping to map each time segment to a corresponding infinite time domain, and respectively generating improved system models, all of which form a switching system; adopting a backstepping method to construct a tracking controller of the improved system model, the controller being based on an integral barrier Lyapunov function, recursively designing a control input, and adopting a fixed dwell time method to ensure global stable tracking control of the controller, solve the convergence of the system after the preset time, and optimize the global adaptive tracking effect.

The invention provides an unmanned ship self-adaptive fuzzy trajectory tracking control method with time-varying output constraint and input quantization based on an event trigger mechanism, and the method comprises the steps: quantizing an input signal through a uniform quantizer, and carrying out the linear description of a quantization process; introducing an asymmetric obstacle Lyapunov function, constraining the state and tracking error of the unmanned ship within a reasonable range, and estimating uncertainty items in a ship model by using a fuzzy logic system; introducing a dynamic event triggering mechanism; the stability of the control strategy is proved based on the Lyapunov stability theory; a simulation experiment verifies that under constraint conditions, the adaptive fuzzy quantization control strategy keeps stable trajectory tracking performance. According to the method, the uncertainty of the model is approximated through the fuzzy logic system, the asymmetric obstacle Lyapunov function constraint output is introduced, and the dynamic event triggering mechanism and the uniform quantizer are combined, so that the high-precision trajectory tracking of the unmanned ship in the complex marine environment is realized, the communication overhead is reduced, and the system stability is ensured.

The application discloses a flexible mechanical arm control method based on predetermined time stability, which is used for controlling a flexible mechanical arm with output constraints under the requirements of meeting predetermined time indexes and high-precision control. Firstly, a standard sliding mode integral chain system is extended to a new high-order sliding mode dynamic system with non-matching terms based on the dynamic behavior of the flexible mechanical arm, and a dynamic model of a motor and a joint is established. A Barrier Lyapunov function satisfying an output constraint condition is adopted. In the case that the upper bound of a gain function of the non-matching term is unknown, an original system is converted through a time-varying scaling function, an auxiliary system for designing a predetermined time controller is constructed, a predetermined time controller based on a high-order sliding mode algorithm is proposed, the control method does not need trial-and-error parameter adjustment, the predictability of the system is further enhanced, and the motion precision and stability of the system are improved under the premise of reducing system energy consumption and mechanical loss.

The application discloses a kind of distributed time-varying state safety constraint control methods of multi-flexible manipulator system, process as follows: construct the dynamics model of 1 N Flexible manipulator with asymmetric time-varying state safety constraints and input quantization;Select the desired signal as a virtual leader, construct a multi-flexible manipulator system;Design trajectory planning function, construct desired tracking signal for each follower manipulator;Consider unknown time-varying disturbance, construct N Disturbance observer;Construct an asymmetric time-varying barrier Lyapunov function based on angle tracking error and convert it to symmetric form through coordinate transformation;Based on distributed observer, construct a distributed adaptive boundary controller;Solve the parameters of the distributed controller;Apply distributed time-varying state safety constraint control to the multi-flexible manipulator system.The application realizes distributed time-varying tracking and vibration control of multi-flexible manipulator system in the presence of asymmetric time-varying state safety constraints and input quantization.

The invention aims to provide a multi-agent system control method with an output dead zone and full-state constraint, and the method comprises the steps: carrying out the state description of a to-be-controlled multi-agent system, and constructing a dead zone model for the output dead zone in the to-be-controlled multi-agent system through a backstepping method; constructing an obstacle Lyapunov function to perform constraint control on a state variable in the dynamic model; approaching an unknown nonlinear function in the multi-agent system to be controlled by adopting a radial basis function neural network; adopting a Nussbaum function to compensate unknown gain brought by an output dead zone; and in combination with the obstacle Lyapunov function and a backstepping method, the control rate meeting the full-state constraint is obtained, it is ensured that the system state is within a preset safety range, and the stability of the multi-agent system is improved.

The present application relates to a kind of cone-shaped dielectric elastomer actuator (Dielectric Elastomer Actuator, DEA) implicit inverse control method for input square state constraint, aims at effectively reducing the influence of hysteresis on system control performance, and solve the input square full state constraint problem in DEA control, including the following steps: based on traditional Preisach model, input square Preisach model is proposed, the hysteresis modeling when input is voltage square term in DEA system is realized.Combined with Fuzzy Logic System (FLS) and Barrier Lyapunov Function (BLF), a new adaptive fuzzy segmented implicit inverse controller is proposed for DEA system with input square state constraint.Based on the control platform built, compared with the controller without implicit inverse and the traditional Backstepping controller, the accuracy and effectiveness of the designed control strategy are verified, the proposed control algorithm has higher precision, and the high-precision control goal of dielectric elastomer actuator is realized.

The invention relates to a steering under-constrained multi-axle vehicle sensitivity analysis and transverse dynamics constraint control method, which comprises the following steps of: calculating an ideal yaw velocity and a side slip angle when a multi-axle vehicle tracks an expected path according to expected path information, vehicle real-time position information and vehicle state information; establishing a multi-axle vehicle transverse dynamic model and a state tracking-oriented decoupling control model; calculating the sensitivity index of each rotation angle input to the yaw velocity and the side slip angle of the vehicle under different working conditions, analyzing the influence degree and the coupling relation of each rotation angle to the transverse dynamic performance of the vehicle, and obtaining a key control rotation angle; constructing an integral sliding mode state constraint controller based on the obstacle Lyapunov function; and according to a multi-axle vehicle turning angle signal output by the controller, an instruction is issued to the actuator, so that the turning angle of each axle is adjusted to a required angle, the motion state of the vehicle is changed, and tracking control is realized. The method can ensure safe and stable driving of the vehicle while realizing accurate tracking control of the multi-axle vehicle.

This application relates to the field of servo system control technology, and provides a green disturbance rejection control method and device for a CMG frame servo system. The method establishes a mathematical model of the CMG frame servo system under multi-source disturbances based on a high-order full-drive method, and models the multi-source disturbances as external sources. Based on the external source model and the system mathematical model, a fine disturbance separation estimator is determined. The fine disturbance separation estimator is used to determine the equivalent estimate of the multi-source disturbances. Based on this equivalent estimate, a state observer is determined, and then the state observer is used to determine the estimate of the higher-order state variables. Finally, a backstepping controller based on a barrier Lyapunov function is established using the estimates of the multi-source disturbances and the higher-order state variables. This backstepping controller controls the CMG frame servo system, providing more adjustable degrees of freedom for control performance optimization, enhancing the fine disturbance rejection capability of the CMG frame servo system under multiple constraints, and exhibiting simple design and low energy consumption.

The present application relates to the technical field of mechanical arm control, and more particularly to an adaptive fuzzy fixed-time control method based on an output limited mechanical arm, comprising the following steps: S1. constructing a mechanical arm dynamics model; S2. setting a constraint condition for the output state of the mechanical arm dynamics model; S3. defining a tracking error and a virtual control law of the mechanical arm dynamics model; S4. based on output state limitation and fixed-time control, designing an actual control law as the input of the mechanical arm dynamics model, and constructing an adaptive law; S5. constructing a three-stage logarithmic barrier Lyapunov function, and combining the three-stage logarithmic barrier Lyapunov function with the virtual control law, the actual control law and the adaptive law step by step, and then according to the actual fixed-time control lemma, ensuring that the output state of the mechanical arm dynamics model does not exceed the preset safety boundary. The present application can ensure high-precision trajectory tracking of the mechanical arm under the premise of safe operation.

The invention discloses a micro-grid cluster cooperative safety control method and system. The system comprises a micro-grid cluster MGC system, a switching control barrier function SCBF, a switching barrier Lyapunov function SBLF, a task allocation decision-making layer, a time-varying communication topology and a distributed secondary safety control protocol. An instruction switching signal output by the task distribution decision-making layer and a topology switching signal output by the time-varying communication topology are respectively input into an SCBF, an SBLF and a distributed secondary safety control protocol; the output of the SCBF and the output of the SBLF are used as the input of a distributed secondary safety control protocol; the output of the distributed secondary safety control protocol is input into the MGC system; and the output of the MGC system is respectively input to the SCBF, the SBLF and the distributed secondary safety control protocol. According to the system provided by the embodiment of the invention, the inertia and damping of the MGC system are improved, the voltage support is enhanced, the MGC system has the characteristics of high inertia, high damping and strong voltage support, and the strength and stability margin of the MGC system are improved.

The invention discloses a damping low-frequency double-event trigger control method for a semi-submersible floating platform, and belongs to the technical field of offshore platforms. The method comprises the following steps: constructing a system kinetic equation through a Newton-Euler formula; based on the constructed system kinetic equation, establishing a multi-agent system through fuzzy logic; constructing a consistency error through a Laplacian matrix based on a multi-agent system; the method comprises the following steps: designing a group of error variables and constructing an obstacle Lyapunov function; in order to overturn the mode platform, the obstacle Lyapunov function is solved on the basis of limitation consideration on the size of the consistency error, so that the consistency error is converged to be infinitely small. According to the method, the initial condition dependency of the threshold is relaxed, the event triggering frequency can be remarkably reduced, so that communication resources are effectively saved, next triggering is allowed only when the threshold bandwidth requirement error is introduced to cross the bandwidth, the generation of a sesame phenomenon is avoided, the triggering frequency is reduced, and the communication resources are saved.

The application relates to an echo state network-based adaptive fault-tolerant control method for a non-strict repetitive system, which comprises the following steps: constructing a nonlinear dynamic system with an actuator fault, and setting a hypothesis condition; introducing a desired error trajectory, constructing a dynamic error equation, and defining a nonlinear function in the equation; approximating the nonlinear function by using an echo state network; proposing an adaptive iterative learning fault-tolerant algorithm, combining a barrier Lyapunov function, deducing a control input, constructing a controller, and filtering redundant batches; and constructing a barrier composite energy function to verify the stability and convergence of the designed adaptive iterative learning fault-tolerant algorithm. The nonlinear dynamic system constructed by the application can still realize effective tracking and control of the system state to the desired trajectory under the conditions that the actuator has additive or multiplicative faults, the system state is limited, and external disturbances exist.

The invention provides a tracking control method for a flexible mechanical arm under preset time. The tracking control method comprises the steps that a coupling effect including connecting rod dynamics and motor actuator dynamics is considered, and a high-order nonlinear dynamic model of a single-connecting-rod flexible joint mechanical arm is established based on an Euler-Lagrange equation; a tracking error and an adaptive filter of the flexible mechanical arm are defined, so that error convergence within finite time is achieved; a preset time function and an obstacle Lyapunov function are constructed, an error conversion function is established, and tracking error constraint is converted into unconstraint; and an actual controller of the flexible mechanical arm is constructed and updated according to the self-adaptive filter, the error conversion function, a preset time function and a barrier Lyapunov function. According to the method and the device, the flexible mechanical arm can be ensured to realize high-precision tracking of the target trajectory within the preset time randomly specified by a user, and all signals in a closed-loop system are kept bounded.

The invention discloses a multi-constraint anti-saturation attitude control method for a variable-shape aircraft, and belongs to the field of aircraft guidance and control. The implementation method comprises the following steps: establishing a variable shape aircraft dynamics model, and writing the model in a control matrix form; considering attitude angle constraint, giving a state tracking error, constructing an asymmetric obstacle Lyapunov function, and introducing the attitude angle constraint into controller design; giving a state tracking error by considering an attitude angular rate constraint, constructing a symmetric obstacle Lyapunov function, and introducing the attitude angular rate constraint into controller design; a composite Lyapunov function is designed, control input constraints are considered, and an attitude angular rate subsystem virtual control law is designed; and realizing the multi-constraint anti-saturation attitude control of the variable shape aircraft according to the anti-saturation attitude control law under multiple constraints. According to the invention, under strict constraints of the attitude angle, the attitude angular rate and the control input, accurate tracking of the attitude angle and the attitude angular rate can be realized, and effective suppression of control buffeting can be realized.

The invention discloses an aircraft guidance and control integrated design method based on a control barrier function. The method comprises the following steps: constructing dynamics and kinematics equations of a hypersonic aircraft; constructing a hypersonic flight vehicle gliding section guidance and control integrated model; constructing an expected attack angle instruction limiting range; acquiring an expected speed inclination angle and track yaw angle instruction; setting a control scheme for designing guidance and control integration of the gliding section of the hypersonic flight vehicle based on a barrier Lyapunov function in combination with a dynamic surface control method; the overall performance of the guidance control system for the gliding section of the hypersonic aircraft is obviously improved; designing an expected attack angle instruction limiting range to restrain the state quantity of the aircraft, thereby ensuring the safety performance of the aircraft and improving the stability of the system; the method can overcome the difficulties of strong coupling, nonlinearity, uncertainty, strong constraint and the like of a hypersonic aircraft system, and ensures that the system can accurately reach a target position under the condition of meeting various constraints.

The invention discloses a combined type vertical take-off and landing unmanned aerial vehicle boundary protection control method based on an asymmetric time-varying obstacle Lyapunov function. The method comprises the following steps that 1, a combined type vertical take-off and landing unmanned aerial vehicle longitudinal dynamic model is established; 2, designing a composite vertical take-off and landing unmanned aerial vehicle safety boundary calculation method to obtain an unmanned aerial vehicle safety flight envelope; 3, designing a virtual instruction anti-saturation auxiliary system to dynamically adjust a dangerous state; 4, designing a smooth saturation function to limit the amplitude of the attack angle instruction, and enabling the attack angle instruction of the unmanned aerial vehicle to be within a safety boundary; 5, constructing a boundary protection controller, and designing a height and speed control law; and step 6, constructing an asymmetric time-varying obstacle Lyapunov function, analyzing the stability of a closed-loop system and selecting control parameters. The invention designs an adaptive robust flight controller, and solves the boundary protection control problem of a combined vertical take-off and landing unmanned aerial vehicle under strong interference and state constraint strips.

The invention discloses a two-degree-of-freedom helicopter predefined time fault-tolerant tracking control method, which comprises the following steps of: establishing a two-degree-of-freedom helicopter dynamical model containing external disturbance and actuator faults, constraining a system state by constructing a time-varying Barrier Lyapunov function, and fusing optimization control based on reinforcement learning into backstepping control, so that the two-degree-of-freedom helicopter is subjected to time-varying fault-tolerant tracking control. The method comprises the steps of designing an optimal virtual controller, designing an optimal tracking controller by adopting a control method based on a mixed zero-sum game theory aiming at an actuator fault and composite disturbance, and relieving communication burden by adopting a dual-channel event triggering mechanism comprising a controller-actuator and a sensor-controller. The controller designed by the invention can ensure that all signals of the whole two-degree-of-freedom helicopter are bounded within the preset time, and ensure that the two-degree-of-freedom helicopter can still quickly and accurately track a reference trajectory within the preset time under the constraint of actuator faults and states.