272 results about "Lyapunov stability" patented technology

The invention discloses a micro-grid intelligent scheduling method and system based on an AI large model, and the method comprises the steps: collecting and processing the real-time output data of a photovoltaic power station and a wind power station, and obtaining a standardized micro-grid operation data set; a discrete time micro-grid dynamic model is established and a recursive least square method is adopted to carry out system parameter online estimation so as to obtain a robust scheduling scheme oriented to uncertainty interference; and in combination with real-time operation state monitoring, real-time micro-grid intelligent scheduling is carried out by deploying edge computing nodes. According to the method, the Lyapunov stability theory and the control barrier function are combined, a safety reinforcement learning framework oriented to micro-grid dispatching is constructed, and the absolute safety of system operation in the dispatching process is ensured.

The invention discloses a control method applied to self-piercing riveting, and relates to the technical field of self-piercing riveting control. According to the method, riveting material data are collected in real time through a multi-source data fusion interface, the high-dynamic deformation process of a riveting head is captured, deformation rate and rebound value characteristic values are extracted, and a multi-dimensional process parameter set is constructed. And comprehensively analyzing the hardness, thickness and plastic dissipation characteristics of the material, and establishing an anti-deformation capability evaluation function. By introducing the fluctuation characteristics of the punching force, the nonlinear relation between the punching force and the elastic deformation of the riveting rod is analyzed, a hybrid compensation model is constructed, and a riveting dynamic coupling compensation vector is output. And generating a compensation weight matrix through an adaptive optimization algorithm, and dynamically adjusting the stamping force and the displacement of the riveting rod in combination with an anti-saturation control strategy. And dynamically adjusting a gain parameter through multi-scale filtering and a Lyapunov stability criterion, and triggering iterative updating of a compensation weight parameter during out-of-tolerance so as to optimize a control effect. Riveting precision and stability are improved, and the service life of equipment is prolonged.

The invention relates to the technical field of attitude control, and discloses a method for realizing self-adaptive active leveling compensation, which comprises the following steps: acquiring real-time data of a vehicle, the data being provided by a plurality of sensors; processing the real-time data through a data fusion algorithm; according to the inclination state and the motion parameters of the vehicle, hydraulic supporting leg adjusting parameters are calculated through a multi-objective optimization algorithm; according to the calculated hydraulic supporting leg adjusting parameters, the action of the hydraulic supporting leg is adjusted through a PI D controller for vehicle balance recovery; the stability of the hydraulic supporting leg adjusting system is verified through the Lyapunov stability theory, and the hydraulic supporting leg adjusting system is used for enabling the adjusting process of the hydraulic supporting leg to be completed in all operation states; and the vehicle inclination state is fed back in real time. By fusing multi-sensor data and adopting a Kalman filtering or particle filtering algorithm, high-precision perception of the real-time inclination state and dynamic parameters of the vehicle is realized, and a more accurate and reliable vehicle attitude judgment effect is obtained.

The invention relates to a multi-machine cooperative dynamic balance driving method, system and device for a spiral lifting machine, and the method comprises the steps: carrying out the compensation of the time lag of an actuator through employing a non-linear state observation and time lag compensation combined method, and obtaining a feedforward control quantity; performing Lyapunov stability feedback processing on the vibration acceleration signal to obtain a vibration suppression control quantity; designing a multi-section S-shaped speed curve, and calculating a closed-loop feedback control quantity by adopting PID (Proportion Integration Differentiation) combined with a robust control algorithm; and according to the feedforward control quantity, the vibration suppression control quantity and the closed-loop feedback control quantity, multi-machine cooperative dynamic balance driving of the spiral lifting machine is carried out. According to the invention, a non-linear state observation and time delay compensation technology is adopted, so that the synchronization error is reduced to a millisecond level; the low-frequency vibration amplitude is reduced through dynamic feedback control designed based on the Lyapunov theory; the hydraulic impact is obviously reduced by adopting a multi-section S-shaped speed curve; external disturbance is observed in real time through Kalman filtering, feed-forward compensation is carried out, and the robustness of the system is greatly enhanced.

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 discloses a doubly-fed induction generator fault detection method combining a sliding-mode observer and a bilateral cumulative sum algorithm, and the method comprises the following steps: designing a doubly-fed induction generator rotor current sliding-mode observer based on the combination of a novel reaching law and a doubly-fed induction generator state equation; carrying out stability and convergence analysis on the designed novel reaching law by adopting a Lyapunov stability theory; and the fault detection method of the doubly-fed induction generator is designed in combination with the optimized bilateral accumulation sum algorithm. A rotor current sensor fault, an input interference voltage fault, a voltage drop fault and a stator turn-to-turn short circuit fault are introduced. The rotor current tracking performance of the designed sliding-mode observer under different doubly-fed induction generator faults is verified by using a residual value obtained by comparing a doubly-fed induction generator rotor current value estimated by the sliding-mode observer with an actual rotor current output value; and meanwhile, the reliability of the designed doubly-fed induction generator fault detection method based on the optimized bilateral cumulative sum algorithm is verified. The doubly-fed induction generator fault detection method combining the sliding-mode observer and the bilateral cumulative sum algorithm has the advantages of being high in tracking precision and accurate in fault state characterization, meanwhile, weak fault features can be effectively converted into digital signals to be output, and faults of the doubly-fed induction generator are detected.

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 belongs to the field of artificial intelligence, particularly relates to an agent strategy generation and online optimization method based on dynamic scene perception, and aims to solve the problems that in a dynamic environment, strategy response is slow, optimization is difficult under sparse rewards, and online learning is unstable. The method comprises the following steps: constructing a multi-modal fused dynamic scene semantic perception module, and generating a high-dimensional scene representation; historical behaviors and environment contexts are fused through an attention mechanism, and an initial probabilistic strategy is output; executing an action and collecting real-time feedback to form an experience tuple; performing incremental strategy updating by adopting a non-parametric Bayesian framework and combining with a multi-peak exploration operator; a Lyapunov stability criterion and a strategy distillation mechanism are embedded to guarantee convergence robustness. According to the scheme, strategy generation within 50 milliseconds is achieved, the convergence speed of sparse reward tasks is increased by three times, strategy fluctuation is controlled within 8%, the system availability reaches 99.5%, and the real-time decision-making capacity and group cooperation efficiency of an intelligent agent in a complex dynamic scene are remarkably improved.

The invention discloses a self-adaptive neural network continuous reaction kettle control method based on an observer, and the method comprises the following steps: constructing a kinetic model used for estimating the conversion rate of reaction components in a continuous reaction kettle and the change rate of reaction temperature, and calculating the change rate of the reaction temperature as the conversion rate of the reaction components and the change rate of the reaction temperature are unmeasurable system states; a state observer needs to be used for estimation; introducing a nonlinear mapping method to ensure that all states meet designed time-varying constraints; an unknown nonlinear dynamic function in a continuous reaction kettle is approximated by using a neural network, and a self-adaptive controller is designed based on a Lyapunov stability theory so as to deal with faults of an actuator and a sensor. According to the method, the internal states such as the conversion rate of reaction components of the continuous reaction kettle system can be estimated under the condition that the system state is unknown, the cost of the control system is reduced, and the efficiency is improved.

The invention discloses a whole-body collaborative voice control system and method for a humanoid robot, relates to the technical field of robots, and aims to solve the problems of semantic understanding superficial layer, action planning localization and safety control lagging in existing humanoid robot voice control. Through closed-loop cooperation of the multi-mode intention understanding module, the whole-body action planning module, the dynamic balance security arbiter and the microkernel security scheduler, a unified control architecture is constructed. According to the system, natural language instructions are deeply analyzed into whole-body motion constraints through a semantic-action mapping knowledge base, anthropomorphic collaborative motion trails are generated, pre-security verification is conducted through a boundary model based on Lyapunov stability, and finally hard real-time execution and full-cycle security guarding are achieved through a microkernel security scheduler. According to the method, direct conversion from natural language to safe, stable and anthropomorphic whole-body motion is realized, and the task execution capability and the interaction naturalness of the humanoid robot in a complex scene are remarkably improved.

The invention provides a pinned pulse safety synchronization control method and system of a multi-coupling time-delay network, and the method comprises the technical schemes: building a coupling time-delay dynamic network model, constructing a mathematical description of a random spoofing attack, designing a pinned pulse safety controller, and deducing a Lyapunov stability discriminant. Through defining an error system of a following network and a target network, under a pinned pulse safety control framework, based on a pulse system theory, system stability is analyzed, an attack probability is described in combination with a Bernoulli random variable, a pinned pulse control node selection strategy is finally designed, and safety synchronous control is successfully realized. The mechanism can effectively extract time delay information with a stabilization effect in a continuous system, and fuses the time delay information into the design of an anti-attack containment pulse safety controller, so that the synchronization safety of the system is remarkably improved, the resource allocation efficiency is optimized, and the attack influence is weakened by utilizing inherent time delay.

The embodiments disclose a financial transaction platform comprising a Stability Verification Engine coupled to a Transaction Input and configured to calculate stability functions using a Lyapunov Stability Engine to evaluate whether a proposed transaction converges toward equilibrium within a Stability Valley defined by threshold values in a Stability Function Database, a Deterministic Consensus Protocol coupled to the Stability Verification Engine and configured to process validated transactions through pre-commit verification, mathematical proof generation, and finality attestation to ensure irreversible acceptance, a Cascade Prevention System coupled to the Deterministic Consensus Protocol and configured to apply progressive intervention levels including enhanced verification, fee adjustment, transaction size limits, processing delays, and emergency stabilization when abnormal conditions are detected, and a Transaction Output coupled to the Cascade Prevention System and configured to forward transactions confirmed as stable and finalized to downstream predictive management and interface node systems.

The invention relates to the technical field of aircraft control, in particular to a four-rotor unmanned aerial vehicle robust trajectory control method based on a sliding mode control-improved extended state observer. The method comprises the following steps: firstly, establishing a nonlinear dynamic model of the quad-rotor unmanned aerial vehicle, and decomposing the system into a hierarchical control structure of a position outer ring and an attitude inner ring; secondly, a third-order extended state observer (ESO) is designed to estimate composite disturbance of each channel in real time, an improved sliding mode control law with observation error compensation is provided, and the vibration bearing phenomenon is effectively restrained; and finally, proving the asymptotic stability of the closed-loop system through the Lyapunov stability theory. The method is used for solving the problems of low trajectory tracking precision and control signal buffeting caused by underactuation, strong coupling nonlinear characteristics and external disturbance of the four-rotor unmanned aerial vehicle. High-precision trajectory tracking under complex disturbance can be realized, and control signal buffeting can be suppressed at the same time.

The invention discloses a converter transient power angle stability analysis method and system based on a linear parameter change controller. Establishing a small-signal dynamic model of the power synchronization type grid-following converter, and constructing a mathematical model considering power filtering and current loop dynamics by orienting an output current to a d axis of a dq coordinate system; a linear parameter change controller is designed, control parameters are adjusted in real time through parameter vectors, decoupling control over active power and reactive power is achieved, and it is ensured that the system can stably operate in both the inversion mode and the rectification mode; based on the Lyapunov stability theory, the transient power angle stability of the system under large disturbance is analyzed in combination with a linearization method and a direct method. The method does not need to depend on a phase-locked loop and grid-connected point voltage information, effectively solves the problem of synchronous stability of a traditional grid-following type converter, remarkably improves the adaptability and operation reliability of a system under the condition of a weak power grid, and provides important technical support for safe and stable operation of a new energy power system.

The invention provides a system behavior simulation and logic verification method and system based on a state machine model. The method comprises the following steps: constructing a state machine model of system behaviors; generating an intermediate representation code embedded with a time constraint check function, wherein the time constraint calculates a state transition time upper limit based on a Lyapunov stability model; compiling the executable code framework; receiving real-time operation data through a human-in-the-loop interface, mapping the real-time operation data into an input event, driving simulation operation, and dynamically rendering a state conversion process by adopting a virtual reality technology; verifying the behavior correctness based on the state coverage and a logic closed-loop index, wherein the logic closed-loop detects a deadlock risk through an improved banker algorithm; and if the verification is not passed, the recent valid state is traced back, the model is adjusted, and the verification is executed again. According to the method, the problems of inaccurate time sequence verification, insufficient real-time interaction, single verification index and the like in a traditional method are solved, and the accuracy and reliability of system simulation are remarkably improved.

The invention discloses an intelligent control method and system applied to a marine floating target, and the method comprises the steps: collecting target ship information and marine environment data in real time through a multi-mode sensor array, and carrying out the time-space alignment and fusion processing, and obtaining an environment state vector; based on the ship kinematics principle, wind and flow disturbance force is decomposed into resultant force and moment vectors under a ship body coordinate system; evaluating the danger degree of the current navigation environment through the dynamic risk index, carrying out navigation risk intelligent grading, and triggering a grading control strategy; a self-adaptive controller is designed based on the Lyapunov stability theory, anti-interference dynamic adjustment is carried out on the target ship, and track deviation caused by environmental interference is eliminated; when an obstacle or a high-risk sea condition is detected, intelligent obstacle avoidance and path re-planning are carried out, and an optimized path for avoiding the obstacle or a surge area is generated in real time; and calculating the minimum safety distance based on the ship dynamics model, and implementing a graded braking strategy to perform dynamic safety braking on the target ship.

The invention provides an unmanned surface vehicle course tracking control method with signal quantization based on a double-expansion observer, and the method comprises the steps: building a third-order response type unmanned surface vehicle course control mathematical model according to the characteristics of a ship and the sea condition information of a surrounding environment; designing a double-expansion observer model for simultaneously estimating matched interference and non-matched interference in the ship course tracking control system and observing uncertain items and external interference in the ship control system; based on a backstepping method and a dynamic surface control algorithm, a course controller of the unmanned surface vehicle is designed, and the calculation complexity brought by a virtual control law is reduced; based on the Lyapunov stability theory, the stability of the designed unmanned surface vehicle course tracking control system with state quantization and input quantization is proved, all signals in a closed-loop system are consistent and bounded in a semi-global mode, and the tracking error is arbitrarily small by adjusting parameters of a controller.

The invention provides a preset time fuzzy control method for a reentrant manufacturing system under intermittent state feedback, and the method comprises the steps: constructing a nonlinear error dynamic model, and employing a fuzzy modeling technology to represent the system as a combination of a plurality of linear subsystems; introducing a time scaling function, and transforming the error state of the global fuzzy model by using the time scaling function to obtain an error scaling state; an event triggering mechanism is designed to realize intermittent state feedback so as to reduce the communication cost; based on the Lyapunov stability theory, a sufficient condition that the system is stable within preset time is deduced, and a controller gain is obtained by solving a linear matrix inequality of the sufficient condition, so that the system still has robustness under external interference. Agile response and low-communication-cost operation of the reentrant manufacturing system within the preset deadline are realized.

The invention provides a multi-cylinder synchronous accurate control method for a hydraulic jacking system of a tower crane, and belongs to the technical field of tower cranes. A pressure sensor and a displacement sensor are mounted on each hydraulic cylinder of a hydraulic jacking system of the tower crane, and a force sensor is arranged at a key position of a tower body, so that a multi-parameter real-time monitoring network is established; an improved Gaussian kernel function nonlinear matrix mapping algorithm is adopted to calculate a pressure deviation coefficient and a displacement synchronization metric value between hydraulic cylinders, the pressure adjustment processing frequency is dynamically adjusted according to the pressure deviation coefficient value, and self-adaptive load balancing control is achieved through tower body stress unbalance threshold value calculation and stress adjustment gain calculation. And finally, the flow distribution of each hydraulic cylinder is adjusted through a proportional valve, and the convergence of the system is ensured by utilizing Lyapunov stability analysis, so that the technical problem that the multi-cylinder synchronous control of the hydraulic jacking system of the tower crane is not accurate enough is solved.

The invention relates to the technical field of power system frequency modulation control, and discloses a collaborative frequency modulation method and system of a hybrid flywheel energy storage system. The method comprises the following steps: constructing a hybrid energy storage array consisting of a power type flywheel array and an energy type flywheel array which are respectively responsible for millisecond-level frequency support and second-level frequency recovery; a double-layer cooperative control structure is designed, the upper layer carries out total power distribution and coordination based on power grid frequency deviation and change rate, and the lower layer carries out instruction execution through speed and current double-closed-loop control; a state manifold design based on a Lyapunov stability theory is introduced; and a self-adaptive gain adjustment mechanism is adopted, flywheel output is dynamically adjusted according to the real-time characteristic of frequency disturbance, and dynamic cooperative scheduling of the two types of flywheels under different time scale frequency fluctuations is achieved. According to the method, the adaptive capacity, the response speed and the control precision of the hybrid flywheel system to complex frequency disturbance are effectively improved, and the frequency stability of a power grid is enhanced.

The invention discloses an electric energy metering method and device based on harmonic self-adaptive observation and zero point tracking type SOGI-FLL. The electric energy metering method comprises the following steps: step 1, carrying out ADC sampling on voltage and current signals of a power grid; 2, performing frequency rapid estimation on the voltage signal based on a zero point tracking frequency-locked loop, and obtaining a fundamental wave angular frequency of a power grid in real time; step 3, constructing adaptive observers of voltage and current by using the fundamental wave angular frequency, and estimating parameters of fundamental waves, harmonic waves and direct current components in voltage and current signals in real time through an adaptive law based on Lyapunov stability; 4, according to the parameter estimation value, the amplitude and phase of the voltage and current are calculated; and step 5, calculating active power and reactive power of each harmonic based on the voltage and current amplitudes and phases obtained in the step 4, and summing to obtain total active power and total reactive power so as to realize metering of active electric energy and reactive electric energy. According to the invention, rapid and accurate metering of fundamental wave and harmonic wave electric energy under complex working conditions is realized.

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 relates to the technical field of hydroelectric engineering, in particular to a T-S fuzzy robust control method for a hydroelectric generating set adjusting system based on a linear matrix inequality, which comprises the following steps: establishing a system nonlinear mathematical model considering modeling uncertainty and external interference under a rigid water attack condition, and converting the system nonlinear mathematical model into an affine nonlinear state space form; a T-S fuzzy model is constructed, and precise approximation of global nonlinear characteristics is realized through linearization of a linear triangular membership function and representative working condition points; a fuzzy controller is designed based on a parallel distribution compensation strategy, and a robust control problem is converted into a linear matrix inequality form to solve a feedback gain matrix in combination with a Lyapunov stability theory and an H-infinity performance index. The method effectively improves the adaptability of the system to a complex operation environment, enhances the anti-disturbance capability, can significantly reduce the system oscillation, shortens the stabilization time, guarantees the safe and reliable operation of the hydroelectric generating set, and has important engineering application value.

The invention discloses a fault-tolerant control method for a discrete-time Markov jump power system, which belongs to the technical field of power system control and comprises the following steps of: introducing a hidden Markov process with unknown partial information to solve the problems of transient faults in a power line, subsequent switching of related circuit breakers and limited mode information of the power system; the influence of the fault-tolerant control of the power system on the stability is considered; establishing a controller model to obtain a closed-loop system model of the system; on the basis of the Lyapunov stability theory, sufficient conditions for ensuring the random stability of the closed-loop system and meeting expected performance are obtained; proving that the inequality condition is effective by utilizing a Lyapunov function and a performance index function; calculating a gain matrix of the controller by using simulation software; and realizing fault-tolerant control of the system according to the gain matrix of the controller and given system parameters. According to the invention, fault-tolerant control of the system can be realized based on a mode of combining performance index control and controller control.

The invention discloses a multi-mechanical-arm system random predefined time control method based on event triggering, belongs to the technical field of control, is used for time control of a multi-mechanical-arm system, and comprises the steps that a kinetic equation of the multi-mechanical-arm system is introduced, a track error tracking system is introduced, and a consensus error of the multi-mechanical-arm system is obtained; an unknown function in a kinetic equation of the multi-mechanical-arm system is estimated, a virtual control signal, a self-adaption rate and an event triggering mechanism are designed according to a self-adaption backstepping method, and stability analysis is conducted in combination with the Lyapunov stability theory. An event triggering mechanism is adopted at the same time, the updating frequency of the controller is reduced, and consensus errors of the experimental multi-mechanical-arm system can be converged into a small neighborhood within predefined time of 1 s in combination with the consensus errors of the experimental multi-mechanical-arm system.

The invention provides an electric vehicle lithium battery sensor fault reconstruction method under multiple disturbances, and relates to the technical field of energy storage system state monitoring and fault diagnosis. The method comprises the following steps: establishing a second-order RC equivalent circuit state space model of a lithium battery, and carrying out online identification on parameters in a battery model by adopting a recursive forgetting least square algorithm; a battery state and a sensor fault are regarded as new state variables, and an augmented system is obtained; an adjustable dimension observer is designed, and compromise between estimation precision and calculation cost is achieved by dynamically adjusting the order of the observer; defining an error variable, selecting a proper parameter matrix, and further deducing an error system; based on the Lyapunov stability theory, stability analysis is carried out on the error system, and stability conditions are given; and finally, performing simulation verification, and performing iterative optimization on the parameters according to a simulation result until satisfactory estimation performance is obtained.

The invention discloses an unmanned ship cluster tracking control method based on reinforcement learning and zero-sum game and a computer program product. The control method comprises the following steps: establishing a motion mathematical model of the three-degree-of-freedom unmanned ship considering external environment interference; based on an improved artificial potential field method, designing an unmanned ship cluster collision avoidance energy potential function; designing an unmanned ship cluster guidance strategy based on Lyapunov stability requirements; external disturbance and uncertain items of a system model are estimated through an adaptive Identifier neural network, and the robustness of an unmanned ship cluster is improved; and completing unmanned ship cluster trajectory tracking control by an Actor-Critic neural network based on a zero-sum game framework. The problem of collision avoidance inside the unmanned ship cluster, the problem of obstacle avoidance outside the cluster and the problem that the trajectory tracking performance is reduced when the cluster is attacked by FDI can be solved.

The invention discloses a safety control method of a high-order chain type multi-agent system under spoofing attack, and belongs to the technical field of safety control of multi-agent systems. The method comprises the following steps: establishing a dynamic model of a high-order chain type multi-agent system; constructing an extreme attack scene in which all communication links are subjected to bounded spoofing attacks; based on a backstepping control method, a distributed fixed time security control protocol is designed for a system, and the protocol counteracts attack influence by designing a virtual control strategy and a Lyapunov function; a Lyapunov stability theory is utilized to prove that under the action of the protocol, a system tracking error can be converged to zero within fixed time, so that safe and consistent tracking is realized. The defect that the prior art mainly aims at a linear system or only can realize asymptotic convergence is overcome, the method is particularly suitable for scenes such as non-complete constraint wheeled mobile robots, and the robustness and the rapid recovery capability of the system under extreme spoofing attacks are effectively improved.

The invention relates to the technical field of extraterrestrial celestial body landing obstacle avoidance, in particular to a landing obstacle avoidance trajectory planning method, system and equipment based on an error-considered voxel model and a medium. The method comprises the following steps: constructing a terrestrial body pixel model by using point cloud data acquired by a laser radar, establishing an obstacle body pixel error model containing three probability error regions through point error propagation, and quantifying the risk degree and uncertainty of each pixel block; in combination with a Gaussian distribution probability density function of land device position uncertainty and a constructed obstacle object pixel error model, calculating a collision probability; and integrating the calculated collision probability as a core component of the repulsive force potential into an artificial potential field method framework, deriving a control instruction based on the Lyapunov stability theory, and planning a safe landing trajectory.

A wind power generation system preset time maximum power point tracking control method comprises the following steps: firstly, establishing a wind power generation system dynamic model containing parameter uncertainty and external disturbance, and meanwhile, constructing a preset time convergence integral sliding mode surface; the method has the core advantages that the convergence time can be directly set by controller parameters and is irrelevant to the initial state of the system; secondly, designing a preset time self-adaptive controller based on the rotating speed tracking error and the sliding mode surface, and enabling the rotating speed tracking error to be quickly converged in preset time; the upper bound of lumped uncertainty of the system is estimated online through a self-adaptive mechanism, unknown dynamic and external disturbance are compensated in a unified mode, and dependence on an accurate model and disturbance prior knowledge is not needed; and finally, strictly proving the preset time stability of the closed-loop system through a Lyapunov stability theory. The method has good dynamic response performance and predictable convergence behaviors, and the robustness and the power generation efficiency of the system are improved.