380 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 discloses a six-rotor unmanned aerial vehicle control method and system with disturbance and performance constraints. The method comprises the steps that 1, a six-rotor unmanned aerial vehicle power model is built; 2, errors are determined based on the dynamic model, functions are combined, and a finite time scheme is determined; step 3, based on the dynamic model, establishing an observer, and knowing a disturbance state; step 4, a performance control scheme and an unknown disturbance state are stipulated in finite time, an error dynamic model is established, and the error dynamic model is established based on reinforcement learning; 5, setting a base scheme, setting a virtual controller and an actual controller, and setting an adaptive law for the base neural network; 6, the controller follower can track the leader, and tracking control is completed; establishing a controller by adopting a backstepping method, establishing a disturbance observer, and compensating negative effects; a reinforcement learning algorithm and a backstepping method technology are combined, and a controller is arranged to realize control; according to the method, the stability is proved by using a Lyapunov judgment stability theory, and the feasible effectiveness is verified by a simulation example.

The invention relates to the technical field of power electronic control, and discloses a voltage and current stabilization and surge suppression cooperative control method for power equipment, and the method comprises the following steps: dynamically segmenting an output current frequency band, and remodeling the output impedance characteristics of a system; predicting and controlling a hierarchical optimization control target based on a multi-time scale model; dynamically switching an energy feedback path; identifying aging parameters of the device on line and adaptively adjusting a control strategy; global stability verification and fault-tolerant protection: verifying the stability of the control system based on the Lyapunov stability theory, and triggering a protection mechanism when the magnetic flux is saturated or the aging of the device exceeds the limit. By means of dynamic impedance frequency domain segmentation, the impedance characteristic of the system is divided into a low-frequency voltage stabilization area and a high-frequency surge suppression area according to frequency bands, the contradiction that in a traditional method, it is difficult to consider steady-state precision and transient surge suppression at the same time due to the single impedance characteristic is solved, and collaborative optimization of voltage stabilization control and surge energy blocking is achieved.

A preset time robust sliding mode control method for a mechanical arm system comprises the steps that (1) under the condition that parameter perturbation, joint friction and external disturbance are considered, a dynamic model and a tracking error system model of the mechanical arm system are established; (2) a robust preset time controller is designed to ensure that the speed tracking error of the mechanical arm converges to zero within preset time; 3) designing a non-singular fast terminal sliding mode controller based on a preset time reaching law so as to ensure that a position tracking error can also converge to zero within the preset time; 4) the feasibility and effectiveness of the method are verified by using a Lyapunov stability analysis method; aiming at a mechanical arm system with parameter perturbation, joint friction and external disturbance, the invention develops a robust nonsingular fast terminal sliding mode control method in preset time so as to ensure that the mechanical arm system can accurately track an expected trajectory signal in the preset time, so that the tracking speed of a mechanical arm is improved, and the tracking precision is improved. And the tracking accuracy and safety of the mechanical arm are ensured.

The invention discloses a security boundary consistency control method for a multi-agent spatio-temporal dynamic system. The method specifically comprises the following technical steps: firstly, constructing a leader-follower spatio-temporal dynamic mathematical model of the multi-agent system based on a partial differential equation; then establishing an abnormal working condition mathematical model containing an actuator fault and a network spoofing attack; deducing to obtain an error dynamic system equation by defining a system consistency control target; constructing an energy function by using a Lyapunov stability theory, and deducing to obtain a system stability criterion; finally, a security boundary consistency control method is designed, and multi-agent space-time dynamic consistency control is achieved. The method effectively solves the problem of high cost caused by arrangement of actuators in a whole spatial domain in a traditional scheme and the problem that a multi-agent system is easily interfered by network attacks in a communication process, and has remarkable application value in engineering practice.

The invention relates to the technical field of digital control switching power supplies, and particularly discloses a switching power supply dynamic response adjusting system based on digital control, which comprises a digital controller, a multi-channel analog-to-digital conversion module, a parameter identification module, a self-adaptive control law adjusting module, a pulse width modulation driving module and a stability monitoring module. On-line identification of key parameters of a system is realized by constructing a nonlinear state space model and combining an extended Kalman filtering algorithm, dynamic compensation is carried out for non-minimum phase characteristics such as a right half plane zero point, and a self-adaptive control law adjustment module optimizes a control strategy in real time according to an updated model. A Lyapunov stability criterion and a predictive control mechanism are introduced, the robustness and response speed of the system are improved, and a stability monitoring module identifies an abnormal state through sliding window variance analysis and peak detection and triggers a fault-tolerant mechanism to guarantee safe operation of the system.

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 discloses an air-ground cooperative system model prediction formation control method in an underground pipe gallery environment, and the method comprises the steps: constructing an air-ground cooperative system nonlinear model, and constructing an underground pipe gallery model; designing a high-order interference observer to estimate current unknown external disturbance, and establishing an interference prediction model to estimate future unknown external disturbance; a rolling optimization control strategy based on state prediction is designed, control signals of all followers are optimized according to the current state of the system and the predicted future state in each control period, and the tracking precision is ensured while the tracking precision is improved. Collision between followers, collision between the followers and the wall of the pipe gallery and obstacle avoidance between the followers and static and dynamic obstacles in the pipe gallery are achieved; and solving is carried out based on a distributed model prediction formation control algorithm combined with a Lyapunov stability theory, so that each follower keeps an expected formation configuration while tracking a leader trajectory. And the driving safety of the formation in the underground pipe gallery environment is ensured.

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 invention relates to a clamping force constraint backstepping sliding mode control method for an electronic mechanical braking system, and belongs to the related technical field of new energy automobile control. The method comprises the following steps of: establishing a state space model of the system by considering the nonlinear characteristic of the electronic mechanical braking system, and reasonably simplifying the state space model into a strict feedback form; a time-varying tangent barrier Lyapunov function (BLF) containing an error integral term is constructed, an exponentially decayed time-varying function is used as a constraint boundary of a clamping force tracking error, the integral term is introduced to eliminate a steady-state error caused by unmodeled dynamics, and the output constraint performance and tracking precision of a system are ensured; on the basis, a control law is designed by combining a backstepping method and non-singular fast terminal sliding mode control, and fast and accurate tracking of the braking clamping force is achieved; and proving the system stability based on the Lyapunov stability theorem. According to the invention, the braking response time and the clamping force control precision of the electronic mechanical braking system can be effectively improved.

The invention discloses a multi-agent sliding mode safety control method based on dynamic event triggering under hybrid network attack, and the control method comprises the following steps: building a multi-agent system model comprising spoofing attack and DoS attack; in order to cope with hybrid network attacks, an integral sliding mode surface function is constructed, an online estimation method is provided, and an unknown network attack mode can be estimated in real time in the absence of prior information; a novel self-adaptive sliding mode controller is developed, and the accessibility of a preset sliding mode surface is ensured; by introducing an auxiliary variable, a dynamic and static event triggering mechanism in the framework is considered, so that the use of communication resources is minimized; a Lyapunov stability theory and a finite time method are utilized to analyze the convergence of the multi-agent system under the control strategy. According to the control method provided by the invention, the influence of spoofing attack and DoS attack on the system can be eliminated, so that the state of the multi-agent system is consistent within finite time.

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 provides a double-input-signal virtual power system stabilizer optimization method, and relates to the technical field of power system stability control. Multi-source signals during VPSS operation are collected in real time and subjected to normalization processing, a one-dimensional time sequence signal is converted into a two-dimensional image matrix through a GASF and a GADF, and the time dependence and the dynamic phase relation of the signals are completely reserved; the physical variable frequency-power coupling is coded through a multi-channel GAF matrix; a lightweight convolutional neural network is adopted, optimization features are extracted from a GAF matrix, and VPSS control parameters are dynamically adjusted by combining a near-end strategy optimization algorithm with Lyapunov stability guarantee; introducing an online learning mechanism and an abnormal switching strategy; a closed-loop framework of signal acquisition, feature coding, mode extraction, parameter optimization, control output and abnormity recovery is adopted, system response is fed back in real time, parameters are adjusted to balance dynamic performance and steady-state efficiency of the system, and the VPSS3B is made to adapt to various operation conditions of access of the network-building type converter.

The invention relates to a time delay optimization calculation unloading strategy for a satellite-to-ground fusion network, and the strategy comprises the following steps: 1, constructing a satellite-to-ground fusion network system model which comprises a network model, a satellite-to-ground link communication model, a queue model, a local equipment calculation model, an LEO satellite calculation model, and a ground cloud calculation center calculation model; problem description is carried out; step 2, based on a Lyapunov stability theory, decoupling a long-term mixed integer nonlinear programming optimization problem into sub-optimization problems of each time slot; 3, converting each time slot calculation unloading problem into a Markov decision process, and solving by using a deep reinforcement learning algorithm; designing a double-strategy network model structure of the Actor module to generate a strategy; and finally, exploring a better unloading strategy by using a ternary order-preserving quantizer, and accelerating model convergence. According to the method, the dynamic regulation and control of the terminal and the low-orbit satellite task queue can be realized, and the long-term stability of the unloading process and the continuous availability of computing resources are improved.

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 provides an underactuated unmanned ship multi-constraint trajectory tracking control method based on a disturbance observer, and the method comprises the steps: building a trajectory tracking control mathematical model of an unmanned ship, and converting the model into an underactuated unmanned ship trajectory tracking control mathematical model in view of the human underactuated characteristics of the unmanned ship under the actual sea condition; a composite quantizer is adopted to quantize control input, and a linear analysis model is used to describe an input quantization process; solving an input constraint problem by using a saturation function; designing a disturbance observer, a longitudinal propulsive force control law and a bow turning torque control law, and obtaining an adaptive law of trajectory tracking of the under-actuated unmanned ship; an event triggering mechanism based on a time-varying threshold value is introduced, and a control law of the under-actuated unmanned ship system is updated; on the basis of the Lyapunov stability theory, it is proved that all signals in the whole closed-loop control system are finally bounded on the basis of the stability of the anti-interference and multi-constraint under-actuated unmanned ship trajectory tracking control system when priori information of parameters does not need to be quantized.