21 results about "Fuzzy sliding mode control" patented technology

The invention discloses a fuel cell vehicle thermal management system and a construction method thereof, and the fuel cell vehicle thermal management system comprises a thermodynamic modeling module, a double-layer fuzzy sliding mode controller, an actuator cooperative control module, a working condition adaptive module and a fault protection module. According to the thermal management system of the fuel cell vehicle and the construction method of the thermal management system, the dynamic thermodynamic model is established, and the double-layer fuzzy sliding mode controller and the actuator cooperative control module are designed, so that millisecond-level high-precision tracking of the temperature of the electric pile and online real-time compensation of unknown disturbance are realized; meanwhile, stable operation of the system in the whole working condition domain range can be ensured through the working condition self-adaption module and the fault protection module, and the system has the advantages of being high in control precision, high in anti-interference capacity and good in system reliability.

The invention relates to the field of coiled material film covering industrial control systems, in particular to a multi-station cooperative intelligent control system for synchronous film covering of multiple coiled materials. The obtaining module obtains a unified state fusion matrix; a multi-station cooperation module; decision generation is carried out on an execution mechanism for synchronous film covering of multiple coiled materials, a prediction control mechanism is embedded in the decision process to serve as constraint processing, and a fuzzy sliding mode control strategy is introduced; an execution and correction module; the system is used for receiving and executing a multi-station coordinated regulation instruction set. According to the method, a multi-agent collaborative decision framework is constructed based on De-POMDP, each station is set as an independent agent, organic combination of local state perception and global collaborative decision is realized, interaction and combinatorial optimization of regulation and control plans of each agent are realized through a shared data pool, an optimal plan combination is screened in combination with a joint reward function, and the optimization of the regulation and control plans is realized. And it is ensured that the regulation and control instruction can accurately meet the actual requirement for synchronous film covering of multiple coiled materials.

The present invention discloses a vehicle fuzzy feedforward path tracking control method based on hydraulic steering leakage compensation. The method comprises: acquiring the steering wheel angle, wheel angle, and piston rod displacement; outputting desired wheel and steering wheel angles in different cycles using a path tracking algorithm; obtaining a feedforward leakage compensation parameter via fuzzy control; constructing a fuzzy control system; defuzzifying it using the centroid method to yield a fuzzy sliding mode controller; comparing the actual rear wheel angle; and controlling a compensation solenoid valve to replenish fluid each cycle. These steps are repeated for subsequent cycles until the path tracking process is complete. The method precisely determines the feedforward compensation parameter, thus accurately controlling the solenoid valve's duty cycle to timely compensate for leakage and enhance the path tracking accuracy of intelligent vehicles.

The invention belongs to the field of mechanical engineering, particularly relates to an intelligent speed regulation control system of a diesel engine, and aims to solve the problems of rotating speed response lag, low control precision and high energy consumption of an existing system under a dynamic load. The system comprises a real-time state sensing module, a composite error generation module, a multi-mode control decision module, an execution driving module and a self-learning optimization module. Smooth switching is realized based on mode arbitration by constructing a three-dimensional composite error feature matrix and fusing three strategies of feed-forward compensation, adaptive fuzzy sliding mode control and online reinforcement learning; and high-precision oil injection execution and offline knowledge extraction are combined, so that the dynamic response, the steady-state precision and the energy efficiency performance are improved.

The invention discloses a low-damping air flotation system hybrid control method integrating intelligent parameter setting, and the method comprises the steps: obtaining a controlled object model according to the sweep frequency of an open-loop system and system identification, and constructing a closed-loop hybrid control model based on proportional integral differential control, speed / acceleration feedforward control and fuzzy sliding mode control; a closed-loop control framework is built by continuously calculating system output and control errors; a two-stage intelligent parameter setting method based on genetic algorithm preliminary setting and manual accurate setting is adopted to complete parameter adjustment of a hybrid control algorithm; and writing the hybrid control model into PMAC hardware, optimizing and adjusting control parameters according to step and sine response tests, and realizing high-precision machining of the low-damping air flotation system. According to the method, the response speed and the control precision of the system can be remarkably improved, nonlinear disturbance in a complex machining task can be adapted, and the parameter setting problem in actual engineering can be solved.

This invention discloses a BIM-based hoisting construction supervision and optimization management system, comprising: a perception layer: real-time acquisition of multi-source heterogeneous data; a decision layer: the bottom layer uses an incremental RRT# algorithm to generate candidate paths that satisfy the kinematic constraints of the crane, and the upper layer embeds a distributed Q-learning framework, where each crane acts as an independent intelligent agent, collaboratively learning through a shared experience pool, dynamically optimizing path planning strategies based on environmental perception data and construction progress requirements, and simultaneously developing a fuzzy sliding mode control algorithm combined with an LSTM-Transformer model of crane trolley and hook travel speeds and hook lifting speeds, as well as a wire rope disturbance prediction model to calculate crane motion compensation parameters, and generating optimal control commands in advance based on predicted crane movement and lifting data; an execution layer: the commands generated by the decision layer are issued to the construction equipment; and an optimization layer: a BIM model is constructed, and the equipment execution results and structural safety monitoring data are fed back to the decision layer.

The invention discloses a magneto-rheological damping suspension fuzzy sliding mode control method based on unscented Kalman filtering, and relates to the technical field of magneto-rheological damping suspension control. Through an innovative inner and outer double-loop control architecture, the output of an inner-loop sliding mode controller is subjected to online intelligent correction and compensation by using an outer-loop fuzzy controller; the inherent buffeting problem of sliding mode control is effectively restrained, control force output is smoother, and the riding comfort is improved. Meanwhile, according to the scheme, an unscented Kalman filter observer is integrated in an inner ring, the key state and uncertain disturbance in the system can be accurately estimated in real time according to limited measurement data, high-quality state information is provided for the sliding mode controller so as to ensure the control accuracy, and the system reliability is improved. And moreover, by generating the compensation force, the inhibition capability of the whole system on model uncertainty and external interference is further enhanced, and the robustness of the suspension and the adaptability to complex road conditions are remarkably improved.

The application discloses an interval type-2 fuzzy sliding mode control method based on a parameter uncertain inverted pendulum system and belongs to the technical field of nonlinear system control, and comprises the following steps: establishing an interval type-2 T-S fuzzy model of the parameter uncertain inverted pendulum system; constructing a sliding mode controller of the parameter uncertain inverted pendulum system based on the interval type-2 T-S fuzzy model; the sliding mode controller comprises a sliding surface, an equivalent controller, a switching controller and a comprehensive controller; the sliding surface is used as the only input variable of the fuzzy controller, the switching gain is dynamically controlled by using a fuzzy logic rule, and the sliding mode controller is optimized into an interval type-2 fuzzy sliding mode controller. The application solves the problem that the prior art cannot ensure that the parameter uncertain inverted pendulum system is stably operated on a sliding surface and is prone to chattering when parameters change and external disturbances occur.

The invention discloses a double-swing-angle main shaft with self-adaptive vibration suppression and online dynamic balance functions and a vibration suppression method thereof.The double-swing-angle main shaft comprises a shaft C, a shaft A, a sensor system, a signal collecting and processing unit and a control unit, the shaft A is hinged to one end of the shaft C, and the shaft A is provided with an electric sliding block and an eccentric adjusting motor; the sensor system is used for collecting signals in the machining process of the double-swing-angle main shaft in real time, the signal collecting and processing unit is used for obtaining the signals collected by the sensor system and processing the signals, and the vibration error amount and the error change rate are obtained through calculation. A compensation instruction quantity is calculated according to the vibration error quantity and the error change rate through a fuzzy sliding mode control strategy, and the control unit is used for controlling the electric sliding block to move and controlling the eccentric adjusting motor to rotate according to the compensation instruction quantity. The compensation control quantity is calculated according to the vibration signals collected in real time, the movement of the electric sliding block and the rotation of the eccentric adjusting motor are controlled to level the dynamic balance of the double-swing-angle main shaft, and the operation stability and the machining surface quality of a main shaft system are improved.

The invention discloses a bandwidth limited system T-S fuzzy sliding mode control method based on an adaptive WTOD protocol, and belongs to the technical field of industrial control and intelligent manufacturing. The method comprises the following steps: establishing a T-S fuzzy networked system model containing time-varying and time-lag; designing a self-adaptive WTOD transmission protocol integrated with a uniform quantization mechanism; constructing a fuzzy sliding mode controller based on the available system state information; giving out discrimination conditions for ensuring that the indexes of the T-S fuzzy networked system are bounded and the sliding mode surface is reachable in an inequality group form; converting an inequality group discrimination condition containing linear coupling into a minimization problem by adopting cone complementary linearization; and optimizing the final upper bound of the closed-loop system state and the upper bound of the sliding mode surface reaching neighborhood based on a particle swarm algorithm. According to the method, the cooperative improvement of the control performance and the communication efficiency is ensured, and a verifiable and easy-to-implement unified analysis and design framework is provided for the bandwidth-limited networked nonlinear system.

The application discloses a ball and link system control method based on fuzzy sliding mode and periodic event triggering, first constructs a state space equation of the system and carries out regular transformation to obtain a standard system model; then, a fuzzy sliding mode switching function is established in combination with a fuzzy membership function, and a periodic event triggering mechanism is designed; on the basis, a periodic event triggering fuzzy sliding mode controller is constructed, an actual sliding mode band is constructed by analyzing a periodic sampling error, state trajectory is ensured to enter the band in a limited time and remain in the band, and the reachability of the sliding mode surface is ensured; then, a controller gain matrix is solved based on stability analysis of the sliding mode, is brought into the controller to complete closed-loop control on the ball and link system, and a system sampling period is established. The application uses the fuzzy membership function to design the sliding mode surface, has lower conservativeness, and uses the periodic sampling to design the event triggering mechanism, theoretically eliminates the Zeno phenomenon, and provides an efficient control scheme for a system with limited network and communication resources.

This invention relates to a control method for a fast-reflecting mirror based on fuzzy sliding mode control, belonging to the field of optical device control technology. The method includes the following steps: S1: Constructing a mathematical model of the fast-reflecting mirror; S2: Constructing a state-space expression based on the mathematical model of the fast-reflecting mirror; S3: Designing a sliding mode controller, designing the sliding surface based on the state-space expression, determining the reaching law, deriving the sliding mode control law, and verifying its feasibility; S4: Designing a fuzzy controller, establishing fuzzy rules, and selecting appropriate defuzzification processing; S5: Constructing a fuzzy sliding mode controller based on the fuzzy controller and the sliding mode controller, and achieving high-precision control of the deflection angle of the voice coil motor-driven fast-reflecting mirror based on the fuzzy sliding mode controller. This invention improves the response speed of the fast-reflecting mirror during deflection and reduces the influence of external interference during the deflection of the fast-reflecting mirror.

The invention discloses a photovoltaic greenhouse winter environment control method based on variable universe fuzzy sliding mode control, and belongs to the technical field of agricultural environment control. The invention aims to solve the problems of greenhouse temperature and humidity coupling interference in winter, difficult control cooperation, weak anti-interference capability of a traditional controller and the like. The method comprises the following steps: establishing a greenhouse temperature and humidity balance model in winter and daytime, including a temperature balance equation reflecting heat change and a humidity balance equation reflecting water vapor mass change; performing feedback linear decoupling on the model to obtain independent temperature and humidity control channels; designing a variable universe fuzzy sliding mode controller, and realizing cooperative control of heating and humidifying equipment by constructing an integral sliding mode surface and a fuzzy rule table and introducing a nonlinear telescopic factor to dynamically adjust the universe; and constructing a Lyapunov function to verify the stability of the system. According to the invention, the control precision and the anti-interference capability are effectively improved, and a suitable crop growth environment in the greenhouse can be stably maintained.

The invention provides a self-adaptive fuzzy sliding mode control system for a mobile robot, and the system is configured to execute the following control processes: step 1, calculating a pose error between an actual pose and an expected track of the mobile robot based on the input of a multi-source sensor system; step 2, executing an adaptive fuzzy sliding mode control algorithm; 3, executing a field-oriented control algorithm: converting the linear velocity and angular velocity control signals into a phase current instruction for a brushless direct current motor through a field-oriented control technology so as to realize high-precision torque and rotating speed control; step 4, updating pose estimation through sensor data fusion, forming closed-loop control, and realizing robust trajectory tracking in an uncertain dynamic environment; through deep cooperation of the AFSMC and the FOC, dual-core task partitioning and continuous switching functions, the system can effectively suppress high-frequency buffeting, and meanwhile, the tracking precision and the energy efficiency are improved. The method is suitable for various mobile robot platforms.

The invention discloses an electric heavy truck path tracking control method and device based on a self-adaptive interval type-2 fuzzy second-order sliding mode under the influence of crosswind, a storage medium and an automobile, and belongs to the field of intelligent traffic. Comprising the steps that 1, disturbance factors existing in the driving process of the electric heavy truck are analyzed, and an electric heavy truck dynamic model and a path tracking model are constructed; 2, estimating a course-related unknown state and lumped disturbance by using an interval type-2 fuzzy logic system; 3, selecting a proper sliding variable, establishing a second-order sliding mode kinetic equation, and describing a dynamic relationship and disturbance suppression of a system state tracking error; and 4, designing a self-adaptive interval type-2 fuzzy sliding mode controller to realize a path tracking target. The method has the advantages that 1, the method has higher robustness on parameter change and external interference; 2, the buffeting phenomenon in the control process can be reduced, and the stability and reliability of the system are improved; and 3, the dynamic response speed and the control precision of the system are improved while the stability of the system is ensured.

The application provides a thermal power unit steam temperature control method and device, relates to the thermal power generation technical field, and the method comprises the following steps: obtaining a first adjustment weight related to a control variable and a second adjustment weight related to a compensation amount according to the operation condition of the thermal power unit; obtaining a first compensation amount according to a first input array related to the steam temperature of the thermal power unit and a prediction model constructed based on an improved Transformer on the basis of the first adjustment weight, obtaining a second compensation amount according to the first input array, the operation condition, the prediction model and a steam temperature control model constructed based on an adaptive fuzzy sliding mode control algorithm, and obtaining a third compensation amount according to an external disturbance amount; and obtaining a control instruction according to the first compensation amount, the second compensation amount, the third compensation amount and the second adjustment weight. The method can ensure that the steam temperature of the thermal power unit is close to a set value, realize the control target of reducing the main reheat steam temperature fluctuation, reducing the amount of desuperheating water, improving the operation efficiency of the unit and maintaining the operation safety of equipment.

A kind of mechanical arm trajectory tracking control method of optimizing fuzzy sliding mode control belongs to industrial robot control technical field, solve the technical problem that traditional mechanical arm trajectory control method system output produces chattering phenomenon, including the following steps:1, obtain the desired trajectory information of mechanical arm;2, establish n degree of freedom mechanical arm dynamics model;3, design sliding surface s and exponential approach law 4, design three coefficients as the gain between input and output of fuzzy controller and sliding mode controller, and use the solution three coefficients using reptile algorithm to optimize membership function;5, design the input of fuzzy controller is sliding surface and the derivative of sliding surface, the switching gain of exponential approach law is output, and the corresponding membership function and fuzzy logic are designed;6, obtain the controller based on reptile algorithm optimization fuzzy control, realize trajectory tracking control.The application effectively realizes mechanical arm trajectory tracking control, has faster response speed, reduces the chattering phenomenon of control output.

The invention discloses a safety triggering sliding mode control method based on a Paillier encryption mechanism. The method comprises the following steps of 1, establishing a T-S fuzzy system model with time varying and time lag; 2, designing a dynamic event triggering mechanism based on membership function dependence; 3, realizing encryption of a trigger state signal based on a Paillier encryption algorithm; 4, realizing encryption of the control signal based on the Paillier semi-homomorphic property; 5, obtaining a decrypted fuzzy sliding mode control law based on a Paillier decryption algorithm, inverse mapping and a scaling coefficient, and obtaining a closed-loop fuzzy system; and 6, giving a discrimination basis which ensures that the indexes of the closed-loop fuzzy system are finally bounded and the sliding mode surface is reachable in the form of a linear matrix inequality group, and establishing an optimization problem to solve a controller gain matrix. The problem that system performance and sensitive information safety are difficult to consider in an existing sliding mode control method is solved.

The invention discloses an interval type-2 fuzzy sliding mode control method based on a parameter-uncertain inverted pendulum system, and belongs to the technical field of nonlinear system control, and the method comprises the steps: building an interval type-2 T-S fuzzy model of the parameter-uncertain inverted pendulum system; constructing a sliding mode controller of the inverted pendulum system with uncertain parameters based on the interval type-2 T-S fuzzy model; the sliding mode controller comprises a sliding mode surface, an equivalent controller, a switching controller and a comprehensive controller; and taking the sliding mode surface as a unique input variable of a fuzzy controller, and dynamically controlling a switching gain by using a fuzzy logic rule to optimize the sliding mode controller into an interval type-2 fuzzy sliding mode controller. The problems that in the prior art, it cannot be ensured that the inverted pendulum system with uncertain parameters stably operates on the sliding mode surface, and the chattering phenomenon is likely to be generated when the parameters change and external disturbance occurs are solved.

This invention provides a bit-flip-resistant sliding mode control method for T-S fuzzy systems with energy-dependent noise, belonging to the field of industrial control and intelligent manufacturing technology. The invention includes the following steps: establishing a T-S fuzzy networked system model with time-varying delays; designing a bit-flip-resistant redundant encoding / decoding strategy to correct measurement signal transmission errors; constructing a sliding surface and a fuzzy sliding mode controller based on the decoded output signal; suppressing control signal transmission noise and constructing a closed-loop system using an analog signal decoupling transmission mode; providing sufficiency criteria for the bounded mean square exponent and reachability of the sliding surface of the closed-loop system using a system of inequalities; and handling non-convex constraints and solving the controller gain matrix using a cone-complement linearization algorithm. This invention ensures the control performance of the system under channel-constrained conditions and provides a comprehensive design scheme for networked nonlinear systems under multi-source interference, balancing communication reliability and control accuracy.

The invention provides an Akman steering motion trajectory optimization method based on a two-wheel differential AGV, and belongs to the technical field of automatic logistics transportation. The method comprises the following steps: constructing a four-wheeler kinematics model; establishing longitudinal braking dynamics; aiming at the characteristics of the two-wheel differential AGV, designing a fuzzy sliding mode controller; setting a sliding mode control law of the anti-lock braking system; setting fuzzy sliding mode control of the anti-lock braking system; wheel slipping and abnormal conditions are monitored and controlled; and multi-AGV cooperative motion control is carried out. The control precision of the steering angle of the four-wheeler is improved, it is ensured that the motion trail of the four-wheeler is highly matched with the expected height, the cooperative operation effect is improved, accurate differential control is achieved, wheel abrasion is reduced, the running stability of the four-wheeler is enhanced, external interference is quickly responded, trail tracking jitter is effectively restrained, vehicle running safety is guaranteed, and the control real-time performance is improved. The motion state of the vehicle can be rapidly adjusted under complex working conditions, and the overall operation efficiency is improved.