17 results about "Good control" patented technology

The control system and method of the sock moving grabbing device have the advantages of being high in intelligent degree, good in control precision, high in self-adaptability and the like, the machine vision and sensor fusion technology is introduced, the edge position of a sock toe and the sock material characteristics are recognized in real time, and the sock moving grabbing device can be controlled in real time. Key parameters such as the opening angle, the downward moving distance and the folding time of the sheet grabbing needle are dynamically calculated based on a self-adaptive control model, and the socks of different specifications are accurately grabbed; meanwhile, a closed-loop control strategy and an online learning mechanism are adopted in the system, control parameters can be corrected in real time in the grabbing process, the grabbing success rate and stability are improved, the problems that in the prior art, sock bodies are prone to falling off, clamping stagnation is prone to occurring, and diversified production requirements are difficult to meet are effectively solved, and the automation level and production efficiency of the sock moving procedure are remarkably improved.

The application provides a cascade type multi-level rectifier topology and a control method thereof, a data model is established based on the topology, is discretized, a prediction model is formed, a reference voltage vector at a next moment is predicted, two basic voltage vectors closest to the reference voltage vector are selected by using a first value function, the action time of the two basic voltage vectors is calculated respectively, the action time is distributed to the corresponding basic voltage vectors, and double vector control is realized. The application can have the advantages of various topologies, has less current ripple, and has good control effect.

The application relates to a predictive control method and device based on an unknown parameter model, wherein the method comprises the following steps: parameter setting is performed on an unknown parameter model used for simulating a controlled real system to obtain model parameters; the model parameters of the unknown parameter model are updated through an adaptive observer, and a terminal domain of the unknown parameter model is calculated; based on the model parameters of the unknown parameter model, the adaptive observer and the terminal domain of the unknown parameter model, iterative calculation of a control quantity of the controlled real system is repeatedly performed, and when the number of times of the iterative calculation reaches a preset total iteration number, an optimal control quantity of the controlled real system is obtained. Through the application, the problem of how to perform predictive control based on an unknown parameter model is solved, the model parameters are updated based on the adaptive observer and are input into the unknown parameter model, the best control quantity is calculated by the model using the terminal domain, the robustness of the system is improved, and good control performance is achieved under the condition that the model parameters are unknown.

The invention discloses a dual-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control, and the method comprises the steps: S1), building a novel kinematics and dynamics model of a dual-rotor unmanned aerial vehicle, and constructing a complete model from input to control; s2) constructing an expansion state observer and a corresponding rule thereof in an inner layer by using active disturbance rejection control; s3) performing accurate sensing and recording on the attitude of the unmanned aerial vehicle on the outer layer by applying fuzzy control; and S4) constructing a cascade optimization strategy including analog control and active disturbance rejection control. According to the method, fuzzy control and active disturbance rejection control are integrated into a control framework of the double helicopters, the complexity of a dynamic model is solved, it is ensured that the unmanned aerial vehicle has excellent controllability and responsiveness in various foreign scenes, the control method of the double-helicopter unmanned aerial vehicle is enhanced, and the control efficiency of the double-helicopter unmanned aerial vehicle is improved. The method particularly focuses on the anti-interference control field of the double-helicopter unmanned aerial vehicle, has a good control effect, and can be widely applied to other anti-interference control systems.

The invention discloses a marine lightering device tail end horizontal stability maintenance control method based on NTSMC, and the method comprises the following steps: S1, building a horizontal luffing mechanism kinematic model based on kinematic analysis; s2, establishing a function relationship between the amplitude variation angle and the stroke of the driving device by using the mathematical model of the driving device and the kinematic model of the amplitude variation mechanism; s3, establishing a driving device mathematical model; s4, deducing an NTSMC control law by using the driving device mathematical model; and S5, establishing a system control model in combination with the NTSMC control law and the luffing mechanism transmission relationship. The method has relatively good control robustness and control precision, can realize efficient and safe lightering operation of personnel and materials, and is suitable for equipment for personnel and material maritime lightering such as a maritime wind turbine embarkation device; according to the invention, the safety and efficiency of the lightering operation of offshore personnel and materials can be obviously improved.

The application discloses a vehicle control method and a driving direction control system, which acquires the lateral deviation of a vehicle from a lane center line in real time, and when a preset compensation condition is met, dynamically compensates a proportional integral differential controller for lateral control according to the lateral deviation and its associated characteristic parameters, and then generates a direction correction instruction to adjust the driving direction of the vehicle. The method can adaptively match the PID control parameters to the current driving condition, effectively overcome the defects of response lag or control overshoot of fixed parameter control in complex scenes, significantly improve the accuracy and stability of the vehicle in the middle of the lane, and maintain good control performance under different conditions.

The invention discloses an intelligent five-constant air heating and ventilation integrated control system which comprises a master control, a master control display screen and a plurality of sub-controls, and the master control display screen and the sub-controls are connected to the master control. Each branch controller comprises a main control board, an intelligent chain 4G-OTA, a dew point panel, a water mixing panel, an intelligent hub, a five-in-one sensor, a heat pump host, a fresh air host and an intelligent chain WIFI-DTU or an intelligent chain 4G-DTU, wherein the intelligent chain 4G-OTA, the dew point panel, the water mixing panel, the intelligent hub, the five-in-one sensor, the heat pump host and the fresh air host are connected to the main control board. A Modbus communication module, a peripheral data integration module, a centralized control core coordination module, a data storage module, a fault judgment module and a 4G networking diagnosis module are integrated on the main control board. The system is high in control integration level, good in control coherence between the master control and each sub-control and between each sub-control and each specific function system, capable of communicating with common peripherals in the heating and ventilation field such as a fresh air ventilator, a heat pump host, a dew point panel and a water mixing panel, and capable of achieving constant and comfortable indoor environment according to related control logic. The use comfort is good, and the overall cost can be effectively controlled.

This invention discloses a lateral balance control method for unmanned bicycles based on adversarial imitation learning. The method uses the lateral tilt angle, handlebar angle, and angular velocity of the unmanned bicycle as the system state, and the handlebar control torque as the continuous control input. It combines expert demonstration data of the unmanned bicycle under stable lateral balance control conditions, collected or loaded, to initialize a policy network and a discriminant network, constructing an adversarial imitation learning framework. During training, the policy network interacts with the dynamic environment of the unmanned bicycle to generate state-action samples. These samples, along with the expert demonstration data, are simultaneously input into the discriminant network. An imitation reward signal is constructed based on the output of the discriminant network, and a policy gradient method with pruning constraints is used to alternately update the policy network and the discriminant network. This allows the control behavior generated by the policy network to gradually approximate the expert demonstration behavior in a distributional sense, thereby obtaining a stable lateral balance control strategy for the unmanned bicycle. By introducing an adversarial imitation learning mechanism, this invention achieves effective learning of the control strategy without explicitly designing complex artificial reward functions. Furthermore, under disturbance conditions, the method can still maintain the lateral balance of the unmanned bicycle, demonstrating good control stability and anti-interference ability, and has good engineering feasibility and application promotion value.

This invention discloses a distributed satellite attitude cooperative anti-saturation control method at a predetermined time. First, a SAR satellite formation model considering saturation constraints is established. Then, a preset performance boundary function that converges within a specified time is designed. Next, problems such as external interference and actuator saturation constraints in the satellite formation flight system are addressed. Finally, a SAR satellite attitude cooperative control law at a predetermined time is designed based on an anti-saturation compensator, an interference observer, and sliding mode control. This invention enables the formation satellites to achieve convergence of attitude cooperative errors within a specified time under actuator saturation constraints, while remaining within the preset performance boundary. It also features high control accuracy, good control performance, and fast convergence speed.

The application designs a performance promotion method of active suspension system tracking control, relates to unknown nonlinear systems, and is applied to the active suspension system of an automobile; an intelligent controller is designed based on the backstepping recursion method and the adaptive control method; firstly, a finite time performance function model is established; secondly, stress analysis is conducted on the quarter active suspension system based on Newton's second law, a dynamics model of the suspension system is established, and the state equation based on the finite time performance function is converted; then, the nonlinear active suspension system is identified by using a neural network; an adaptive law and a controller are designed based on the Lyapunov function and the backstepping recursion method; the system is analyzed in the light of the Lyapunov stability theory, and it is proved that all signals are bounded; finally, simulation experiments are conducted by using MATLAB, and it is proved that the method has good control effect.

The application discloses a kind of based on expert self-disturbance controller's piling machine vibration frequency control method, first utilize the differential tracker in self-disturbance controller to the input signal arrangement transition process and extract its differential signal, then expansion observer carries out real-time dynamic estimation and compensation to the total disturbance of system, then the output of differential tracker is combined with the output of expansion observer and is input to expert controller and nonlinear combination link, expert controller is adapted to the key parameters of nonlinear combination link according to input range, finally the output of nonlinear combination link is combined with the total disturbance estimation value of state observer output and acts on motor, motor drives eccentric block to realize the frequency control of vibration hammer.The application overcomes the contradiction between the rapidity and overshoot of traditional control algorithm, greatly improves the robustness of system, and can be widely used in the frequency control of hydraulic vibration piling machine, and has good control effect.

The application provides a gas turbine IGV opening degree control method and device based on generalized predictive control, which comprises the following steps: establishing a transfer function model between the gas turbine IGV opening degree and the exhaust temperature, and identifying initial parameters based on historical operation data; using the initial parameters to establish a prediction model of the gas turbine IGV opening degree, and predicting the object output under different control quantities; introducing a step factor and performing rolling optimization on the control quantity to obtain a target control quantity as an IGV opening degree control instruction; and correcting the parameters of the prediction model online through a recursive least square method to improve the robustness of the control system. The gas turbine IGV opening degree control method provided in the embodiment of the application can adjust the IGV opening degree to control the exhaust temperature by using the generalized predictive control principle, can quickly control the exhaust temperature near the temperature control line, and still has good control effect when the object characteristics change.

The application discloses a kind of based on reinforcement learning's garbage incinerator discharge automatic control method, comprising the following steps: setting garbage incinerator each control parameter and with a control parameter vector x=[v1, v2, d1, d2, v m , h, v l , m] is expressed;Setting toxic emission concentration vector W=[w1, w2,..., w n ] and energy consumption vector e=[e1, e2,..., e j ] is expressed, find a group of control parameter vector x, so that toxic emission concentration vector W and energy consumption vector e minimum: using deep deterministic policy gradient constructs Ev model, Ac model and Q model;With the historical monitoring data in incinerator DCS training Ev model, then with the trained Ev model corresponding data for Ac model and Q model training after action calculation, the trained Ac model can according to the state S of current incinerator Predict the best control parameter vector x, realize the automatic control of garbage incinerator flue gas emission.The application is adjusted by using reinforcement learning algorithm, combined with incinerator historical monitoring data, control parameter in incineration process is automatically adjusted, to realize that flue gas emission reaches environmental protection standard while reducing energy consumption.

A data-driven modeling and predictive control method for ESR process with time-delay characteristics is provided, which is based on the mechanism relationship between the servo motor encoder stroke and the consumable electrode output position to identify and model the ESR process by data-driven method; the transfer function model is converted into a standard linear regression form; a one-dimensional search algorithm is used to estimate the nonlinear time-delay parameters, and an adaptive forgetting factor is constructed by using the estimated parameter change rate; a history control input sequence is introduced into the augmented state vector to convert the original time-delay system into an equivalent time-delay-free augmented state space model; a rolling optimization mechanism is used to dynamically compensate the phase lag caused by multi-source time delay, and combined with feedback correction to effectively suppress the interference of uncertain factors, so as to obtain the optimal control sequence, and make the controller control the ESR system with strong nonlinear and multi-time delay coupling dynamic characteristics in real time with the optimal control sequence. The method can have excellent tracking accuracy and good control stability in the process of processing ESR tracking control.

The present invention provides a control device and program that suppress increases in computational load, reduce the impact of model errors (the difference between the characteristics of the controlled object and the characteristics of the nominal model), and maintain good control performance by suppressing the occurrence of malfunctions in the controlled object even when the model error becomes large. [Solution] The control device 1 includes a nominal model 12 representing the characteristics of the controlled object 20, a controller 11 that performs model predictive control based on the nominal model 12, and a control input u to the controlled object 20 based on the difference between the output of the controlled object 20 and the output of the nominal model 12. c Compensation input u for adjusting d A model error suppression compensator 13 outputs a compensation input u d The system includes an identification unit 14 that, when the value exceeds a predetermined threshold, identifies the controlled object 20, modifies the nominal model 12, and applies the modified nominal model 12 to the internal model of the controller 11.

The application discloses a kind of based on model predictive control algorithm's pneumatic system positioning control method, comprising: the hardware composition and action principle of pneumatic system are analyzed, the mathematical model of pneumatic system is divided into the mass flow equation of gas, the mathematical equation of slide valve, piston force balance equation, based on above-mentioned three equations construction pneumatic system slide valve opening and system output mathematical model;Valve core is analyzed to find the midpoint position of making the stable inaction of both sides of cylinder, design pneumatic system setting process, according to setting process determines the various parameters of pneumatic system slide valve opening and system output mathematical model;Based on the setting process of design, design pneumatic system model predictive controller, this method designs pneumatic system model predictive controller, suppresses each kind of disturbance in system, inside and outside, realizes to pneumatic system and carries out good control.

The invention discloses a thermoelectric cooperative control method and system based on a methanol reforming hydrogen production fuel cell, and belongs to the field of fuel cell control, and the control method comprises the steps: obtaining a real-time operation parameter set of a fuel cell system, and obtaining a real-time operation parameter set of the fuel cell system based on an electric pile instantaneous current and a preset Faraday electrolysis mathematical equation; calculating the theoretical hydrogen consumption rate of the galvanic pile anode, and performing algebraic mapping calculation to generate the transient heat mismatch amount of the reformer; and synchronously outputting a first control instruction and a second control instruction through a hardware control interface according to the transient heat mismatch amount. The method does not need to depend on an online identification algorithm, a neural network or frequent manual recalibration, so that the feed-forward control model can keep good control precision in each stage of the full life cycle of the equipment.