142 results about "Nonlinear control" patented technology

The invention discloses a wind power operation and maintenance ship embarkation system compensation control method based on active disturbance rejection control and related equipment. The method comprises the following steps: predicting a system external wave disturbance variable of a six-degree-of-freedom embarkation compensation platform according to environmental parameters through a wave disturbance prediction model; the total disturbance quantity in the system is predicted through the extended state observer according to the real-time attitude information and the electric cylinder control signal, and then the total disturbance of the system is obtained; a nonlinear control quantity is calculated through an active disturbance rejection controller according to real-time attitude information, expected attitude information and a preset decoupling matrix, a feed-forward compensation quantity is calculated according to total disturbance of a system, then an output instruction of the controller is calculated, and compensation control is achieved. According to the embodiment of the invention, compensation control can be realized through the wave interference prediction model, the state expansion observer and the active disturbance rejection controller, and high precision and response speed are achieved. The method can be widely applied to the technical field of automation control.

The invention discloses a high-precision temperature control method and system for a photoetching machine, and belongs to the technical field of photoetching machine temperature control. The method comprises the following steps: acquiring a temperature array on the lower surface of a mask, heat flux density distribution of a bearing surface of an exposure table and a hot pressure difference signal of an air floating layer, carrying out feature coding, and constructing a high-dimensional thermal coupling situation feature matrix; a dynamic thermal weight correlation map is generated based on the matrix, exposure key nodes serve as anchor points, and explicit modeling is conducted on nonlinear thermal paths among the nodes through a graph neural network; further calculating the spatial gradient change rate of the heat flux per unit area of the mask region according to the thermal weight map, and mapping the spatial gradient change rate to an exposure table temperature control array to generate a nonlinear control function curved surface; and dynamically adjusting power output and response delay parameters of the local heating unit according to the control function, so that dynamic thermal field equalization with nanoscale precision can be realized, thermal drift is effectively inhibited, and the photoetching imaging quality and the yield of an advanced process are improved.

The invention discloses a single-connecting-rod mechanical arm dynamic memory event triggering fixed time control method and system, and the method comprises the steps: describing a controlled system as a nonlinear system with state time lag and input time lag through modeling; introducing coordinate transformation based on a nonlinear system, and defining a tracking error; designing a virtual control law and an adaptive updating law through the defined tracking error; the stability of the control system is ensured by providing a dynamic memory event triggering mechanism, the system comprises a sensor module, a communication module, a control system and a man-machine interaction module, and the dynamic memory event triggering control mechanism in the method is used as a novel nonlinear control strategy, so that network resources and data transmission can be saved, and the system reliability is improved. The designed fixed time control strategy enables the system to achieve stable control within strictly specified time by accurately presetting the convergence time boundary, the response speed is remarkably improved, and the method is particularly suitable for industrial automation scenes with strict requirements for time precision.

The invention discloses a nonlinear PID control method based on intelligent element driving and a fault-tolerant control system thereof, and belongs to the technical field of intelligent control. According to the method, three behavior mapping mechanisms of punishment, memory and prediction are introduced, a traditional PID controller structure is expanded, a compound error signal is constructed, and a dual-channel control strategy of instinct response and learning response is designed. The controller provided by the invention has adaptive gain adjustment capability, a dynamic adjustment law is constructed in combination with a Lyapunov stability theory, and robust control without model information is realized. Meanwhile, a fault-tolerant mechanism is provided for correcting control signal input by considering the situation of performance degradation of an actual actuator, so that the stability and tracking precision of a control system under non-ideal conditions are improved. The control method is suitable for complex nonlinear object control scenes such as underwater robots, mobile robots and parallel Delta robots.

The invention discloses a cross arm and insulator installation robot motor control method based on a T-S fuzzy model, and the method comprises the following steps: building a permanent magnet synchronous motor nonlinear model according to electromagnetism and motor dynamics; based on a sector nonlinear method, establishing a permanent magnet synchronous motor T-S fuzzy model; designing an observer to obtain a load torque estimated value; designing an L-infinity robust controller to ensure that the angular velocity of the motor can track a reference instruction; and an anti-control gain matrix solving criterion is formulated, and it is ensured that the system meets performance indexes. According to the method, the nonlinear control problem of the permanent magnet synchronous motor system is effectively solved, the influence of continuous interference signals on the system can be effectively suppressed, and the robustness of the system is enhanced.

The application discloses an advertisement optimization method, system, device and medium. The method comprises the following steps: obtaining an error value between a current advertisement effect and an expected effect; calculating a nonlinear PID control signal by using a nonlinear PID algorithm according to the error value; obtaining historical data of the effect of the advertisement, and predicting the error by using a long short-term memory network on the historical data to obtain error prediction data; converting the error prediction data by using a nonlinear function to obtain a feedforward compensation signal; and optimizing the advertisement according to the nonlinear PID control signal and the feedforward compensation signal. Compared with the related art, the application optimizes the PID algorithm by introducing a nonlinear function, and improves the response speed of the advertisement optimization system while improving the accuracy of the advertisement optimization system by combining the long short-term memory network (LSTM) for feedforward compensation prediction.

The invention provides an anti-swing nonlinear control method and system based on a variable frequency driver, and relates to the technical field of ocean engineering equipment.The method comprises the steps that obtained system parameters of an offshore crane system are input into a nonlinear disturbance observer, and an aggregation disturbance observation value output by the nonlinear disturbance observer is obtained; determining mechanical energy, a state error vector and an anti-swing parameter of the offshore crane system based on the system parameters; processing the mechanical energy, the state error vector and the anti-swing parameter by using an energy storage function to obtain virtual energy; and inputting the aggregated disturbance observation value, the mechanical energy, the state error vector and the anti-swing parameter into a nonlinear anti-swing controller to obtain a control parameter which is output by the nonlinear anti-swing controller and corresponds to the virtual energy, so that the offshore crane system executes the control parameter. According to the invention, high-precision positioning of the load can be ensured, and swinging can be effectively inhibited.

The invention discloses an anti-parameter disturbance bidirectional converter non-linear control method and system, and the method comprises the following steps: building a three-order non-linear dynamic model of a three-phase voltage source converter, defining the reciprocal 1 / Rc of an AC side resistor R and a DC side load resistor in the non-linear dynamic model as an unknown parameter, and calculating the parameter disturbance of the three-order non-linear dynamic model; obtaining a system dynamic equation with parameter uncertainty of the three-phase voltage source converter; designing a state transformation function, linearizing a system dynamic equation, and mapping a state variable x; s30, a tracking error variable is defined as a difference value between the converted state variable and a reference track of the state variable, and the difference value is used for quantifying the deviation between the actual state and the expected state of the system; defining and designing a parameter updating law of the three estimated values, and calculating and updating unknown parameters on line according to the tracking error variable; and designing and calculating a control input law based on the tracking error variable and the three estimated values, and proving the asymptotic stability of the closed-loop system through a Lyapunov function.

The application discloses a vehicle control method, a vehicle control device, an electronic device and a readable storage medium. The method comprises the following steps: acquiring a nonlinear control quantity corresponding to a target vehicle at a current moment, wherein the nonlinear control quantity comprises an actual state quantity, an expected state quantity, an actual control input quantity and an expected control input quantity of the target vehicle; inputting the nonlinear control quantity into a target neural network to obtain a control increment, wherein the target neural network is an equivalent representation of a target function in a norm form based on a target error model, the target error model is determined based on a target dynamics model, and the control increment is a first term of a target control sequence for minimizing the target function; and performing motion control on the target vehicle according to the control increment at a next moment.

The application discloses a rocket landing control method based on multi-agent reinforcement learning in the technical field of rocket landing control methods, and the rocket landing control method comprises the following steps: establishing a rocket engine model, collecting and outputting necessary state parameters in the working process of a liquid rocket engine; establishing a vertical landing simulation model of a carrier rocket, collecting and outputting necessary parameters in the vertical landing process of the carrier rocket; defining a state space, an action space and a reward function in the engine starting process; improving on the basis of the MADDPG algorithm to realize the LCO-MADDPG algorithm; and designing, training and evaluating the MARL model. The rocket landing control method realizes nonlinear control of the vertical landing process control of the carrier rocket by means of intelligent control methods without the need of designing complex control logic.

A system and method for providing nonlinear control of a generator, comprising: a linear voltage controller and a nonlinear current controller, wherein the linear voltage controller is implemented on a microcontroller to perform: determining a reference angle for an output voltage from a first generator using a phase-locked loop; converting the reference angle and the generator output voltage from the time domain to an orthogonal reference system to generate two rotating coordinate system reference voltages; calculating the root mean square voltages of the two rotating coordinate system reference voltages and converting the root mean square voltages into an output current IfSet1; providing IfSet1 to the nonlinear current controller; and wherein the nonlinear current controller determines a control action based on the difference between IfSet1 and the output current IfFBK of a second generator.

The present invention provides a network coverage optimization method, system, and storage medium for fire monitoring. The network coverage optimization method includes the following steps: Step A, using a nonlinear control strategy and a Lévy flight mechanism to improve the SOA algorithm to obtain an improved ISOA algorithm; Step B, combining the ISOA algorithm with the PSO algorithm to form an ISOAPSO algorithm. The ISOAPSO algorithm includes inner-layer optimization and outer-layer optimization. When solving the network coverage optimization problem for fire monitoring, the inner-layer ISOA algorithm is first used to optimize sensor nodes. The sensor nodes optimized by the ISOA algorithm are then transferred to the outer-layer PSO algorithm for secondary optimization, thereby achieving the purpose of improving network coverage. The beneficial effect of the present invention is that the network coverage optimization method of the present invention can better solve the network coverage optimization problem for fire monitoring and enhance fire monitoring capabilities.

The application discloses a wheel-legged robot motion control method, system and device facing an unstructured environment, a storage medium and computer equipment, and relates to the technical field of robot control. The control method comprises the following steps: constructing a simulation model of a wheel-legged robot, building a learning training scene of the wheel-legged robot, and training a nonlinear controller model by using a reinforcement learning algorithm; converting the nonlinear controller model into a nonlinear controller which can be deployed and run on an actual physical prototype platform; acquiring current motion state data of the wheel-legged robot and inputting the current motion state data into the nonlinear controller to obtain expected joint positions and expected wheel speeds of the wheel-legged robot; and inputting the expected joint positions and the expected wheel speeds into a low-level controller to output joint torques for controlling the wheel-legged robot to perform a control task. The application not only greatly shortens the development cycle of the wheel-legged robot controller, but also improves the robustness, dynamics and compliance of the wheel-legged robot in an unstructured environment.

The invention provides a micro-droplet multi-dimensional control device and system based on photoelectric cooperative control, and relates to the field of biological microfluidics. The invention provides a micro-droplet multi-dimensional control device based on photoelectric cooperative control. The micro-droplet multi-dimensional control device comprises a photoinduced charged film and an LED addressing module arranged below the photoinduced charged film. The LED addressing module comprises a PCB (Printed Circuit Board), a plurality of LED assemblies are arranged on the PCB, and each LED assembly comprises an LED and an LED coil connected with the LED; the LED addressing module is used for emitting light and driving the photoinduced charged film to generate gradient charges. According to the invention, gradient charges can be generated on the surface of the photoinduced charged film through lighting of the LED, so that the movement of liquid drops is driven, unmarked liquid drop control is realized, the space limitation of a traditional fixed light trap system is broken through, complex trajectory planning of the liquid drops is realized, and nonlinear regulation and control of light intensity gradient and surface wettability are realized.

This invention discloses a sliding mode control method for wastewater treatment processes based on predetermined time performance, belonging to the field of wastewater treatment and nonlinear control technology. This invention is the first to combine second-order integral sliding mode control with a second-order command filter and apply it to the control system of a wastewater treatment plant (WWTP). It considers the requirement that the control coefficient must be greater than 0, and the control effect is superior to existing results. To ensure the timely operation of the wastewater treatment plant, predetermined time performance is used to keep the overall control performance within a specified range and achieve faster convergence. An improved integral sliding surface is constructed, and a novel adaptive controller is designed, achieving stable control of the wastewater treatment plant under three different weather conditions.

The invention relates to the technical field of nonlinear control, and discloses a transverse and lateral attitude controller design method based on an all-wheel-drive system method and interference compensation. The method comprises the following steps: establishing an aircraft transverse and lateral coupling model; according to the transverse and lateral coupling model of the aircraft, calculating a reference control instruction by using an all-drive system method; and obtaining an interference compensation attitude controller by using an active disturbance rejection method, and compensating the reference control instruction through the interference compensation attitude controller to obtain a compensated control instruction. The controller designed by the invention can well track the attitude instruction.

The application provides a passive control device and design method for dead-zone operation precision of a reciprocating mechanism. The device is installed on a sliding block of the mechanism, and comprises a vibrator, an amplitude limiting device and a nonlinear energy sink (NES). The distance between the amplitude limiting device and the vibrator is continuously adjustable. The mass ratio of the vibrator to the sliding block is between 1% and 5%. The application can generate a larger control force under a smaller vibrator mass by using the amplitude limiting device, and solves the problem of poor positioning precision of the mechanism caused by the gap between mechanisms by combining the nonlinear control force generated by the NES. The application does not depend on the state observation of the controlled mechanism, and effectively reduces the complexity of the control structure without increasing the connecting structure between the controlled mechanism and the fixed frame.

The invention discloses a photovoltaic flexible power point tracking control method and system based on a nonlinear controller, and relates to the technical field of photovoltaic system output voltage regulation, and the method comprises the steps: constructing a power conversion structure comprising a photovoltaic array, a Boost converter and an output resistor; analyzing the average model of the Boost circuit, and converting the average model into a standard form; performing dynamic identification and compensation on uncertainty disturbance inside the power conversion structure by using a nonlinear disturbance observer; designing a backstepping control structure by using the average model converted into the standard form, constructing a virtual control variable, and constructing a recursive Lyapunov function; based on a nonlinear interference observer and a backstepping control structure, a nonlinear controller is constructed, and the photovoltaic output voltage is adjusted in real time. According to the method, an observable and controllable photovoltaic power conversion structure is constructed, the anti-interference and stable adjustment capability is improved, and high-precision robust control over the output voltage of the Boost converter is achieved.

Aspects herein describe new methods of determining optimal actions to achieve high-level objectives based on an optimized chosen statistic. At least one high-level objective, along with various observational data about the world, is identified by a computational unit. The computational unit determines, through a particle method, an optimal course of action. The particle method is doubly-exponentially accelerated based on one or more acceleration methods. The doubly-exponentially accelerated particle method comprises alternating backward and forward sweeps of a coupled induction loop to optimize a selection policy and test for convergence to determine said optimal course of action. The doubly-exponentially accelerated particle method may be applied in multiple different time scales.

The invention provides a nonlinear control method suitable for high-maneuverability and large-overload flight, and the method comprises the steps: obtaining an unfiltered compensation control law instruction based on a current-beat state disturbance estimation item of an aircraft, a current-beat input disturbance estimation item of the aircraft and a current-beat constant disturbance estimation item of the aircraft; multiplying the state signal of the current shot of the aircraft by the full-state feedback gain matrix to obtain an unfiltered full-state feedback instruction; multiplying a current shot control instruction of an aircraft pilot by the control gain matrix to obtain an unfiltered main control law control instruction; summing the unfiltered full-state feedback instruction and the unfiltered master control law control signal to obtain an unfiltered master control law instruction; summing the non-filtered compensation control law instruction and the non-filtered main control law instruction to obtain a non-filtered flight control instruction; the unfiltered flight control instruction passes through a low-pass filter to obtain a filtered flight control instruction; and controlling the aircraft to realize high-maneuverability and large-overload flight through a nonlinear steering engine based on the filtered flight control instruction.

This invention discloses an integrable short-circuit current constraint modeling method and apparatus for power systems. The method constructs a Norton equivalent circuit model by acquiring the electromotive force and subtransient reactance parameters of the synchronous generator before a fault. Through a multi-dimensional constraint transformation strategy, the nonlinear control logic of the inverter power supply is transformed into mixed-integer constraints to obtain the inverter power supply injection current constraint. Based on the node current injection information of the synchronous generator and the inverter power supply injection current constraint, a node admittance matrix of the power system is constructed. Based on the node admittance matrix, network equation constraints of the power system are constructed. The Norton equivalent circuit model, mixed-integer constraints, and network equation constraints are integrated to construct and solve a mixed-integer quadratic constraint optimization model to obtain the short-circuit current value required for power system optimization. This invention solves the problems of mismatched nonlinear control characteristics of high-proportion IBGs and the difficulty of directly embedding existing fault current iterative solvers into upper-level optimization.

Aspects herein describe a new approach to determining optimal actions for achieving advanced goals based on optimized selection statistics. At least one advanced target and various observation data about the world are identified by a computing unit. The calculation unit determines an optimal action process by a particle method. The particle methodology is double exponentially accelerated based on one or more acceleration methodologies. A dual exponential accelerated particle method includes alternately coupling reverse and forward scans of inductive cycles to optimize selection strategies and test convergence to determine the optimal process of action. In one embodiment, a user inputs advanced targets into a cell phone that senses observation data. The cellular phone communicates with a server that provides instructions. The server determines an optimal process of action via a dual exponential accelerated particle approach, and then the cellular phone displays instructions to the user.

The invention belongs to the technical field of aircraft tracking control, and provides an aircraft continuous entering and leaving tracking control method based on iterative learning. The method comprises the following steps: establishing an aircraft nonlinear control system model, and converting the aircraft nonlinear control system model into a linear system control problem through virtual input conversion; a target track random optimal control planning method comprehensively considering targets such as flight time, fuel consumption and environmental influence is designed; a flight path tracking control method based on iterative learning is designed by utilizing the characteristic that an aircraft flies along the same target flight path during continuous climbing or descending, and it is ensured that the aircraft flies along the given target flight path and is not affected by disturbance factors such as turbulent flow and transmission errors. According to the aircraft continuous entry and departure tracking control method based on iterative learning, accurate tracking of the target track can be realized, and safe, orderly and efficient operation of the entry and departure aircraft is ensured.

The invention belongs to the technical field of electric power, and relates to a control method and device of a flexible load field station, a medium and electronic equipment. The method comprises the following steps: acquiring a mechanism model of the flexible load station and operating parameters of the flexible load station, and predicting state parameters of the mechanism model by using an optimization algorithm and the operating parameters; a power grid instruction corresponding to the flexible load field station is obtained, an operation objective function and operation boundary conditions of the flexible load field station are constructed, the operation objective function is related to the power grid instruction, and the operation boundary conditions comprise constraint conditions considering the power grid instruction; and constructing a nonlinear control model according to the operation objective function and the operation boundary conditions, and solving the nonlinear control model by using the state parameters to obtain a control instruction of the flexible load station. According to the method, the requirements of the flexible load field station participating in peak regulation and frequency modulation are met, various constraint conditions are considered in the control process of the flexible load field station, and the method participates in related research of a power grid on the basis of ensuring the hydrogen production amount and the operation service life.

The application discloses a pilot multi-way valve control system position control method considering output state constraints, which is based on an output state constraint function constructed, combines a backstepping control thought, and designs a nonlinear position control controller with instruction filtering, state and disturbance observation. For the position control problem of the pilot multi-way valve system, the application can not only rely on the feedback of the system output state signal, construct an extended state observer and a state constraint nonlinear conversion function to obtain unmeasured states of the system, realize output state constraint and disturbance compensation of the system, but also avoid the differential explosion problem in the traditional nonlinear control method through the instruction filter, reduce the influence of the closed-loop control overshoot on the system, and realize high-precision position tracking performance.

The invention discloses a nonlinear control method and device for a permanent magnet synchronous motor-converter system, and belongs to the technical field of permanent magnet synchronous motor control, and the method comprises the steps: designing the control rate of d-axis and q-axis currents of a permanent magnet synchronous motor based on a unity power factor control target; completing the design of a parameter adaptive controller of the control rate of d-axis and q-axis current based on a unity power factor control target; obtaining an estimation function expression of the q-axis inductance of the permanent magnet synchronous motor changing along with the actual d-axis and q-axis current values of the permanent magnet synchronous motor; correcting the control rate of the d-axis current and the q-axis current of the unity power factor control target obtained in the step 2 according to the obtained inductance change rule; and closed-loop control of the permanent magnet synchronous motor is completed. The unity power factor operation effect that the output reactive power of the permanent magnet power generation system is zero is achieved, and the active power density of the permanent magnet power generation system is improved.

The application relates to the field of artificial intelligence, and in particular to a key frame extraction method and device based on contrast learning, equipment and a medium. Applied to a medical scene, in the process of iteratively training a feature embedding network, a constraint term of parameter adjustment is determined according to a contrast loss, an update rule of parameters in the initial feature embedding network is determined according to the constraint term, a stability adjustment mechanism based on a nonlinear control theory is introduced, strict convergence guarantee is provided for contrast learning, key frame classification is performed on video frames according to target time sequence saliency and a preset key frame selection strategy, core dynamic changes of video content can be accurately captured, intelligent classification of key frames is realized in combination with the preset selection strategy, the selection of key frames is more in line with the internal logic and time evolution law of video content through quantitative analysis of the target time sequence saliency, and the accuracy of key frame extraction is effectively improved.

The embodiment of the invention provides a control method of an airship hanging load, electronic equipment, a storage medium and a program product, and relates to the technical field of nonlinear control, the control method of the airship hanging load provided by the embodiment of the invention designs a component of a virtual control force along a cable direction in load trajectory tracking control and position error control, so that the control precision of the airship hanging load is improved; and driving the load to approach the expected trajectory. A cable direction error is introduced in cable swing angle suppression, a component perpendicular to a cable is designed, swing is suppressed, stability is guaranteed, in airship driving control implementation, according to the load control requirement, analog control force needed by the airship is solved, dynamic balance is achieved by adjusting a propelling system of the airship, the dynamic coupling effect of an airship speed ring is considered, and the airship swing angle is suppressed. The self-adaptive control of the attitude is realized, the problems of large deviation of load tracking expected trajectory, insufficient cable swing suppression and unstable airship attitude are solved, and the hoisting control precision of the airship hanging load is improved.

The invention discloses a beneficial disturbance perception-oriented pneumatic artificial muscle manipulator control method and system, and belongs to the technical field of pneumatic system control, and the method comprises the following steps: constructing a nonlinear kinetic model of a pneumatic artificial muscle manipulator system according to a three-element model of pneumatic artificial muscle and a kinetic equation of a manipulator, defining an angle error and an angular velocity error when the manipulator moves; a nonlinear controller based on beneficial disturbance perception is constructed by taking the control targets that the motion angle of the manipulator reaches an expected position and the tracking angle error converges to 0 and considering unknown dynamic state and external disturbance in the system; and according to the angle, obtained through actual measurement, of the manipulator during movement, the constructed nonlinear controller is used for determining the input air pressure of the pneumatic artificial muscle so as to drive the manipulator to move. Accurate and efficient angle tracking control of the manipulator under external disturbance can be achieved, and stable and efficient operation of the system is guaranteed.