76 results about "Nonlinear control" patented technology

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 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.

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.

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.

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 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 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 application discloses a symbolic controller design method based on chino polyhedron under linear temporal logic specification, belongs to the technical field of nonlinear system control, and solves the linear temporal logic (LTL) task controller synthesis problem of a nonlinear control system. First, an accepted path is generated for a preset LTL task. Second, a chino polyhedron and a constrained chino polyhedron are used to divide a state space, the divided regions are defined as 'units', adjacent units are allowed to intersect, a unit topology graph is constructed based on the unit intersection relationship, and the realizability of the LTL accepted path is verified. Finally, if the accepted path is realizable, the global LTL task is decomposed into a plurality of local subtasks, a local symbolic model is constructed for each unit, a local symbolic controller is iteratively designed through a 'local to global' control strategy, and combination is completed, so that a symbolic controller satisfying the global LTL specification is obtained. The application supports different units to adopt a differentiated local equivalence relationship, reduces the conservativeness of a single equivalence relationship, reduces the calculation complexity of global approximation, and improves the efficiency and practicability of controller synthesis.

The application relates to the technical field of data processing, and discloses an airborne optoelectronic platform turning system, which comprises the following: a nonlinear controller, a selection switch, a current loop controller, a power driving element, a motor, a current feedback element, a speed feedback element, an angular position feedback element, a first error transformation processing unit, a position loop controller, a second error transformation processing unit and a speed loop controller. The nonlinear given value output by the nonlinear controller is used to make the airborne optoelectronic platform rotate to a preset angle. However, the nonlinear given value will cause large overshoot, which is not conducive to the requirement of fast turning stability. Therefore, the second phase current is determined through the speed loop controller and the position loop controller, and the motor is controlled by adopting the closed-loop phase second phase current, so that the airborne optoelectronic platform is rotated to a position of 180 degrees, the overshoot amount of fast turning is reduced, and the 180-degree fast turning of the airborne optoelectronic platform is realized.

The application discloses a center-of-gravity driving aircraft precise attitude regulation method and system, and particularly relates to the field of aircraft attitude control technology, and is used for solving the problem of high operation threshold and easy loss of control of man-machine coupling in a complex environment. First, cabin pressure distribution data is collected and frequency domain decoupling is performed, and a real low-frequency intention driving vector and an associated high-frequency jitter feature are accurately separated. Then, the intention is mapped to a flow field coordinate system that fuses terrain and airflow to perform aerodynamic interference impedance analysis, generate an aerodynamic impedance compensation matrix, and avoid collision risks. The high-frequency jitter and the expected body angular response matching resonance band are extracted, a dynamic anti-oscillation damping coefficient is output, and resonance is suppressed. Finally, multi-dimensional parameters are input into a nonlinear control solver to perform joint optimization and generate a thrust distribution sequence for execution, thereby constructing a regulation closed loop from intention decoupling to physical execution, and ensuring extreme smoothness and flight safety in an extremely simple operation mode.

The invention provides a self-adaptive resource scheduling method and device for a data center, and the method comprises the steps: obtaining the service quality state of a running application program at the beginning of a resource scheduling period; setting the resource scheduling granularity in the resource scheduling period through the service quality state; and carrying out resource scheduling on beneficiary applications and victim applications in the application program in the resource scheduling period according to the resource scheduling granularity. The invention further provides electronic equipment and a computer readable storage medium. According to the resource scheduling method, a nonlinear control strategy which is tightly coupled with the urgency quantitative model is adopted, the intelligent resource scheduling effect is achieved through specifically-designed interval and granularity mapping, and finally the technical purposes of reducing feedback delay, accelerating performance recovery and improving the resource utilization rate are achieved cooperatively.

The invention provides a power system stability optimization method based on hydroelectric generating set interaction energy and multi-channel LADRC. The method comprises the following steps: calculating a sensitivity mathematical expression of a key characteristic value of a hydroelectric grid-connected power system to the hydroelectric generating set interaction energy based on a characteristic value method; and deriving a multi-channel LADRC input tuning matrix, a control link expansion matrix and an output result distribution matrix based on the interaction information of the hydroelectric generating set, and constructing a multi-channel LADRC control strategy. And on the basis of the interaction energy and the sensitivity of the multi-channel LADRC, a unit control parameter coordination control strategy is constructed, and hydroelectric generating unit control parameters influencing stable operation of the power system are optimized. Due to the nonlinearity of the interaction energy and the strong nonlinearity of control parameter optimization, the influence of the interaction energy of the hydroelectric generating set on the stability of the power system is considered, more reasonable set control parameters can be obtained, and the stability of the hydroelectric grid-connected power system can be improved.

The application discloses a digital filtering reconstruction method for lossless audio, and relates to the field of audio filtering reconstruction. Firstly, the transient vibration intensity of the segmented audio frame is extracted in real time to obtain a transient index value, and the transient index value is mapped into a window asymmetry factor by using a nonlinear control curve. According to the factor, a front half cycle attenuation compression and a rear half cycle stretching are applied to a reference window function to generate a dynamic asymmetric window and further obtain dynamic filter coefficients. Finally, the audio is weighted and convoluted by using the dynamic coefficients, and a cross-fading splicing technology is combined to eliminate frame boundary artifacts caused by dynamic adjustment. In this way, dynamic reconstruction can be realized only by relying on time-domain point-by-point modulation of a single set of filters, and the storage of a large number of filter banks or complex offline conversion requirements are completely eliminated.

The invention relates to the control of a permanent magnet speed regulator, and discloses a permanent magnet speed regulator rotating speed control method, which comprises the following steps: acquiring a target rotating speed, and calculating a feedforward regulation distance based on a multi-dimensional nonlinear control model according to the target rotating speed and real-time working condition parameters; meanwhile, according to the deviation between the target rotating speed and the actual rotating speed, a feedback correction distance is calculated through a feedback controller; and fusing the feedforward adjustment distance and the feedback correction distance into a final target adjustment distance, and controlling an execution mechanism to act. Through feedforward-feedback compound control, the problems that in the prior art, control precision is low, dynamic response is slow, and working condition changes cannot be adapted are solved, and high-precision, high-robustness and intelligent control over the permanent magnet speed regulator is achieved.

This invention discloses a deep learning-based integrated stealth and control allocation method, belonging to the field of aircraft stealth and control technology. By using a deep neural network, the three-axis torque commands generated by the flight control law are mapped to control surface deflection commands, addressing the issues of control surface nonlinearity and the impact of control surface deflection on stealth performance. Specifically, it includes: 1) fitting the nonlinear relationship between control surface deflection and torque using wind tunnel and CFD data; 2) constructing a deep autoencoder network, using a combination of virtual control error and control surface deflection as the loss function; 3) offline training of the network, including supervised and unsupervised training, and online deployment to the flight control system. This invention achieves high-precision nonlinear control allocation while optimizing control surface deflection to reduce stealth performance loss, offering advantages such as strong real-time performance and low data requirements.

The invention discloses a finite time convergence adaptive robust control method for a hydraulic mechanical arm under an unknown load. The method comprises the steps that a system dynamics model of the hydraulic mechanical arm is reconstructed through a generalized momentum method, and a finite time convergence adaptive law and a nonlinear controller are designed; the state information of the mechanical arm is input into the finite time convergence self-adaption law in real time, the corrected self-adaption gain updating law is output after processing so as to update the self-adaption gain in the nonlinear controller in real time, meanwhile, the expected track and the expected output thrust of the mechanical arm are input into the nonlinear controller, virtual control flow is output after processing, and therefore the self-adaption gain in the nonlinear controller is updated in real time. And after nonlinear flow mapping is conducted, valve port control voltage is obtained, and then a proportional control valve of the mechanical arm is controlled. On the basis of Lyapunov analysis, finite time convergence of parameter estimation and asymptotic convergence of trajectory tracking errors of the method are strictly proved, and the method shows excellent performance in the aspects of tracking precision and load estimation accuracy of a hydraulic mechanical arm platform.

The invention provides a polyaluminum chloride addition control method based on raw water turbidity and water intake pump frequency, relates to the technical field of water treatment automatic control, and aims to solve the problems of hysteresis, inaccuracy and high energy consumption of traditional manual control and existing automatic control. According to the method, a raw water turbidity value T and a water taking pump operation frequency value F are monitored in real time and input into a preset control rule set for matching, a metering pump frequency control instruction is output, and a polyaluminum chloride adding metering pump is driven to operate. The control rule set defines the accurate mapping relation between the frequency of the water taking pump and the target frequency of the metering pump under different turbidity intervals. Complex nonlinear control is converted into efficient table look-up operation, response is rapid, control is accurate, accurate matching of the adding amount, water quality and water quantity is achieved, the coagulation effect is improved, agent waste and energy consumption increase are avoided, system logic is clear, reliability is high, and the method is suitable for automatic accurate adding of polyaluminum chloride in waterworks.

The invention relates to the technical field of motor control, in particular to a low-speed large-torque control method and system for an industrial robot joint motor, and the method comprises the steps: collecting the voltage of a DC bus, each phase of current of a stator, and the position and rotating speed of a rotor, and carrying out the coordinate transformation of each phase of current of the stator according to the position of the rotor; obtaining d-axis current and q-axis current of the synchronous rotating coordinate system; solving a stator flux linkage estimation value and an electromagnetic torque estimation value according to the d-axis current, the q-axis current and preset motor parameters, and generating a torque error and a flux linkage error; the torque error passes through a torque regulator to obtain a load angle instruction, and the flux linkage error and the rotating speed pass through a flux linkage regulator to obtain a voltage vector amplitude instruction and a voltage vector angle instruction; generating a d-axis voltage instruction and a q-axis voltage instruction; constructing an inverter nonlinear voltage disturbance estimation model, defining d-axis disturbance voltage and q-axis disturbance voltage as disturbance voltage states, and merging the disturbance voltage states into an extended Kalman filtering state space model; executing extended Kalman filtering prediction and correction to obtain a d-axis disturbance voltage estimated value and a q-axis disturbance voltage estimated value; forming a voltage compensation amount and superposing the voltage compensation amount to obtain a compensation voltage instruction; driving pulses are generated through inverse coordinate transformation and space vector modulation, and low-speed large-torque online compensation is achieved. According to the invention, the problems that the output pole voltage of the joint motor of the industrial robot has unexpected distortion and further shows control nonlinearity and the distortion voltage is difficult to directly sense and measure can be solved.

The application discloses a high-precision temperature control method and system of a photoetching machine, belongs to the technical field of temperature control of photoetching machines, collects a temperature array of a lower surface of a mask, a heat flow density distribution of a bearing surface of an exposure table and a thermal pressure difference signal of an air floating layer, carries out feature coding, and constructs a high-dimensional thermal coupling situation feature matrix; then, a dynamic thermal weight correlation graph is generated based on the matrix, exposure key nodes are taken as anchor points, a graph neural network is used to explicitly model a nonlinear thermal path between nodes; further, a spatial gradient change rate of unit area heat flux of a mask area is calculated according to the thermal weight graph, and is mapped to a temperature control array of the exposure table to generate a nonlinear control function surface; and the power output and response delay parameters of a local heating unit are dynamically adjusted according to the control function, so that the method can realize dynamic thermal field equalization with nanometer-level precision, effectively suppress thermal drift, and improve photoetching imaging quality and yield of advanced processes.

The application discloses a synchronous hydraulic system and a control method thereof. The system comprises four oil cylinders, a control module, a pressure acquisition module, a servo pump group and an oil tank. The four oil cylinders are a pair of long oil cylinders and a pair of short oil cylinders. The input end of the servo pump group is connected with the oil tank, and the output end is connected with the oil cylinders. The pressure acquisition module is adapted to acquire the output pressure of the servo pump group and the load pressure of the oil cylinders. The control module is in communication connection with the pressure acquisition module and the servo pump group. The control module is adapted to perform PID closed-loop control on the servo pump group according to the acquisition data of the pressure acquisition module. The application has the beneficial effects that the pressure closed-loop control is realized through the combination of the pressure acquisition module and the servo pump group, so that a closed-loop electronic load-sensitive control mode is provided for a large-amplitude A-shaped frame. The problems of hydraulic-mechanical feedback lag due to long pipelines and the problems of pressure open-loop nonlinear control of remote proportional relief valves are solved.

The invention relates to the technical field of temperature detection and automation, and discloses an intelligent temperature detection and control method and a big data Internet of Things system thereof, and the method comprises the steps: collecting a temperature value sequence of a detected object, and predicting the temperature; acquiring the actual temperature regulation control quantity to obtain an ideal temperature value; acquiring a temperature prediction value and a temperature disturbance quantity based on the actual control quantity and the temperature value sequence; the difference value between the temperature disturbance quantity and the temperature disturbance predicted value is fed back to the neural network for learning, the difference value between the temperature predicted value and the temperature predicted value in a period of time is fed back to the neural network for learning, and the temperature disturbance quantity and the temperature predicted value which are fed back in real time are obtained; the difference value between the expected temperature value and the predicted temperature value passes through the neural network controller to obtain a linear control quantity and a nonlinear control quantity, and the difference value between the accumulated value and the temperature disturbance quantity fed back in real time is processed to obtain a temperature regulation actual control quantity. Compared with the prior art, the dynamic nature, robustness and accuracy of temperature detection and intelligent control are improved.