Research on Active and Reactive Power Decoupling Control Based on VSC-HVDC

Voltage Source Converter-based High Voltage Direct Current(VSC-HVDC)transmission technology represents a groundbreaking approach in high voltage Direct Current(DC)transmission,offering numerous technical advantages and broad application prospects.However,in the d-q synchronous rotating coordinate system,the VSC-HVDC exhibits the coupling effect of active power and reactive power,so it needs to be decoupled.This paper introduces the basic principle and mathematical model of the VSC-HVDC transmission system.Through the combination of coordinate transformation and variable substitution,a feedforward decoupling control method is derived.Then the VSC-HVDC simulation model is designed,and the simulation analysis is carried out in the MATLAB environment.The simulation results demonstrate that the method effectively achieves decoupling control of active and reactive power,exhibiting superior dynamic performance and robustness.These findings validate the correctness and effectiveness of the control strategy.

Nonlinear Decoupling Control of the Bearingless Induction Motors Based on the Airgap Motor Flux Orientation

The bearingless induction motor, which combines the inductionmotor and magnetic bearing is a strongly coupled complicatednonlinear system; the decoupling control of the electromag- net toqueand readial levitation force is the base of the stable operation ofthe benaringless motor. In this paper, the air-gap motor fluxoriented vector control is proposed to realize the decoupling controlof this nonlinear system even in the transient case based on thelevitation principle. Simulations show the stable suspension and goodperformance of the proposed algorithm.

Decoupling Control Method Based on Neural Network for Missiles

In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neural network to approximate the decoupling control laws which are designed for different aerodynamic characteristic points, so a new decoupling control law based on BP neural network is produced after the network training. The simulation results on an example illustrate the approach obtained feasible and effective.

Neural adaptive PSD decoupling controller and its application in three-phase electrode adjusting system of submerged arc furnace

Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and differential) dispersive decoupling controller was developed by combining neural adaptive PSD algorithm with dispersive decoupling network. In this work, the production technology process and control difficulties of submerged arc furnace were simply introduced, the necessity of establishing a neural adaptive PSD dispersive decoupling controller was discussed, the design method and the implementation steps of the controller are expounded in detail, and the block diagram of the controlled system is presented. By comparison with experimental results of the conventional PID controller and the adaptive PSD controller, the decoupling ability, adaptive ability, self-learning ability and robustness of the neural adaptive PSD dispersive decoupling controller have been testified effectively. The controller is applicable to the three-phase electrode adjusting system of submerged arc furnace, and it will play an important role for achieving the power balance of three-phrase electrodes, saving energy and reducing consumption in the process of smelting.

Dynamic Analysis and Decoupling Control of Octo-pneumatic Actuator Vibration Isolation Platform

Control of a six-DOF vibration isolation platform is generally difficult which is due to the strong coupling among its input and output channels. The dynamic behavior and decoupling approach of a six-DOF vibration isolation platform with eight pneumatic actuators are investigated. Owing to the symmetric configuration design of the platform, the coupling among different channels is greatly weakened. When the payload＇s principal axes of inertia parallel to the platform＇s axes of symmetry and the payload＇s center of mass is at the extension line of the platform＇s central axis, the motion can be decomposed into two independent single-input single-output channels and two independent two-input two-output subsystems. The second-order subsystems are decoupled further with the simultaneous matrix diagonalization. Thus a decoupling control strategy is developed. Effectiveness of the decoupling approach is verified through experiments of the platform, and the experimental results show that vibrations of the platform are attenuated obviously owing to the active control.

Nonlinear decoupling controller design based on least squares support vector regression

Support Vector Machines (SVMs) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on a method of least squares SVM (LS-SVM) for multivariate function estimation, a generalized inverse system is developed for the linearization and decoupling control of a general nonlinear continuous system. The approach of inverse modelling via LS-SVM and parameters optimization using the Bayesian evidence framework is discussed in detail. In this paper, complex high-order nonlinear system is decoupled into a number of pseudo-linear Single Input Single Output (SISO) subsystems with linear dynamic components. The poles of pseudo-linear subsystems can be configured to desired positions. The proposed method provides an effective alternative to the controller design of plants whose accurate mathematical model is un- known or state variables are difficult or impossible to measure. Simulation results showed the efficacy of the method.

Genetic Optimization Algorithm of PID Decoupling Control for VAV Air-Conditioning System

Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.

ESO-based decoupling control with multi-objective optimization for boiler-turbine unit

A model-assistant extended state observer(MESO)-based decoupling control strategy is proposed for boiler-turbine units in the presence of unknown external disturbance and model-plant mismatch. For ease of implementation, the decoupling compensator is reduced to the proportion integration(PI) decoupler with the frequency domain analysis, where the decoupling error in collusion of uncertainties and disturbances can be estimated by the proposed MESO and then compensated. To decrease the sensitivity of the dynamic error for the decoupling control and fulfill various requirements of constraints, such as safety operation, energy conservation, emission reduction, etc., the plant is transmitted through a scheduled steady state region which is achieved from the optimized reference governor in advance. Simulation results show that the proposed control strategy can well suppress various disturbances including a decoupling error, and multi-objective optimization can meet multiple requirements with the premise of safety production.

Optimal Decoupling Control Method and Its Application to a Ball Mill Coal-pulverizing System

Abstract-The conventional optimal tracking control method cannot realize decoupling control of linear systems with a strong coupling property. To solve this problem, in this paper, an optimal decoupling control method is proposed, which can simultaneousiy provide optimal performance. The optimal decoupling controller is composed of an inner-loop decoupling controller and an outer-loop optimal tracking controller. First, by introducing one virtual control variable, the original differential equation on state is converted to a generalized system on output. Then, by introducing the other virtual control variable, and viewing the coupling terms as the measurable disturbances, the generalized system is open-loop decoupled. Finally, for the decoupled system, the optimal tracking control method is used. It is proved that the decoupling control is optimal for a certain performance index. Simulations on a ball mill coal-pulverizing system are conducted. The results show the effectiveness and superiority of the proposed method as compared with the conventional optimal quadratic tracking （LQT） control method.

DECOUPLING CONTROL OF TWO MOTORS SYSTEM BASED ON NEURAL NETWORK INVERSE SYSTEM

In accordance with the characteristics of two motors system, the unitedmathematic model of two-motors inverter system with v/f variable frequency speed-regulating isgiven. Two-motor inverter system can be decoupled by the neural network invert system, and changedinto a sub-system of speed and a sub-system of tension. Multiple controllers are designed, and goodresults are obtained. Tie system has good static and dynamic performances and high anti-disturbanceof load.

Decoupling Control of Fluid Catalytic Cracking Unit

This study presents a decoupling control scheme of fluid catalytic cracking unit to account for the high interaction between two temperature control loops. The feed flow rate load disturbance is introduced to test the proposed decoupling control scheme. Through simulation study shown that the decoupling is effective, stable and it presents advantage over controller without decoupler. Also, this scheme is able to offer good dynamic performance for most disturbances.

Decoupling Control of Lateral Dynamics for 4WS Vehicle

An four wheel steering (4WS) feedback control system that simultaneously achieves both body sideslip angle and yaw rate responses always desirable regardless of changes in vehicle dynamics. Quantitative feedback theory (QFT) is offered as the main tool for designing the control law. Inverted decoupling is also employed to make multivariable quantitative feedback design easier. Various nonlinear analyses are carried out and show that the proposed control system is a robust decoupling controller which not only makes body sideslip angle and yaw rate of the vehicle track the desired reference input signals respectively, but also satisfies the requirement of robustness for the control system. The results also indicate that the control system can make it available to realize ideal lateral steering dynamics tracking for vehicles.

Fault-tolerant stator flux oriented decoupling control for dual three-phase permanent magnet motor without diagnosis and reconfiguration

In this paper,the fault-tolerant capability of the existing stator-flux-oriented decoupling control(SFOC)for the DTP-PM motor is investigated,and a simple fault-tolerant SFOC is further designed to enhance fault tolerance.Firstly,the mathematical model of the DTP-PM motor in the stator-flux-oriented rotating coordinate system is analyzed.An SFOC is proposed to guarantee healthy operation performance,considering torque,flux linkage,and harmonic currents.Secondly,the coupling relationship under open-phase conditions is assessed.The assessed result shows that the coupling relationship between the harmonic and fundamental components results in conflicts and poor post-fault operation.Thirdly,the proposed SFOC includes an automatic deactivation module to detect conflicts with a variable threshold.The conflicted harmonic current controllers can be excluded automatically.Hence,fault-tolerant control can be remedied without diagnosing the specific fault scenario,and excellent faulttolerant capability can be achieved.Finally,experiments on a DTP-PM motor are carried out to verify the feasibility and effectiveness of the proposed strategy.

Multivariable Decoupling Control of Civil Turbofan Engines Based on Fully Actuated System Approach

Gas turbine engines must be operated by means of control,and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more attention.The paper considers the multivariable decoupling problems of aero-engines by using a compound controller,which originates from the fact that it is impossible to eliminate all the nonlinear dynamics of system to obtain desired constant linear closed-loop system by using full actuated control because of modeling errors and some physical constraints.Two controllers are involved in the compound controller.One is a fully actuated controller and the other is classical feedback controller.In order to use fully actuated control and maintain the accuracy of engine model,a full state scheduling linear parameter-varying(LPV)modeling method is proposed based on fuzzy neural network weights.For a general input matrix of the system,its generalized inverse is applied to design fully actuated controller to result in a pseudolinear system.Combined with a feedback controller and control limiter,the control synthesis is achieved.The simulation shows that the proposed method is possessed of a better decoupling and tracking effect compared with traditional control approach.

Nonlinear Decoupling PID Control Using Neural Networks and Multiple Models

For a class of complex industrial processes with strong nonlinearity, serious coupling and uncertainty, a nonlinear decoupling proportional-integral-differential （PID） controller is proposed, which consists of a traditional PID controller, a decoupling compensator and a feedforward compensator for the unmodeled dynamics. The parameters of such controller is selected based on the generalized minimum variance control law. The unmodeled dynamics is estimated and compensated by neural networks, a switching mechanism is introduced to improve tracking performance, then a nonlinear decoupling PID control algorithm is proposed. All signals in such switching system are globally bounded and the tracking error is convergent. Simulations show effectiveness of the algorithm.

A Decoupling Control Model on Perturbation Method for Twin-Roll Casting Magnesium Alloy Sheet

To better understand the twin-roll casting process,based on the analysis of the solidification phenomenon,the geometry shape of the molten metal pool,the continuity of metal and the balance of energy and momentum,five critical partial equations were established separately including the equations of pool level,solidification process,roll separating force,roll gap and casting speed.Meanwhile,to obtain a uniform sheet thickness and keep a constant roll separating force,a decoupling control model was built on the perturbation method to eliminate the interference of process parameters.The simulation results show that the control model is valuable to quickly and accurately determine the control parameters.Moreover,Mg alloy sheets with high quality were cast by applying this model.

PID Neural Net work Decoupling Control Based on Hybrid Particle Swarm Optimization and Differential Evolution

For complex systems with high nonlinearity and strong coupling,the decoupling control technology based on proportion integration differentiation(PID)neural network(PIDNN)is used to eliminate the coupling between loops.The connection weights of the PIDNN are easy to fall into local optimum due to the use of the gradient descent learning method.In order to solve this problem,a hybrid particle swarm optimization(PSO)and differential evolution(DE)algorithm(PSO-DE)is proposed for optimizing the connection weights of the PIDNN.The DE algorithm is employed as an acceleration operation to help the swarm to get out of local optima traps in case that the optimal result has not been improved after several iterations.Two multivariable controlled plants with strong coupling between input and output pairs are employed to demonstrate the effectiveness of the proposed method.Simulation results show t hat the proposed met hod has better decoupling capabilities and control quality than the previous approaches.

An LMI-based decoupling control for electromagnetic formation flight

Electromagnetic formation flight （EMFF） leverages electromagnetic force to control the relative position of satellites. EMFF offers a promising alternative to traditional propellant-based spacecraft flight formation. This novel strategy is very attractive since it does not consume fuel. Due to the highly coupled nonlinearity of electromagnetic force, it is difficult to individually design a controller for one satellite without considering others, which poses challenges to communications. This paper is devoted to decoupling control of EMFF, including regulations, constraints and con- troller design. A learning-based adaptive sliding mode decoupling controller is analyzed to illustrate the problem of existing results, and input rate saturation is introduced to guarantee the validity of frequency division technique. Through transformation, the imposed input rate saturation is con- verted to state and input constraints. A linear matrix inequalities （LMI）-based robust optimal con- trol method can then be used and improved to solve the transformed problem. Simulation results are presented to demonstrate the effectiveness of the proposed decoupling control.

An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network

High precision control of substrate tension is the premise and guarantee for producing high-quality products in roll-to-roll precision coating machine.However,the complex relationships in tension system make the problems of decoupling control difficult to be solved,which has limited the improvement of tension control accuracy for the coating machine.Therefore,an ADRC parameters self-tuning decoupling strategy based on RBF neural network is proposed to improve the control accuracy of tension system in this paper.Firstly,a global coupling nonlinear model of the tension system is established according to the composition of the coating machine,and the global coupling model is linearized based on the first-order Taylor formula.Secondly,according to the linear model of the tension system,a parameters self-tuning decoupling algorithm of the tension system is proposed by integrating feedforward control,ADRC and RBF.Finally,the simulation results show that the proposed tension control strategy has good decoupling control performance and effectively improves the tension control accuracy for the coating machine.

Stabilization Variable Structure Control for Singular Decoupling Motor System

This paper describes the important application of variable structure control (VSC) theory on induction motor (IM) decoupling control system. A design scheme using singular system variable structure control method for a decoupling IM system is presented. The scheme is shown to be robust to parametric variations and external disturbances. Simulation results show the stability and effectiveness of the proposed scheme