Nonlinear and Variable Structure Excitation Controller for Power System Stability

A new nonlinear variable structure excitation controller is proposed. Its design combines the differential geometry theory and the variable structure controlling theory. The mathematical model in the form of ＂an affme nonlinear system＂ is set up for the control of a large-scale power system. The static and dynamic performances of the nonlinear variable structure controller are simulated. The response of system with the controller proposed is compared to that of the nonlinear optimal controller when the system is subjected to a variety of disturbances. Simulation results show that the nonlinear variable structure excitation controller gives more satisfactorily static and dynamic performance and better robustness.

Operator-Based Robust Nonlinear Control for SISO and MIMO Nonlinear Systems With PI Hysteresis

In this paper, operator based robust nonlinear control for single-input single-output(SISO) and multi-input multi-output(MIMO) nonlinear uncertain systems preceded by generalized Prandtl-Ishlinskii(PI) hysteresis is considered respectively. In detail, by using operator based robust right coprime factorization approach, the control system design structures including feedforward and feedback controllers for both SISO and MIMO nonlinear uncertain systems are given, respectively.In which, the controller design includes the information of PI hysteresis and its inverse, and some sufficient conditions for the controllers in both SISO and MIMO systems should be satisfied are also derived respectively. Based on the proposed conditions, influence from hysteresis is rejected, the systems are robustly stable and output tracking performance can be realized.Finally, the effectiveness of the proposed method is confirmed by numerical simulations.

CONTROLLABILITY CANONICAL FORM FOR NONLINEAR CONTROL SYSTEMS

General nonlinear control systems are studied in this paper with the goal to transform them into the so-called controllability canonteal form via state transformation only. The conditions of transformability are given for both single input and multiple input cases. Besides, by an algebraic approach the procedure for constructing the state transformation is established. This paper is formulated in the framework of calculus rather than differential geometry approach.

An improved nonlinear control strategy for deep space formation flying spacecraft

This paper aims to provide further study on the nonlinear modeling and controller design of formation flying spacecraft in deep space missions. First, in the Sun-Earth system, the nonlinear formation dynamics for the circular restricted three-body problem （CRTBP） and elliptic restricted three-body problem （ERTBP） are presented. Then, with the Floquet mode method, an impulsive controller is developed to keep the Chief on the desired Halo orbit. Finally, a nonlinear adaptive control scheme based on Nonzero set- point LQR and neural network is proposed to achieve high precision formation maneuver and keeping. The simulation results indicate that the proposed nonlinear control strategy is reasonable as it considers not only the orbit keeping of the Chief, but also the formation modeling inaccuracy. Moreover, the nonlinear adaptive control scheme is effective to improve the control accuracy of the formation keeping.

The Application and Design of the Economical Nonlinear Controller

This anticle gives a design method of the economical nonlinear controller. The controller is composed of an expert intelligent coordination controller, a fuzzy prediction controller, a fuzzy feedforward controller, a nonlinear controller and so on. The consistence of a distributed control system based on this controller is also shown briefly.

Quantized Nonlinear Control-A Survey

Quantized control systems design is motivated by the convergence of controls and communications to address modern engineering applications involving the use of information technology. This paper presents an overview of recent developments on the control of linear and nonlinear systems when the control input is subject to quantization or the quantized states or outputs are used as feedback measurements. The co-existence of high-dimeasionality, quantization, nonlinearity and uncertainty poses great challenges to quantized control of nonlinear systems and thus calls for new ideas and techniques. The field of quantized nonlinear control is still at its infancy. Preliminary results in our recent work based on input-to-state stability and cyclic-small-gain theorems are reviewed. The open problems in quantized nonlinear control are also outlined.

Model algorithm control using neural networks for input delayed nonlinear control system

The performance of the model algorithm control method is partially based on the accuracy of the system＇s model. It is difficult to obtain a good model of a nonlinear system, especially when the nonlinearity is high. Neural networks have the ability to ＂learn＂the characteristics of a system through nonlinear mapping to represent nonlinear functions as well as their inverse functions. This paper presents a model algorithm control method using neural networks for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one produces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to illustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.

Review:Recent advances in nonlinear control technologies for shape memory alloy actuators

This paper reviews recent developments in nonlinear control technologies for shape memory alloy (SMA) actuators in robotics and their related applications. SMA possesses large hysteresis, low bandwidth, slow response, and non-linear behavior, which make them difficult to control. The fast response of the SMA actuator mostly depends upon, (1) type of controller, (2) rate of addition and removal of heat, and (3) shape or form of the actuator. Though linear controllers are more desirable than nonlinear ones, the review of literature shows that the results obtained using nonlinear controllers were far better than the former one. Therefore, more emphasis is made on the nonlinear control technologies taking into account the intelligent controllers. Various forms of SMA actuator along with different heating and cooling methods are presented in this review, followed by the nonlinear control methods and the control problems encountered by the researchers.

A Nonlinear Control Strategy for Vienna Rectifier Under Unbalanced Input Voltage

The Vienna rectifier with unbalanced input voltage and load transient is analyzed.A nonlinear control strategy for Vienna rectifier under unbalanced input is proposed.From the view of positive and negative sequence components,the proposed nonlinear control strategy suppresses the twice frequency ripple and guarantees the dynamic response characteristic at the same time.Thanks to the proposed nonlinear control strategy,the DC bus capacitor can be reduced a lot since the voltage ripple and drop can be suppressed.A 10 kW Vienna rectifier is built to verify the proposed control strategy.After applying the proposed nonlinear control strategy,the voltage ripple is only7 V and decreases over 75%over the traditional PI control when the unbalanced degree is 20%.The voltage drop can be reduced about 80%than former control strategy which is helpful to reduce the DC bus capacitor and achieve higher power density.The volume of the capacitor can be reduced by 83.3%with the new control method.

A new adaptive backstepping method for nonlinear control of turbine main steam valve

A new approach for nonlinear adaptive control of turbine main steam valve is developed. In comparison with the existing controller based on ＂classical＂ adaptive backstepping, this method does not follow the classical certaintyequivalence principle in the design of adaptive control law. We introduce this approach, for the first time, to power systems and present a novel parameter estimator and dynamic feedback controller for a single machine infinite bus （SMIB） system with steam valve control. This system contains unknown parameters such as reactance of transmission lines. Besides preserving useful nonlinearities and the real-time estimation of uncertain parameters, the proposed approach possesses better performances with respect to the response of the system and the speed of adaptation. The simulation results demonstrate that the proposed approach is better than the design based on ＂classical＂ adaptive backstepping in terms of properties of stability and parameter estimation, and recovers the performance of the ＂full-information＂ controller. Hence, the proposed method provides an alternative for engineers in applications.

ABSOLUTE STABILITY OF TIME-VARYING NONLINEAR CONTROL SYSTEM

In this paper the authors study two classes of time-varying nonlinear control systems. A few sufficient conditions of absolute stability of these systems were obtained by means of classical analysis and the analogue of the variation of constants formula of nonlinear systems. Moreover, they gave some sufficient conditions of absolute stability in Hurwitz angle for these systems.

A novel excitation controller using support vector machines and approximate models

This paper proposes a novel excitation controller using support vector machines （SVM） and approximate models. The nonlinear control law is derived directly based on an input-output approximation method via Taylor expansion, which not only avoids complex control development and intensive computation, but also avoids online learning or adjustment. Only a general SVM modelling technique is involved in both model identification and controller implementation. The robustness of the stability is rigorously established using the Lyapunov method. Several simulations demonstrate the effectiveness of the proposed excitation controller.

Modified Projective Synchronization of a New Hyperchaotic System via Nonlinear Control

In this paper, a nonlinear control scheme of two identical hyperchaotic Chert systems is developed to realize their modified projective synchronization. We achieve modified projective synchronization between the two identical hyperchaotic systems by directing the scaling factor onto the desired value. With symbolic computation system Maple and Lyapunov stability theory, numerical simulations are given to perform the process of the synchronization.

Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

Dynamic Neural Network Based Nonlinear Control of a Distillation Column

Taking advantage of the knowledge of top and bottom compositions of a distillation column, a dynamic neural network (DNN) is designed to identify the input-output relationship of the column. The weight-training algorithm is derived from a Lyapunov function. Based on this empirical model, a nonlinear H∞ controller is synthesized. The effectiveness of the control strategy is demonstrated using simulation results.

Variable Parameter Nonlinear Control for Maximum Power Point Tracking Considering Mitigation of Drive-train Load

Since mechanical loads exert a significant influence on the life span of wind turbines, the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking U+0028 MPPT U+0029 controller. Moreover, a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue. However, for the existing control strategies based on nonlinear model of wind turbines, the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft. Hence, in this paper, a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously. Then, simulations on FAST U+0028 Fatigue, Aerodynamics, Structures, and Turbulence U+0029 code and experiments on the wind turbine simulator U+0028 WTS U+0029 based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load. © 2017 Chinese Association of Automation.

Robust Nonlinear Control of Continuous Stirred Tank Reactors

This paper deals with the temperature tracking control problem of continuous stirred tank reactors (CSTRs) widely used in chemical engineering. Design of robust tracking controller for a class of CSTRs plant with uncertainties is presented using input output feedback linearization techniques. The control scheme has been applied to a first order irreversible exothermic reaction process carried out in a CSTR, and simulation results show that it is effective.

Improving the Performance of Motor Drive Servo Systems via Composite Nonlinear Control

This paper presents a discrete-time design of robust compositenonlinear controller to achieve fast and accurate set-pointtracking for motor servo systems subject to actuator saturationand disturbances.The basic idea here is to use a combination oflinear and nonlinear control,together with a disturbancerejection mechanism based on extended state observer.The linearcontrol part is designed to yield a fast response,and thenonlinear part serves to reduce the overshoot,while the extendedstate observer estimates simultaneously the state vector and theunknown disturbance for control and compensation.The closed-loopstability is analyzed using the Lyapunov theory.Practicalapplication in a permanent magnet synchronous motor position servosystem is given to demonstrate the effectiveness of the proposedcontrol scheme.

Robust Absolute Stability of General Interval Lur'e Type Nonlinear Control Systems

In this paper, Lyapunov function method is used to study the robust absolute stability of general interval Lur'e type nonlinear control systems. As a result, algebraically sufficient conditions with interval matrix inequality form are obtained for the general interval Lur'e type nonlinear control systems, thus the relationship between the stability of symmetrical interval matrix and the robust absolute stability of general interval Lur'e type nonlinear control systems is established.

EXACT LINEARIZATION BASED MULTIPLE-SUBSPACE ITERATIVE RESOLUTION TO AFFINE NONLINEAR CONTROL SYSTEM

To the optimal control problem of affine nonlinear system, based on differential geometry theory, feedback precise linearization was used. Then starting from the simulative relationship between computational structural mechanics and optimal control, multiple-substructure method was inducted to solve the optimal control problem which was linearized. And finally the solution to the original nonlinear system was found. Compared with the classical linearizational method of Taylor expansion, this one diminishes the abuse of error expansion with the enlargement of used region.