Real time implementation of H∞ loop shaping robust PSS for multimachine power system using dSPACE

This paper presents the simulation and the experimental validation of the designed robust power system stabilizer (RPSS) to stabilize a linearized uncertain power system using Glover-McFarlane’s H_∞ loop shaping design procedure. Guidance for setting the feedback configuration for loop shaping, weighing functions selection and synthesis are also presented. The efficiency of the designed controller is simulated using Matlab/Simulink and tested by implementing on real time environment using dSPACE work stations DS1005 and DS1104. The real time experimental results of RPSS are compared with that of the conventional power system stabilizer (CPSS) for a three phase fault. Also, the real time simulation results of RPSS are compared with the off-line simulation results of RPSS, thus validating the simulation results with the experimental results. Justification of robustness is also presented by considering three different operating points. The proposed method presented in this paper shows the effectiveness of the RPSS in damping the power system oscillations.     

Robust controller design for large interconnected power systems with model uncertainties based on wide-area measurement

Recently the controller using wide-area measurement systems (WAMS) signals has been suggested to accommodate the dynamic performances of large interconnected power systems. However, there is an unavoidable delay before the wide-area signals are received at the controller site. Therefore, a delay-independent robust control problem of large interconnected power systems is studied via H _∞ fuzzy control method based on wide-area measurement. First, a set of equivalent Takagi–Sugeno (T–S) fuzzy model is adopted to represent the nonlinear large interconnected power system. A wide-area state feedback decentralized H _∞ fuzzy control scheme is developed to override the various disturbances, solve the effect of model uncertainties and stabilize the large power system. The H _∞ decentralized control problem is parameterized in terms of a linear matrix inequality (LMI) problem, and the LMI problem can be solved efficiently using convex optimization techniques. Finally, the effectiveness of the proposed controller design methodology is demonstrated through simulation example. This work is supported by the National Science Foundation of China under grant 60374039, 60404007.     

Decentralized guaranteed cost control for uncertain large‐scale systems using additive control gain

This paper investigates an application of additive control gain to the guaranteed cost control (GCC) problem of decentralized robust control for a class of discrete‐time uncertain large‐scale systems. Based on the Linear Matrix Inequality (LMI) design approach, a class of decentralized local fixed state feedback controllers with additive control gain is established. The novel contribution of this paper is that multiobjective control is attained by using the additive control gain. Although the additive control gain is included in the uncertain large‐scale systems, the closed‐loop system is asymptotically stable. In order to demonstrate the efficiency of our proposed controller, using the fuzzy logic control as the additive control gain, the simple numerical example is given. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 169(3): 18–32, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20726     

Decentralized output feedback controller design for nonlinear interconnected systems with unknown control direction and time‐varying delays

The decentralized output feedback control problem is considered for a class of large‐scale systems with unknown time‐varying delays. The uncertain interconnections are bounded by general nonlinear functions with unknown coefficients. The control direction parameters are unknown for each subsystem, which brings a challenging issue for decentralized controller design. To deal with this problem, we propose a new decentralized control scheme with the help of Nussbaum function. The decentralized filter is designed at first. By constructing Lyapunov–Krasovskii functional, we design the dynamic output feedback controller. It is rigorously proved that the closed‐loop system is asymptotically stable. Finally, the simulation is performed, and the results verify the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

LMI‐based adaptive output feedback fault‐tolerant controller design for nonlinear systems

This paper presents 2‐novel linear matrix inequality (LMI)‐based adaptive output feedback fault‐tolerant control strategies for the class of nonlinear Lipschitz systems in the presence of bounded matched or mismatched disturbances and simultaneous occurrence of actuator faults, including failure, loss of effectiveness, and stuck. The constructive algorithms based on LMI with creatively using Lyapunov stability theory and without the need for an explicit information about mode of actuator faults or fault detection and isolation mechanism are developed for online tuning of adaptive and fixed output‐feedback gains to stabilize the closed‐loop control system asymptotically. The proposed controllers guarantee to compensate actuator faults effects and to attenuate disturbance effects. The resulting control methods have simpler structure, as compared with most existing recent methods and more suitable for practical systems. The merits of the proposed fault‐tolerant control scheme have been verified by the simulation on nonlinear Boeing 747 lateral motion dynamic model subjected to actuator faults.     

Robust control of doubly fed induction generator for stand-alone applications

The doubly fed induction generator (DFIG) is generally used in the production of the electric energy and more specifically in wind turbines. Currently, a problem of electrical machine control and especially for wind turbines is the change of internal parameters of the machine, which greatly deteriorates the control. In addition, for stand-alone applications, the load and wind speed change frequently. In this paper, a robust control strategy based on the H_∞ control theory is developed for the independent control of the stator voltage amplitude and frequency of a stand-alone DFIG. The DFIG is fed through the rotor windings by a voltage inverter controlled by Space Vector Modulation (SVM). A capacitive and inductive filter is introduced to reduce harmonics on stator voltages and rotor currents. The robust control strategy rejects all the disturbances that may affect the system and that result from the variations of machine parameters, of the rotor speed and of the load. Experimental tests are carried out to verify the effectiveness of the robust control through a comparison with the classical PI regulator in the framework of the Field Oriented Control (FOC) strategy of the DFIG.     

Decentralized adaptive control of nonlinear large‐scale pure‐feedback interconnected systems with time‐varying delays

In this paper, an adaptive decentralized neural control problem is addressed for a class of pure‐feedback interconnected system with unknown time‐varying delays in outputs interconnections. By taking advantage of implicit function theorem and the mean‐value theorem, the difficulty from the pure‐feedback form is overcome. Under a wild assumption that the nonlinear interconnections are assumed to be bounded by unknown nonlinear functions with outputs, the difficulties from unknown interconnections are dealt with, by introducing continuous packaged functions and hyperbolic tangent functions, and the time‐varying delays in interconnections are compensated by Lyapunov–Krasovskii functional. Radial basis function neural network is used to approximate the unknown nonlinearities. Dynamic surface control is successfully extended to eliminate ‘the explosion of complexity’ problem in backstepping procedure. To reduce the computational burden, minimal learning parameters technique is successfully incorporated into this novel control design. A delay‐independent decentralized control scheme is proposed. With the adaptive neural decentralized control, only one estimated parameter need to be updated online for each subsystem. Therefore, the controller is more simplified than the existing results. Also, semiglobal uniform ultimate boundedness of all of the signals in the closed‐loop system is guaranteed. Finally, simulation studies are given to demonstrate the effectiveness of the proposed design scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems

This paper investigates the problem of adaptive multi‐dimensional Taylor network (MTN) decentralized tracking control for large‐scale stochastic nonlinear systems. Minimizing the influence of randomness and complex nonlinearity, which increases computational complexity, and improving the controller's real‐time performance for the stochastic nonlinear system are of great significance. With combining adaptive backstepping with dynamic surface control, a decentralized adaptive MTN tracking control approach is developed. In the controller design, MTNs are used to approximate nonlinearities, the backstepping technique is employed to construct the decentralized adaptive MTN controller, and the dynamic surface control technique is adopted to avoid the “explosion of computational complexity” in the backstepping design. It is proven that all the signals in the closed‐loop system remain bounded in probability, and the tracking errors converge to a small residual set around the origin in the sense of a mean quartic value. As the MTN contains only addition and multiplication, the proposed control method is more simplified and of good real‐time performance, compared with the existing control methods for large‐scale stochastic nonlinear systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this paper has good real‐time performance and control quality, and the dynamic performance of the closed‐loop system is satisfactory.     

Robust wide‐area damping controller design for inter‐area oscillations with signals' delay

A new wide‐area damping control strategy is investigated for flexible AC transmission systems (FACTS) device using wide‐area measurement system (WAMS) signals. The purpose is to design a dynamic output wide‐area damping controller (WADC) for improving the stability of interconnected power systems. The time‐varying delay of wide‐area signal is incorporated into the design process, which can effectively reduce the delay effect on the damping performance. First, a discrete‐time plant model with time‐varying delay is established for power systems; then by using the proposed improved free‐weighting matrices (IFWMs) approach and a convex optimization algorithm, a new and less conservative delay‐dependent stability criterion, expressed in the terms of linear matrix inequalities (LMIs), is obtained without ignoring any useful terms on the difference of a Lyapunov function. Detailed case studies on a 4‐machine two‐area benchmark test system and 16‐machine five‐area NETS‐NYPS interconnected system show that the designed WADC can not only maintain effective damping performance under the condition of time‐varying delay but also get the maximum wide‐area time delay. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Robust adaptive sliding mode control for uncertain delta operator systems

In this paper, a robust adaptive sliding mode controller is presented for delta operator systems with mismatched uncertainties and exogenous disturbances. The parameters of the delta operator system are taken for norm‐bounded uncertainties. The exogenous disturbance is also assumed to be bounded. After the statement of a sufficient condition for the existence of linear sliding surface based on linear matrix inequality technique, a robust reaching motion control method for delta operator systems is presented. Afterwards, an adaptive sliding mode controller for delta operator systems is designed. A bridge between the robust adaptive sliding mode control and the delta operator system framework is made. Numerical example is given to illustrate the effectiveness of the developed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

Adaptive robust H∞ state feedback control for linear uncertain systems with time‐varying delay

This paper considers the problem of adaptive robust H_∞ state feedback control for linear uncertain systems with time‐varying delay. The uncertainties are assumed to be time varying, unknown, but bounded. A new adaptive robust H_∞ controller is presented, whose gains are updating automatically according to the online estimates of uncertain parameters. By combining an indirect adaptive control method and a linear matrix inequality method, sufficient conditions with less conservativeness than those of the corresponding controller with fixed gains are given to guarantee robust asymptotic stability and H_∞ performance of the closed‐loop systems. A numerical example and its simulation results are given to demonstrate the effectiveness and the benefits of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.     

Free‐weighting matrices‐based robust wide‐area FACTS control design with considering signal time delay for stability enhancement of power systems

This paper presents a free‐weighting matrix (FWM) method based on linear control design approach for the wide‐area robust damping (WARD) controller associated with flexible AC transmission system (FACTS) device to improve the dynamical performance of the large‐scale power systems. First, the linearized reduced‐order plant model is established, which efficiently considers the time delay of the remote feedback signals transmitted by wide‐area measurement systems. Then, based on the robust control theory, the design of the FACTS‐WARD controller is formulated as the standard control problem on delay‐dependent state‐feedback robust control, which is described by a set of linear matrix inequality constraints. Furthermore, in order to obtain the optimal control parameters that can endure the maximum time delay, a FWM approach is proposed to solve the time‐dependent problem of the time‐delay system. Meanwhile, an iterative algorithm based on cone complementary linearization is presented to search out the optimal control parameters. Finally, the nonlinear simulations on the 2‐area 4‐machine and the 5‐area 16‐machine test systems are performed, to evaluate the control performance of the proposed robust wide‐area time‐delay control approach. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Adaptive observer for nonlinear fractional‐order systems

In this paper, an adaptive observer is proposed for the joint estimation of states and parameters of a fractional nonlinear system with external perturbations. The convergence of the proposed observer is derived in terms of linear matrix inequalities (LMIs) by using an indirect Lyapunov method.The proposed adaptive observer is also robust against Lipschitz additive nonlinear uncertainty. The performance of the observer is illustrated through some examples including the chaotic Lorenz and Lü's systems. Copyright © 2016 John Wiley & Sons, Ltd.     

Stochastic H∞ control problem with state‐dependent noise for weakly coupled large‐scale systems

In this paper, stochastic H_∞ state feedback control with state‐dependent noise for weakly coupled large‐scale systems is discussed. After establishing the asymptotic structure of the stochastic algebraic Riccati equation (SARE), a new iterative algorithm that combines the Newton's method with the fixed‐point algorithm is derived for the first time. As a result, both the quadratic convergence and the reduced‐order computation in the same dimension of the subsystems are attained. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.