Unified Smith Predictor Based H∞ Wide-Area Damping Controller to Improve the Control Resiliency to Communication Failure

Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)Hm controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a Hm controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results,it is verified that,the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.     

A wide area measurement based neurocontrol for generation excitation systems

Power system is a highly interconnected nonlinear system that needs optimal and accurate control for continuous operation. Large power transfer through long transmission line between different electrical areas, stressed system and adverse interaction between local controllers, may give rise to slow frequency inter-area oscillations. The inter-area modes may not be visible from local measurements and hence it is useful to use remote measurement based centralized supplementary control. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control to local controllers such as automatic voltage regulators, power system stabilizers, etc. to damp out inter-area oscillations. This paper presents a design and real time implementation of a nonlinear neural network based optimal wide area controller using adaptive critic design (ACD). The real time implementation of a power system model is carried out on a real time digital simulator (RTDS). The performance of the WACS as a power system stability agent is studied using a two-area power system under different operating conditions and contingencies. The WACS shows improvement in the damping of inter-area mode with the use of supplementary excitation control. In addition, results show that the designed controller can provide robust performance under small communication delay in remote signal transmission.     

Sliding controller for damping inter-area power oscillations

In this paper, a sliding control algorithm design is considered for damping the inter-area power transmission oscillations. The control algorithm is intended for the static Var compensators (SVC) to supply reactive power to the power transmission system, in order to stabilize the system in the event of faults. The controller is capable of achieving full utilization of the SVC and is insensitive to parameter variations and modeling errors. The simulation results show the effectiveness of the sliding controller in damping the inter-area power oscillations, and in enhancing the stability as well as loadability of the transmission systems.     

Hybrid Adaptive Type‐2 Fuzzy Tracking Control of Chaotic Oscillation Damping of Power Systems

In this paper a novel hybrid direct/indirect adaptive fuzzy neural network (FNN) moving sliding mode tracking controller for chaotic oscillation damping of power systems is developed. The proposed approach is established by providing a tradeoff between the indirect and direct FNN controllers. It is equipped with a novel moving sliding surface (MSS) to enhance the robustness of the controller against the present system uncertainties and unknown disturbances. The major contribution of the paper arises from the new simple tuning idea of the sliding surface slope and intercept of the MSS. This study is novel because the approach adopted tunes the sliding surface slope and intercept of MSS using two simple rules simultaneously. One advantage of the proposed approach is that the restriction of knowing the bounds of uncertainties is also removed due to the adaptive mechanism. Moreover, the stability of the control system is also presented. The proposed controller structure is successfully employed to damp the complicated chaotic oscillations of an interconnected power system, when such oscillations can be made by load perturbation of a power system working on its stability edges. Comparative simulation results are presented, which confirm that the proposed hybrid adaptive type‐2 fuzzy tracking controller shows superior tracking performance.     

Delayed-input power system stabilizer using supplementary remote signals

The design of a local H_∞-based power system stabilizer controller, using wide area or global signals as additional measuring information considering time delay, is presented in this paper. The wide area signals are taken from suitable remote network locations where the oscillations are well observable. A long time delay introduced by remote signal transmission and processing in wide area measurement system (WAMS) may harm system stability and degrade system robustness. Three methods for dealing with the effects of time delay are presented in this paper. To provide robust behavior, H_∞ control theory together with an algebraic Riccati equation (ARE) approach has been applied to design the controllers. The effectiveness of the resulting robust H_∞-based PSS controllers is demonstrated through digital simulation studies conducted on a test power system. The simulation results show that the proposed controller contributes significantly to the damping of inter-area oscillations and the enhancement of small-signal stability in the presence of uncertainty in time delay under a wide range of system operating conditions.     

Design of interval type-2 fuzzy sliding-mode controller

In this paper, an interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for linear and nonlinear systems. The proposed IT2FSMC is a combination of the interval type-2 fuzzy logic control (IT2FLC) and the sliding-mode control (SMC) which inherits the benefits of these two methods. The objective of the controller is to allow the system to move to the sliding surface and remain in on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the interval type-2 fuzzy sliding-mode controller system. The design procedure of the IT2FSMC is explored in detail. A typical second order linear interval system with 50% parameter variations, an inverted pendulum with variation of pole characteristics, and a Duffing forced oscillation with uncertainty and disturbance are adopted to illustrate the validity of the proposed method. The simulation results show that the IT2FSMC achieves the best tracking performance in comparison with the type-1 Fuzzy logic controller (T1FLC), the IT2FLC, and the type-1 fuzzy sliding-mode controller (T1FSMC).     

Robust adaptive fuzzy logic power system stabilizer

This paper introduces a robust adaptive fuzzy controller as a power system stabilizer (RFPSS) used to damp inter-area modes of oscillation following disturbances in power systems. In contrast to the IEEE standard multi-band power system stabilizer (MB-PSS), robust adaptive fuzzy-based stabilizers are more efficient because they cope with oscillations at different operating points. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, components that ensure robust and adaptive performance are included in the control law to compensate for modelling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearities. The second system is an adaptive one that compensates for modelling errors. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.     

Design of dual-dimensional controller based on multi-objective gravitational search optimization algorithm for amelioration of impact of oscillation in power generated by large-scale wind farms

This paper studies the impact of high penetration of wind generation technology on dynamic stability of power networks. A mathematical model of a multi-machine power system, including Large-scale Wind Power Generation System (LWPGS) incorporating active power oscillation due to tower shadow and wind shear phenomena is developed. Based on this model, an extended Small-Signal Scrutiny (SSS) procedure to study the impact of oscillatory modes on mechanical vibrations is proposed. The critical operating points that can be dangerous for power system performance are detected. The study is based on modified 16-machine 5-area network with lightly damped electromechanical modes. A dual-dimensional controller for LWPGS is proposed. The first and second dimensions of the designed controller are based on wide-area and local signals, respectively. Selection of the best input of the LWPGS is based on Singular Value Decomposition (SVD) analysis, while the qualified remote control signal is found by geometric approach. Multi-Purpose Gravitational Search Algorithm (MPGSA) based on fuzzy decision making is applied for the coordinated design of LWPGS controller and accelerating power PNS (PNS2B) of the synchronous machines. The simulation results are presented to elucidate the effectiveness of the well-tuned damping controller of the LWPGS.     

TCSC鲁棒自适应控制器的非线性逆推设计

设计了一种应用于互联电网的TCSC鲁棒自适应调制控制器(RAMC).该控制器采用广域测量系统中的全局信号,旨在对各区域的惯量中心进行控制并保持同步运行.采用反推法推导了控制规律,并在2区域4机系统中进行了控制器性能检测.仿真结果显示,该控制器可有效阻尼互联电力系统间的机电振荡,与传统的控制器相比具有良好的性能.     

Fault tolerant control based on neural network interval type-2 fuzzy sliding mode controller for octorotor UAV

In this paper, a robust controller for a six degrees of freedom (6 DOF) octorotor helicopter control is proposed in presence of actuator and sensor faults. Neural networks (NN), interval type-2 fuzzy logic control (IT2FLC) approach and sliding mode control (SMC) technique are used to design a controller, named fault tolerant neural network interval type-2 fuzzy sliding mode controller (FTNNIT2FSMC), for each subsystem of the octorotor helicopter. The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the number of rules for the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the FTNNIT2FSMC can greatly alleviate the chattering effect, tracking well in presence of actuator and sensor faults.     

Synchronization of uncertain chaotic systems based on adaptive type-2 fuzzy sliding mode control

A novel direct adaptive interval type-2 fuzzy neural network (FNN) controller in which linguistic fuzzy control rules can be directly incorporated into the controller is developed to synchronize chaotic systems with training data corrupted by noise or rule uncertainties involving external disturbances, in this paper. By incorporating direct adaptive interval type-2 FNN control scheme and sliding mode approach, two non-identical chaotic systems can be synchronized based on Lyapunov stability criterion. Moreover, the chattering phenomena of the control efforts can be reduced and the external disturbance on the synchronization error can be attenuated. The stability of the proposed overall adaptive control scheme will be guaranteed in the sense that all the states and signals are uniformly bounded. From the simulation example, to synchronize two non-identical Chua’s chaotic circuits, it has been shown that type-2 FNN controllers have the potential to overcome the limitations of tpe-1 FNN controllers when training data is corrupted by high levels of uncertainty.     

永磁同步电机自适应高阶滑模Type-2模糊控制

针对t永磁同步电机数学模型不确定问题,提出一种自适应高阶滑模Type-2模糊控制方法.采用积分滑模面二阶滑模控制律,保持传统滑模控制的鲁棒性并实现不含不确定高阶输入输出有限时间稳定;不需要预先确定干扰与不确定上边界,利用yapunov理论获得自适应调节Type-2模糊规则生成Super--Twisting信号削弱抖振.仿真结果表明永磁同步电机具有良好的跟踪性能,同时验证了该方法的可行和有效性.     

Transient stability improvement of multi-machine power systems using on-line fuzzy control of SMES

Fuzzy control of the super-conducting magnetic energy storage (SMES) is proposed here to improve the transient stability and damping requirements of multi-machine power systems. The effects of the SMES control on the line power transfer are considered in the design of the fuzzy controller. A theoretical realisation of the proposed control scheme is presented and a simulation study on the New-England test system is carried out. A practical implementation, based on local measurements, is explained. The improvement of the system’s critical clearing time, and also the system damping requirements, are clearly demonstrated. Finally, a conclusion is provided.     

Design of self-tuning fuzzy sliding mode control for TORA system

In this paper, a self-tuning fuzzy sliding-mode controller design approach with decoupled method is proposed. The decoupled method provides a simple way to achieve asymptotic stability for a class of fourth-order nonlinear system. Moreover, heuristic sliding factors are implemented as fuzzy inference. Therefore, the proposed method eliminates the trial-and-error process for finding appropriate the sliding factor and fuzzy rules in decoupled self-tuning signed-distance fuzzy sliding mode controller implementation. The simulation of translational oscillations by a rotational actuator (TORA) system is presented to demonstrate the effectiveness and robustness of the method. Using this approach, the response of system will converge faster than that of previous reports.     

Systematic design of a stable type-2 fuzzy logic controller

Stability is one of the more important aspects in the traditional knowledge of automatic control. Type-2 fuzzy logic is an emerging and promising area for achieving intelligent control (in this case, fuzzy control). In this work we use the fuzzy Lyapunov synthesis as proposed by Margaliot and Langholz [M. Margaliot, G. Langholz, New Approaches to Fuzzy Modeling and Control: Design and Analysis, World Scientific, Singapore, 2000] to build a Lyapunov stable type-1 fuzzy logic control system, and then we make an extension from a type-1 to a type-2 fuzzy logic control system, ensuring the stability on the control system and proving the robustness of the corresponding fuzzy controller.     

Type-2 Fuzzy Logic Control of a Flexible-Joint Manipulator

A type-2 fuzzy logic controller (FLC) is proposed in this article for robot manipulators with joint elasticity and structured and unstructured dynamical uncertainties. The proposed controller is based on a sliding mode control strategy. To enhance its real-time performance, simplified interval fuzzy sets are used. The efficiency of the control scheme is further enhanced by using computationally inexpensive input signals independently of the noisy torque and acceleration signals, and by adopting a trade off strategy between the manipulator’s position and the actuators’ internal stability. The controller is validated through a set of numerical experiments and by comparing it against its type-1 counterpart. It is shown through these experiments the higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities. This work was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Microelectronics Corporation (CMC).     

Robust SVC controller design and analysis for uncertain power systems

A Static Var Compensator (SVC) installed in a power transmission network can be effectively used to enhance the damping of electromechanical oscillations [Schweickardt, H. E., Romegialli, G., & Reichert, K. (1978). Closed loop control of static VAR sources (SVS) on EHV transmission lines. IEEE Pes winter power meeting, (paper no A78, pp. 135–136), New York, Jan. 29–Feb. 3]. An adequately designed robust controller, which takes into account variations in the operating conditions, can help to achieve the desired damping control. The proposed approach described in this paper is aimed to achieve damping of electromechanical oscillations by considering a systematic approach, based on interval systems theory and Kharitonov's Theorem. The method presented allows for the design of a fixed-parameter, low-order controller, given a supposed stability degree of the system. The synthesis of a robust SVC controller is divided into two tasks. The first is the determination of the region of stability in the controller parameter plane by plotting the stability boundary locus. The second task is the optimization of the selected controller parameters from the obtained solutions to the first task. Examples of eigenvalue analysis and time simulation demonstrate the effectiveness and robustness of the designed controller.     

Adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties

A new design approach of an adaptive fuzzy terminal sliding mode controller for linear systems with mismatched time-varying uncertainties is presented in this paper. A fuzzy terminal sliding mode controller is designed to retain the advantages of the terminal sliding mode controller and to reduce the chattering occurred with the terminal sliding mode controller. The sufficient condition is provided for the uncertain system to be invariant on the sliding surface. The parameters of the output fuzzy sets in the fuzzy mechanism are adapted on-line to improve the performance of the fuzzy sliding mode control system. The bounds of the uncertainties are not required to be known in advance for the presented adaptive fuzzy sliding mode controller. The stability of the fuzzy control system is also guaranteed. Moreover, the chattering around the sliding surface in the sliding mode control can be reduced by the proposed design approach. Simulation results are included to illustrate the effectiveness of the proposed adaptive fuzzy terminal sliding mode controller.     

An intelligent fuzzy sliding mode control system with application on precision table positioning

In this paper, an intelligent fuzzy sliding mode control system, which cooperates with a new learning approach called modulus genetic algorithm, is proposed. Furthermore, it is applied to a high precision table positioning system for verifying its practicability. Fuzzy sliding mode controller (FSMC) is a special type of fuzzy controller with certain attractive advantages than the conventional fuzzy controller. The learning and stability issues of FSMC are discussed in the paper. Furthermore, to overcome the encoding/decoding procedure that leads to considerable numeric errors in conventional genetic algorithm, this paper proposes a new algorithm called modulus genetic algorithm (MGA). The MGA uses the modulus operation such that the encoding/decoding procedure is not necessary. It has the following advantages: (1) the evolution can be speeded up; (2) the numeric truncation error can be avoided; (3) the precision of solution can be increased. For verifying the practicability of the proposed approach, the MGA‐based FSMC is applied to design a position controller for a high precision table. The experimental results show the proposed approach can achieve submicro positioning precision. © 2001 John Wiley & Sons, Inc.     

Development of a Fuzzy Rule-Based Multi-Objective Hybrid Controller for Static Synchronous Compensator

Static synchronous compensator (Statcom) is a powerful new device for power systems, which can be used for various purposes. The multi-objective demands are quite different in nature, e.g. continuous linear control for voltage maintaining, and discrete bang-bang control for oscillation damping. Unfortunately, they often conflict with each other. In this respect, a supplementary damping control together with an independent voltage control is normally used. However, inevitable small disturbance and uncertainties will cause problems in the coordination of the two functions. To overcome such difficulties, a fuzzy rule-based hybrid controller is proposed in this paper, which incorporates conventional linear voltage control along with the fuzzy rule-based supplementary power damping control to form a unified global controller for Statcom. Because only simple fuzzy rules and a few input signals are involved, it is very easy to implement in a practical power system. The simulation performed on a Single- Machine-Infinite-Bus (SMIB) power system and an actual large power system demonstrates the effectiveness of the proposed approach.