Hassan Yousef

Flatness-based adaptive fuzzy output tracking excitation control for power system generators

In this paper, a novel approach for the design of an indirect adaptive fuzzy output tracking excitation control of power system generators is proposed. The method is developed based on the concept of differentially flat systems through which the nonlinear system can be written in canonical form. The flatness-based adaptive fuzzy control methodology is used to design the excitation control signal of a single machine power system in order to track a reference trajectory for the generator angle. The considered power system can be written in the canonical form and the resulting excitation control signal is shown to be nonlinear. In case of unknown power system parameters due to abnormalities, the nonlinear functions appearing in the control signal are approximated using adaptive fuzzy systems. Simulation results show that the proposed controller can enhance the transient stability of the power system under a three-phase to ground fault occurring near the generator terminals.

L1 Adaptive fuzzy controller for a class of nonlinear systems with unknown backlash-like hysteresis

ABSTRACT This paper proposes an adaptive fuzzy logic control scheme for a class of strict-feedback nonlinear systems with unknown backlash-like hysteresis. The proposed controller exploits the properties of the newly developed adaptive control in conjunction with the approximation capability of fuzzy systems. The developed controller is fast, the adaptation can be as fast as the CPU permits, and robust by virtue of the adaptive control structure and the direct estimation of the system nonlinear functions via fuzzy logic systems. As a result, the proposed adaptive fuzzy controller has a simpler form and requires fewer adaptation parameters. The inverted pendulum and Duffing forced oscillation systems are used in simulation studies to verify the effectiveness of the proposed adaptive fuzzy control scheme.

Saturated robust control with regional pole placement and application to car active suspension

In this paper a new saturated control design for uncertain systems is proposed. The developed saturated control scheme is based on linear matrix inequality (LMI) optimization to achieve prescribed dynamic performance measures e.g., settling time and damping ratio. In this design, the closed-loop poles are forced to lie within a desired region. The proposed design provides robustness against system uncertainties. The existence of the saturated robust control with regional pole placement is shown using LMI and Lyapunov function analysis. Simulation results of two illustrative examples are given to validate the effectiveness of the proposed controllers. Application to car active suspension to achieve comfortable dynamic performance by pole placement and avoiding actuator saturation is also considered.

Robust flatness-based tracking control for brushless direct current motor drives:

The trajectory tracking problem for nonlinear brushless direct current drive is solved by combined robust and flatness state feedback control. The drives nonlinear model is shown to have the flatness property. The proposed controller consists of two parts, linear and nonlinear. Linear matrix inequalities (LMI) optimization is used to design the linear part which achieves robust stability against system uncertainties, desired swiftness, and guaranteed cost performance. System uncertainty due to changes in the drives parameters is represented with a norm-bounded structure. The nonlinear control part solves the motion planning problem through flatness which avoids integrating the differential equations of the dynamics. The main advantages of this technique are that the LMI algorithm includes an optimal part to preclude high control efforts, and the control burden is heavily placed on the linear part to achieve flatness properties. In some systems, in which flatness cannot be achieved, adding robust linear control can overcome or alleviate this problem.

Nonlinear power system excitation control using adaptive wavelet networks

A wavelet network-based nonlinear excitation control is designed to enhance the transient stability of a power system. The power system model used to improve the transient stability via excitation control can be written in the canonical form. The resulting excitation control signal that achieves a prescribed tracking performance is shown to include unknown nonlinear terms. A wavelet network is constructed to generate an approximation of these nonlinear terms and hence facilitate the design of the nonlinear excitation controller. Based on the wavelet network approximation, suitable adaptive control and appropriate parameter update algorithm are developed to force the nonlinear uncertain power system to track a prescribed trajectory with desired dynamic performance. It is shown that the proposed controller achieves ultimately bounded tracking error and boundedness of the closed loop signals. A single machine infinite bus system with uncertain fault location is presented to illustrate the proposed design procedure and exhibit its performance. The performance of the proposed excitation controller is compared with the classical IEEE-type ST1A static exciter equipped with a power system stabilizer. The paper addresses the problem of designing a wavelet network-based nonlinear excitation control for power systems. A wavelet network is utilized in designing such controller.The capability of a wavelet network to approximate nonlinear functions is exploited in this work. The objective of the proposed adaptive wavelet controller is to achieve tracking between the power system output (generator angle in this case) and a prescribed reference trajectory.This controller achieves ultimately bounded tracking error and boundedness of the closed loop signalsThe proposed controller is compared with the classical IEEE static exciter.The comparison proves the effectiveness of the proposed controller in damping out power system oscillations that occur due to sever abnormality (e.g. three-phase to ground fault).

Stability and Convergence Analysis of Direct Adaptive Inverse Control

In adaptive inverse control (AIC), adaptive inverse of the plant is used as a feed-forward controller. Majority of AIC schemes estimate controller parameters using the indirect method. Direct adaptive inverse control (DAIC) alleviates the adhocism in adaptive loop. In this paper, we discuss the stability and convergence of DAIC algorithm. The computer simulation results are presented to demonstrate the performance of the DAIC. Laboratory scale experimental results are included in the paper to study the efficiency of DAIC for physical plants.

Indirect adaptive fuzzy logic frequency control of multi-area power system

This paper presents a new load frequency control (LFC) scheme for multi area power system. The power systems under study is uncertain due to unknown parameters. The indirect adaptive fuzzy control technique is used to design tracking controller by generating approximations of unknown functions. Suitable adaptive control law and updating algorithms for the controller parameters are synthesized using Lyapunov function. The designed tracking controller for each area uses the frequency and tie-line power deviations of the area. The proposed controller guarantees the boundedness of the closed-loop signals. Simulation results of a three-area power system are presented to validate the effectiveness of the proposed.

Performance of a stand-alone renewable energy system based on hydrogen energy storage

In this paper, an ac-linked hybrid electrical energy system comprising of photo voltaic (PV) and fuel cell (FC) with electrolyzer for standalone applications is proposed. PV is the primary power source of the system, and an FC-electrolyzer combination is used as a backup and as long-term storage system. A Fuzzy Logic controller is developed for the maximum power point tracking for the PV system. A simple power management strategy is designed for the proposed system to manage power flows among the different energy sources. A simulation model for the hybrid energy has been developed using MATLAB/Simulink.

Decentralized Robust Saturated Control of Power Systems Using Reachable Sets

Electric power grids are highly nonlinear complex systems. This manuscript presents a novel approach to the stabilization of large power systems. The proposed control satisfied three constraints: decentralization, input saturation imposed in practice, and robustness against load changes. The large power system is decomposed into subsystems, for each a decentralized controller is designed. The effect of the rest of the system on each subsystem is considered as an external disturbance and represented in norm-bounded form. A new approach to solve this problem is proposed in the present paper. The approach is based on the method of invariant ellipsoids, and the tool of linear matrix inequalities (LMI) is utilized to solve the resulting optimization problem. Control of multimachine power system is studied using the proposed control. Comparison with other techniques is also given.

Load frequency control of a multi-area power system with PV penetration: PI and PID approach in presence of time delay

In this paper, a new methodology for load frequency control (LFC) in multi-area power systems is developed based on the closed loop set-point overshoot method. LFCs for each area are designed based on availability of frequency deviation of each area and tie-line power deviation between areas. The PID controllers are tuned based on each area parameters to achieve acceptable response. The PV penetration was introduced and found tolerable with the tuned PI and PID controllers. The proposed controller guarantees stability of the overall closed-loop system in the presence of time delay. Simulation results for a real four-area power system prove the effectiveness of the proposed LFC and show its effectiveness in the presence of time delay.