SUMMARYThis paper presents two novel nonlinear fractional-order sliding mode controllers for power angle response improvement of multi-machine power systems. First, a nonlinear block control is used to handle nonlinearities of the interconnected power system. In the second step, a decentralized fractional-order sliding mode controller with a nonlinear sliding manifold is designed. Practical stability is achieved under the assumption that the upper bound of the fractional derivative of perturbations and interactions are known. However, when an unknown transient perturbation occurs in the system, it makes the evaluation of perturbation and interconnection upper bound troublesome. In the next step, an adaptive-fuzzy approximator is applied to fix the mentioned problem. The fuzzy approximator uses adjacent generators relative speed as own inputs, which is known as semi-decentralized control strategy. For both cases, the stability of the closed-loop system is analyzed by the fractional-order stability theorems. Simulation results for a three-machine power system with two types of faults are illustrated to show the performance of the proposed robust controllers versus the conventional sliding mode. Additionally, the fractional parameter effects on the system transient response and the excitation voltage amplitude and chattering are demonstrated in the absence of the fuzzy approximator. Finally, the suggested controller is combined with a simple voltage regulator in order to keep the system synchronism and restrain the terminal voltage variations at the same time.
This paper focuses on speed control of Five-Phase interior permanent magnet synchronous motor (IPMSM) through proportional-integral (PI) controller, sliding mode control (SMC) and novel fractional integral terminal sliding mode control (FITSMC) approaches under normal and open one-phase and two-phase faulty conditions. The SMC and FITSMC design processes have been deeply illustrated, while the stability of the aforementioned controllers has been guaranteed via Lyapunov theory. These ones are all designed based on rotor speed error which is generated from its measured and referenced values. Simulation results confirm the effectiveness and feasibility of the proposed control approaches in the fault tolerant control strategy and normal drive for Five-Phase IPMSM.
PurposeThe purpose of this paper is to develop sliding mode control with linear and nonlinear manifolds in discrete‐time domain for robot manipulators.Design/methodology/approachFirst, a discrete linear sliding mode controller is designed to an n‐link robot based on Gao's reaching law. In the second step, a discrete terminal sliding mode controller is developed to design a finite time and high precision controller. The stability analysis of both controllers is presented in the presence of model uncertainties and external disturbances. Finally, sampling time effects on the continuous‐time system outputs and sliding surfaces are discussed.FindingsComputer simulations on a three‐link SCARA robot show that the proposed controllers are robust against model uncertainties and external disturbance. It was also shown that the sampling time has important effects on the closed loop system stability and convergence.Practical implicationsThe proposed controllers are low cost and easily implemented in practice in comparison with continuous‐time ones.Originality/valueThe novelty associated with this paper is the development of an approach to finite time and robust control of n‐link robot manipulators in discrete‐time domain. Also, obtaining an upper bound for the sampling time is another contribution of this work.
In this article, a simple yet efficient adaptive control method is proposed to investigate synchronizing two chaotic systems. This approach presents an improved type-2 fuzzy wavelet neural network for estimating the unknown terms and the external disturbance in the chaotic systems’ dynamics. Furthermore, an efficient robust control term is integrated into the suggested controller so that the robustness of the controller against system unknown disturbances and uncertainties is improved. This approach offers a very desirable characteristic as a model-free controller. With the help of the Lyapunov stability theory supported with the transient performance analysis, it is established that the proposed control scheme can guarantee the synchronization and the stability of the closed-loop control system. Comparative simulation results with radial basis function neural networks are given that prove the proposed method has superiority in secure communication applications.
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