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Swarm optimization tuned fuzzy sliding mode control design for a class of nonlinear systems in presence of uncertainties

机译:存在不确定性的一类非线性系统的群体优化调谐模糊滑模控制设计

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摘要

This paper provides an optimal controlling approach for a class of nonlinear systems with structured and unstructured uncertainties using fuzzy sliding mode control. First known dynamics of the system are eliminated through feedback linearization and then optimal fuzzy sliding mode controller is designed using an intelligent fuzzy controller based on Sugeno-Type structure. The proposed controller is optimized by a novel heuristic algorithm namely Particle Swarm Optimization with random inertia Weight (RNW-PSO). In order to handle, the uncertainties Lyapunov method is used. There are no signs of the undesired chattering phenomenon in the proposed method. The globally asymptotic stability of the closed-loop system is mathematically proved. Finally, this control method is applied to the inverted pendulum system as a case study. Simulation results show desirability of the system performance.
机译:本文针对一类具有结构和非结构不确定性的非线性系统,采用模糊滑模控制提供了一种最优控制方法。首先通过反馈线性化消除系统的已知动力学,然后使用基于Sugeno-Type结构的智能模糊控制器设计最佳模糊滑模控制器。通过一种新颖的启发式算法,即具有随机惯性权重的粒子群优化(RNW-PSO),对提出的控制器进行了优化。为了处理,使用不确定性李雅普诺夫方法。在所提出的方法中没有迹象表明不希望的颤动现象。数学上证明了闭环系统的全局渐近稳定性。最后,将此控制方法应用于倒立摆系统作为案例研究。仿真结果表明系统性能是理想的。

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