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首页> 外文期刊>Journal of applied mathematics >Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System
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Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

机译:粒子群算法和重力搜索算法与非线性系统控制器设计的性能比较

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This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based on the tracking error between reference input given to the system and the system output. Then, the efficacy of the backstepping controller is verified in simulation environment under various system setup including both the system subjected to external disturbance and without disturbance. The simulation results show that backstepping with particle swarm optimization technique performs better than the similar controller with gravitational search algorithm technique in terms of output response and tracking error.
机译:本文提出了用于非线性系统跟踪目的的反推控制器设计。由于设计的控制器的性能取决于控制参数的值,因此重力搜索算法(GSA)和粒子群优化(PSO)技术用于优化这些参数,以实现预定义的系统性能。基于提供给系统的参考输入和系统输出之间的跟踪误差来评估性能。然后,在各种系统设置(包括受外部干扰的系统和无干扰的系统)的仿真环境中,验证了反步控制器的功效。仿真结果表明,在输出响应和跟踪误差方面,采用粒子群优化技术的反推性能优于采用重力搜索算法的同类控制器。

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