کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385109 | 660860 | 2011 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Swarm intelligence-based extremum seeking control Swarm intelligence-based extremum seeking control](/preview/png/385109.png)
This paper proposes an extremum seeking control (ESC) scheme based on particle swarm optimization (PSO). In the proposed scheme, the controller steers the system states to the optimal point based on the measurement, and the explicit form of the performance function is not needed. By measuring the performance function value online, a sequence, generated by PSO algorithm, guides the regulator that drives the state of system approaching to the set point that optimizes the performance. We also propose an algorithm that first reshuffles the sequence, and then inserts intermediate states into the sequence, in order to reduce the regulator gain and oscillation induced by population-based stochastic searching algorithms. The convergence of the scheme is guaranteed by the PSO algorithm and state regulation. Simulation examples demonstrate the effectiveness and robustness of the proposed scheme.
► This paper propses an extremum seeking control scheme based on particle swarm optimization (PSO).
► The system states are steered to the optimal point by the controller, and the explicit form of the performance function is not needed.
► We also propose an reshuffle-then-insertion algorithm to reduce the regulator gain and osillation induced by population-based stochastic searching algorithms.
Journal: Expert Systems with Applications - Volume 38, Issue 12, November–December 2011, Pages 14852–14860