هوش ازدحامی مبتنی بر حداکثر جستجوی کنترلی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|52716||2011||9 صفحه PDF||سفارش دهید||7106 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 38, Issue 12, November–December 2011, Pages 14852–14860
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.