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Optimization of static and dynamic anti-windup compensator using new improved particle swarm optimization algorithm

机译:新改进粒子群优化算法优化静态抗风补偿器的优化

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In this paper, the optimal static and the dynamic anti-windup compensators (AWC) are designed using a new improved particle swarm optimization (PSO) algorithm. The existing optimization techniques for AWC make use of LMI (Linear Matrix Inequality) and various concepts of nonlinear control concepts that require complex mathematics. For this optimization, we have developed and utilized an improved version of PSO. In this new improved PSO algorithm, first the problem-space is explored with constant non-zero inertia factor until the fitness function saturates to a local or global minima. The solution obtained thus far is then further refined by rerunning the algorithm but with inertia factor set to zero. This slight improvement enables a better search for a solution within the already explored problem-space. The optimized static and dynamic AWC is compared with the existing LMI-based AWC for the performance index, and it is observed that the improved PSO-based AWC gave better results and optimized value of the performance index.
机译:在本文中,使用新的改进的粒子群优化(PSO)算法设计了最佳静态和动态抗风补偿器(AWC)。 AWC的现有优化技术利用LMI(线性矩阵不等式)和需要复杂数学的非线性控制概念的各种概念。对于这种优化,我们开发并利用了PSO的改进版本。在这种新的改进的PSO算法中,首先,使用恒定的非零惯量因子探索问题空间,直到健身功能饱和到本地或全球最小值。因此,通过重生算法而是进一步改进迄今为止所获得的解决方案,但惯性因子设置为零。这种略微改进使得能够更好地搜索已经探索的问题空间内的解决方案。将优化的静态和动态AWC与现有的基于LMI的AWC进行比较,并且观察到基于PSO的AWC的改进的效果和优化的性能指标值。

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