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In this paper, a two-phase hybrid particle swarm optimization (PSO) approach is used to solve optimal reactive power dispatch (ORPD) problem. In this hybrid approach, PSO is used to explore the optimal region and direct search is used as local optimization technique for finer convergence. The performance of the proposed hybrid approach is demonstrated with(More)
The Knowledge Base of a Fuzzy Logic Controller (FLC) encapsulates expert knowledge and consists of the Data Base (membership functions) and Rule-Base of the controller. Optimization of these Knowledge Base components is critical to the performance of the controller and has traditionally been achieved through a process of trial and error. Such an approach is(More)
In this paper, particle swarm optimization (PSO) with cauchy mutation (PSO-CM) and adaptive mutation (PSO-AM) approaches are used to solve optimal reactive power dispatch (ORPD) problem. The different mutations are integrated with the classical PSO to overcome its drawbacks. The performance of the proposed approach is demonstrated with the IEEE 14 bus and(More)
This paper presents a modified particle swarm optimization (MPSO) algorithm to design an optimal multi input multi out (MIMO) fuzzy logic controller for a cement mill process. The membership function, rule base and the scaling factor of the multi input multi output FLC is tuned for optimal control performance using MPSO by minimizing the Integral absolute(More)
Conventional PID controllers have been widely applied in industrial process control for about half a century because of their simple structure and convenience of implementation. The implementation of PID controllers needs proper tuning of proportional gains, integral gains, and derivative gains of the controllers. Among the existing gain tuning techniques,(More)
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