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The paper presents the application of Particle Swarm Optimization PSO technique for the tuning of error-driven self-adjusting multi loop dynamic speed regulator for large industrial PMDC motor drives. Tri-loop dynamic error driven Multi-incremental self regulating controller is simulated and tuned using Particle Swarm optimization PSO for high performance permanent magnet PMDC industrial motor drives...
This paper presents a comparison of swarm intelligence and evolutionary techniques based approaches for minimization of system losses and improvement of voltage profiles in a power network. Efficient distribution of reactive power in an electric network can be achieved by adjusting the excitation on generators, the on-load tap changer positions of transformers, and proper switching of discrete portions...
Considering the flow control of large-scale sewer networks to minimize overflows, a control algorithm based on particle swarm optimization with mutation operator (MPSO) is proposed in this paper to achieve optimal operations of reservoir gates. By introducing element models, the mathematical model of whole sewer network can be formulated. The algorithm is applied to solve the optimization problem...
An optimal motion planning scheme using a modified particle swarm optimization (PSO) is proposed for non-holonomic systems. A cost function is used to incorporate the final errors and control energy. The motion planning is to determine control inputs to minimize the cost function and is formulated as an infinite dimensional optimal control problem. By using the control parameterization, the infinite...
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