This paper presents the design of a robust proportional integral and derivative (PID) controller for a first-order lag with pure delay (FOLPD) model using particle swarm optimization (PSO)-enabled automated quantitative feedback theory (QFT). The plant model considered here can be approximated as a first-order system with a non-minimum phase (NMP) zero. Synthesis of controller for the FOLPD model via manual graphical technique involved in the QFT method is always a challenging and cumbersome task, because an NMP system stabilizes by a small gain. In this paper, a proposal is being presented to automate the loop-shaping phase in the QFT design method to synthesize a robust controller that can undertake the exact amount of plant uncertainty even in the presence of larger uncertainties than those assumed initially and can ensure a proper trade-off between robust stability and tracking performance specifications over the entire range of design frequencies. In this paper,s the PSO technique has been employed to tune the controller automatically,which can significantly reduce the computational effort compared with manual graphical techniques. It has also been demonstrated that this methodology not only automates loop shaping but also improves design quality and, most usefully, improves performance with optimally tuned PID controller in quantitative manner.
This paper presents the design of a robust PID controller for load frequency control of non-minimum phase Hydro power plant using Particle Swarm Optimization (PSO) enabled automated Quantitative Feedback Theory (QFT). The plant model considered here is a Dynamic Model of Power System that includes the turbine, governor, load and machine dynamics subjected to control the load frequency in accordance with power input to the governor. In the present contribution, a proposal is being presented to automate the loop shaping phase in QFT design method to synthesize a robust load frequency controller that can undertake the exact amount of plant uncertainty and can ensure a proper trade off between robust stability specifications and plant input disturbances over the entire range of frequencies. In this article the PSO technique has been employed to tune the controller automatically that can greatly reduce the computational effort compared to manual graphical techniques. It has also been demonstrated that this methodology not only automates loop-shaping but also improves design quality and, most usefully, improves the quality with a reduced order controller.
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