Designing Fractional-order PIlambdaDµ Controller using a Modified Invasive Weed Optimization Algortihm.
NaBIC(2009)
摘要
Invasive weed optimization (IWO) has been found to be a simple but powerful algorithm for function optimization over continuous spaces. It has reportedly outperformed many types of evolutionary algorithms and other search heuristics when tested over both benchmark and real-world problems. This article describes the design of fractional-order proportional-integral-derivative (FOPID) controllers, using a newly developed variant of IWO, known as IWOSS (invasive weed optimization with stochastic selection). Parameters for FOPID controllers include the proportionality constant, integral constant, derivative constant, derivative order and, integral order; and, its design is more complex than that of conventional integer-order proportional-integral-derivative (PID) controller since the latter involves only three variables. Controller synthesis is based on user specifications like peak overshoot and, rise time; which are used to formulate a single objective optimization problem. Tustin operator-based continuous fraction expansion (CFE) scheme was used to digitally realize fractional-order closed loop transfer function of the designed plant-controller setup. Simulation results for some real life analog plants and, comparison of the same for IWOSS and few established optimization techniques (particle swarm optimization (PSO) and genetic algorithm (GA)) have been presented to support the claim of superiority of the proposed design technique.
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关键词
control system synthesis,genetic algorithms,particle swarm optimisation,three-term control,Tustin operator-based continuous fraction expansion scheme,controller synthesis,fractional-order PIλDμ controller design,fractional-order closed loop transfer function,fractional-order proportional-integral-derivative controllers,genetic algorithm,invasive weed optimization with stochastic selection,modified invasive weed optimization algorithm,particle swarm optimization,plant-controller setup,Fractionalorder PID controller,Genetic Algorithm,Invasive Weed Optimization,Particle Swarm Optimization
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