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Gaussian Quantum-Behaved Particle Swarm Optimization Applied to Fuzzy PID Controller Design

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Quantum Inspired Intelligent Systems

After having enjoyed an increasingly great popularity in Japan during the last two decades, Fuzzy Logic Control (FLC) systems have been investigated in many technical and industrial applications as a powerful modeling tool that can cope with the uncertainties and nonlinearities of modern control systems. Conventional control depends on the mathematical model of the plant being controlled. FLCs have become popular because they do not necessarily require a theoretical model of the plant which is to be controlled. The main drawback of these FLC methodologies in the industrial environment is the number of tuning parameters to be selected. Inspired by the classical particle swarm optimization (PSO) method and quantum mechanics theories, this work presents a novel Quantum-behaved PSO approach using Gaussian distribution (G-QPSO) to tune the design parameters of a FLC with PID (Proportional-Integral-Derivative) conception. The FLC-PID design has been applied to a control valve with nonlinear dynamic behavior. Numerical results presented here indicate that proposed FLC-PID design with G-QPSO is effective for the control of reactor.

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Coelho, L.d.S., Nedjah, N., Mourelle, L.d.M. (2008). Gaussian Quantum-Behaved Particle Swarm Optimization Applied to Fuzzy PID Controller Design. In: Nedjah, N., Coelho, L.d.S., Mourelle, L.d.M. (eds) Quantum Inspired Intelligent Systems. Studies in Computational Intelligence, vol 121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78532-3_1

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  • DOI: https://doi.org/10.1007/978-3-540-78532-3_1

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