Discretized fractional calculus
SIAM Journal on Mathematical Analysis
An introduction to differential evolution
New ideas in optimization
Journal of Global Optimization
Two improved differential evolution schemes for faster global search
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
International Journal of Advanced Intelligence Paradigms
Fractional-order PID controller optimization via improved electromagnetism-like algorithm
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Engineering Applications of Artificial Intelligence
Optimum design of fractional order PIλDµ controller for AVR system using chaotic ant swarm
Expert Systems with Applications: An International Journal
Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm
Applied Computational Intelligence and Soft Computing
Fractional-order PI λDµ controller design
Computers & Mathematics with Applications
Engineering Applications of Artificial Intelligence
Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator
Expert Systems with Applications: An International Journal
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Differential evolution (DE) has recently emerged as a simple yet very powerful technique for real parameter optimization. This article describes an application of DE to the design of fractional-order proportional-integral-derivative (FOPID) controllers involving fractional-order integrator and fractional-order differentiator. FOPID controllers' parameters are composed of 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. Here the controller synthesis is based on user-specified peak overshoot and rise time and has been formulated as a single objective optimization problem. In order to digitally realize the fractional-order closed-loop transfer function of the designed plant, Tustin operator-based continuous fraction expansion (CFE) scheme was used in this work. Several simulation examples as well as comparisons of DE with two other state-of-the-art optimization techniques (Particle Swarm Optimization and binary Genetic Algorithm) over the same problems demonstrate the superiority of the proposed approach especially for actuating fractional-order plants. The proposed technique may serve as an efficient alternative for the design of next-generation fractional-order controllers.