Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Rank-density-based multiobjective genetic algorithm and benchmark test function study
IEEE Transactions on Evolutionary Computation
A unified approach for sensitivity design of PID controllers in the frequency domain
WSEAS Transactions on Systems and Control
Robust performance characterization of PID controllers in the frequency domain
WSEAS Transactions on Systems and Control
Multi-objective optimum design of balanced SAW filters using generalized differential evolution
WSEAS TRANSACTIONS on SYSTEMS
Some observations on development and testing of a simple autotuning algorithm for PID controllers
WSEAS Transactions on Systems and Control
Robust stabilization of interval plants using Kronecker summation method
WSEAS TRANSACTIONS on SYSTEMS
WSEAS TRANSACTIONS on SYSTEMS
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This paper proposes a novel adaptive genetic algorithm (AGA) for the multi-objective optimization design of a fractional PID controller and applies it to the control of an active magnetic bearing (AMB) system. Different from PID controllers with three constants, the fractional PID controller's parameters are composed of proportional constant, integral constant, derivative constant, derivative order and integral order. The fractional PID controller is more flexible and gives the possibility of adjusting more carefully the closed-loop system characteristics. However, its design becomes more complex than that of conventional integer order PID controller. An adaptive genetic algorithm is proposed to design the fractional PID controller. The five parameters of the fractional PID controller are selected as parameters to be determined. The dynamic model of an AMB system for axial motion is also presented. The simulation results of this AMB system show that a fractional PID controller designed via the proposed AGA has good performance.