Swarm intelligence for controller tuning and control of fractional systems

Swarm intelligence for controller tuning and control of fractional systems

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In this chapter, particle swarm optimization, ant colony optimization, artificial bee colony optimization and cuckoo search optimization are examined in detail. Differences, advantages and disadvantages of these algorithms are emphasized clearly. Performances of the swarm algorithms in terms of computing time, computing complexity and accuracy and convergence behavior are compared each other. As application area, fractional control systems from new attractive topics of control are chosen. In this chapter, the fractional order proportional integral derivative controllers are tuned with the swarm algorithms using objective functions such as integral of absolute error, integral of the squared error, the integral of time multiplied by the absolute error and integral of time multiplied by the squared error. The simulation results can be used to determine which swarm algorithms yield better search performance in the multiobjective and high-dimensional nonlinear constrained optimization problems such as the fractional order control systems.

Chapter Contents:

  • Abstract
  • 10.1 Introduction
  • 10.2 Swarm-based optimization algorithms
  • 10.3 Particle swarm optimization
  • 10.4 Artificial bee colony
  • 10.5 Cuckoo search algorithm
  • 10.6 Ant colony optimization algorithm
  • 10.7 Fractional calculus and fractional order PID controller
  • 10.8 Simulation results and discussion
  • 10.9 Case study 1: lag-dominated FOS
  • 10.10 Case study 2: delay-dominated FOS
  • 10.11 Case study 3: high-order complex delay FOS
  • 10.12 Conclusion
  • References

Inspec keywords: three-term control; search problems; control system synthesis; convergence; computational complexity; particle swarm optimisation; artificial bee colony algorithm; ant colony optimisation

Other keywords: fractional order proportional integral derivative controllers tuning; ant colony optimization; particle swarm optimization; convergence behavior; computing complexity; artificial bee colony optimization; multiobjective optimization problems; high-dimensional nonlinear constrained optimization problems; squared error; fractional order control systems; absolute error; swarm intelligence; cuckoo search optimization

Subjects: Control system analysis and synthesis methods; Computational complexity; Optimisation techniques

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