Optimization of Emotional Learning Approach to Control Systems with Unstable Equilibrium

  • Mohammad Hadi ValipourEmail author
  • Khashayar Niki Maleki
  • Saeed Shiry Ghidary
Part of the Studies in Computational Intelligence book series (SCI, volume 569)


The main problem concerning model free learning controllers in particular BELBIC (Brain Emotional Learning Based Intelligent controller), is attributed to initial steps of learning process since the system performance is dramatically low, because they produce inappropriate control commands. In this paper a new approach is proposed in order to control unstable systems or systems with unstable equilibrium. This method is combination of one imitation phase to imitate a basic solution through a basic controller and two optimization phases based on PSO (Particle Swarm Optimization) which are employed to find a new solution for stress generation and to improve control signal gradually in reducing error. An inverted pendulum system is opted as the test bed for evaluation. Evaluation measures in simulation results show the improvement of error reduction and more robustness than a basic tuned double-PID controller for this task.


Particle Swarm Optimization Unstable Equilibrium Optimization Phase Basic Controller Active Queue Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mohammad Hadi Valipour
    • 1
    Email author
  • Khashayar Niki Maleki
    • 2
  • Saeed Shiry Ghidary
    • 1
  1. 1.Department of Computer EngineeringAmirkabir University of TechnologyTehranIran
  2. 2.The University of TulsaTulsaUSA

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