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Exploratory Particle Swarm Optimization: Stability and Robot Control Tuning

Rashvand, Armin
http://rave.ohiolink.edu/etdc/view?acc_num=csu1451082975

Abstract Details

2015, Master of Science in Electrical Engineering, Cleveland State University, Washkewicz College of Engineering.
The goal of this research is to propose, implement, and analyze a new particle swarm optimization (PSO) algorithm with enhanced exploration, referred to as exploratory particle swarm optimization (ExPSO). We use the PSO and ExPSO algorithms to optimize tuning parameters for a passivity-based impedance controller on a hip robot simulation model which is used for testing a prosthetic leg. ExPSO has features in common with negative reinforcement particle swarm optimization (NPSO); both algorithms use not only individuals’ successes, but also their mistakes, to modify individual velocities in the search space. NPSO uses mistakes to avoid poor solutions, but ExPSO uses mistakes to increase exploration. The 2005 Congress on Evolutionary Computation (CEC 2005) benchmark problems are used to evaluate the performance and parameter tuning of PSO and ExPSO. We find that ExPSO can arrive at optimum solutions better and faster than PSO and NPSO, especially for high-dimensional and complex problems. ExPSO can find solutions that are up to 55% better in terms of cost function values. For the problems that we tested, the standard form for ExPSO which is based on standard PSO (SPSO), namely ExSPSO, can solve 10 out of 38 benchmarks better than SPSO. SPSO can solve 7 out of 38 benchmarks better than ExSPSO, and both algorithms can solve 21 out of 38 benchmarks equally well. Additionally, analytical convergence conditions for ExPSO are derived.
Dan Simon, PhD (Committee Chair)
Hanz Richter, PhD (Committee Member)
Majid Rashidi, PhD (Committee Member)
Antonie van den Bogert , PhD (Committee Member)
Electrical Engineering

Recommended Citations

Citations

  • Rashvand, A. (2015). Exploratory Particle Swarm Optimization: Stability and Robot Control Tuning [Master's thesis, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1451082975

    APA Style (7th edition)

  • Rashvand, Armin. Exploratory Particle Swarm Optimization: Stability and Robot Control Tuning . 2015. Cleveland State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1451082975.

    MLA Style (8th edition)

  • Rashvand, Armin. "Exploratory Particle Swarm Optimization: Stability and Robot Control Tuning ." Master's thesis, Cleveland State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=csu1451082975

    Chicago Manual of Style (17th edition)

csu1451082975
435
© 2015, all rights reserved.
This open access ETD is published by Cleveland State University and OhioLINK.