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Multiobjective optimization of autonomous control for a biped robot

Multiobjective optimization of autonomous control for a biped robot

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In the present study, a multiobjective particle swarm optimization (PSO) is used to Pareto optimal design of controller for a biped robot walks in the coronal plane. Both nonlinearity of the dynamic equations and the tracking system cause an effective control that has to be used to address these problems.Thus, the proportional-derivative control is employed to control of the robot in the coronal plane, and the multiobjective algorithm is utilized to tune the heuristic parameters of the controller. The obtained Pareto front by the multiobjective PSO algorithm is compared with three prominent algorithms: modified NSGAII, sigma method, and MATLAB® Toolbox MOGA.

Chapter Contents:

  • Abstract
  • 4.1 Introduction
  • 4.2 Optimization algorithm
  • 4.2.1 Particle swarm optimization
  • 4.2.2 Convergence operator
  • 4.2.3 Divergence operator
  • 4.2.4 Combination of PSO, convergence, and divergence operators
  • 4.2.5 Multiobjective procedure
  • 4.3 Biped robot
  • 4.3.1 Dynamic model and inverse kinematic
  • 4.3.2 Proportional–derivative control
  • 4.4 Multiobjective optimal control of the biped robot
  • 4.5 Conclusion
  • References

Inspec keywords: Pareto optimisation; particle swarm optimisation; control system synthesis; robot dynamics; legged locomotion; PD control

Other keywords: controller design; autonomous control; modified NSGA II; Pareto optimal design; multiobjective particle swarm optimization; proportional-derivative control; sigma method; coronal plane; biped robot; dynamic equations; multiobjective PSO algorithm

Subjects: Mobile robots; Control system analysis and synthesis methods; Robot and manipulator mechanics; Optimisation; Optimisation techniques

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