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Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA)
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This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA). To control the one legged hopping robot, a CPG controller is designed and integrated with a conventional Proportional-Integral (PI) controller. Conventionally, the CPG parameters are tuned manually. But by using this method, the parameters produced are not exactly the optimum parameters for the CPG. Therefore, a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. The GA is designed based on minimizing the error produced towards achieving the reference height. The re-sponse of the one legged hopping robot is compared and the results of the error towards reference height are analyzed.
Title: Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA)
Description:
This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA).
To control the one legged hopping robot, a CPG controller is designed and integrated with a conventional Proportional-Integral (PI) controller.
Conventionally, the CPG parameters are tuned manually.
But by using this method, the parameters produced are not exactly the optimum parameters for the CPG.
Therefore, a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters.
The GA is designed based on minimizing the error produced towards achieving the reference height.
The re-sponse of the one legged hopping robot is compared and the results of the error towards reference height are analyzed.
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