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Evolutionary Intelligence
Published in: Evolutionary Intelligence 1/2019

03-11-2018 | Research Paper

An optimal PID controller for a biped robot walking on flat terrain using MCIWO algorithms

Authors: Ravi Kumar Mandava, Pandu R. Vundavilli

Published in: Evolutionary Intelligence | Issue 1/2019

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Abstract

The design of appropriate controller plays an important role in achieving the dynamically balanced gaits of the biped robot. The present paper deals with the tuning of gains (Kp, Kd and Ki) of the proposed PID controller using two non-traditional global optimization algorithms, namely Particle Swarm Optimization (PSO) and a variant of Invasive Weed Optimization (IWO) called Modified Chaotic Invasive Weed Optimization (MCIWO) algorithms, which is newly proposed by the authors. The effectiveness of the newly proposed MCIWO algorithm has been verified with the help of benchmark functions by conducting the normality test, parametric and non-parametric tests. Further, the developed MCIWO algorithm is used to develop the optimal PID controller for the biped robot. Once the PID controllers are optimized, the performance of the controllers in terms of various performance measures of the biped robot are compared. Finally, the gait generated using the optimal PID controllers are tested on a real biped robot.
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Metadata
Title
An optimal PID controller for a biped robot walking on flat terrain using MCIWO algorithms
Authors
Ravi Kumar Mandava
Pandu R. Vundavilli
Publication date
03-11-2018
Publisher
Springer Berlin Heidelberg
Published in
Evolutionary Intelligence / Issue 1/2019
Print ISSN: 1864-5909
Electronic ISSN: 1864-5917
DOI
https://doi.org/10.1007/s12065-018-0184-y

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