Evolving robust controller parameters using covariance matrix adaptation

In this paper, the advantages of introducing an additional amount of tests when evolving parameters for specific purposes is discussed. A set of optimal PID-controller parameters are sought for an exemplary system, which simulates a human-like robotic arm. When evolving the controller parameters, the number of different movements included in the optimization process is varied. By including extra movements to the optimization process, the time it takes to evolve the parameters does increase, but the uncertainty due to noise is correspondingly lowered. Additionally, it is shown that the added movements, which improve robustness of the system, do not significantly lower the overall performance of the resulting system, when utilizing the evolved parameters. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Control theory; I.2.9 [Artificial Intelligence]: Robotics—Manipulators; J.2 [Computer Applications]: Physical Sci...

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Gerulf K. M. Pedersen, Martin V. Butz
• Keywords: GECCO 2010, Optimal Pid-controller Parameters, Optimization, Optimization Process, Parameters