Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems

Abstract

A new concept called "betterment process" is proposed for the purpose of giving a learning ability of autonomous construction of a better control input to a class of multi-input multi-output servomechanism or mechatronics systems such as mechanical robots. It is assumed that those dynamic systems can be operated repeatedly at low cost and in a relatively short time under invariant initial physical conditions, but the knowledge on precise description of their dynamics is not required. The betterment process is composed of a simple iteration rule that generates autonomously a present actuator input better than the previous one, provided a desired output response is given. The convergence of iteration is proved for a simple betterment process where the k+1th input is composed of the kth input plus an increment of the derivative error between the kth output response and given desired response. Discussions on potential applications of the proposed theory to controlling robots or other mechanical systems are presented together with future subjects to be investigated.