Experience Mapping based Prediction Controller

Abstract

A novel controller termed as Experience Mapping based Prediction Controller (EMPC) is developed in this work. EMPC is developed utilizing the broad control concepts of human motor control (HMC). The concepts of HMC are utilized to develop the core concepts of EMPC for the control of ideal Type-1 LTI systems. The control accuracy of the developed concepts is studied and the mathematical stability criterion for the controller is developed. The applicability of EMPC for the control of real world problems is tested on a Permanent Magnet DC motor based position control system. 1. Novel learning methods are presented to form experience mapped knowledge-base (EMK) which is used for the creation of the forward and inverse models. 2. Control and Adaptation Techniques which overcome the presence of non idealities are developed using the inverse model. 3. Two separate techniques which utilize the forward model for improving the adaptation capabilities of EMPC are developed. 4. Two novel techniques are developed for the improvement of the tracking performance in terms of the accuracy and smoothness of tracking. These techniques are tested under various system conditions including large dynamic parameter changes on a simulation model and a practical setup. The performance of EMPC is compared against that of PID, MRAC and LQG controllers for all the proposed techniques and EMPC is found to perform significantly better under the various system conditions in terms of transient and steady state characteristics. Finally, the effectiveness of EMPC in stabilizing unstable systems using the concepts developed is tested on a practical Inverted Pendulum system. The problem of the simultaneous development of experiences and control of the system is addressed with the stabilizing problem. The proposed controller, EMPC provides an alternative approach for the existing control of systems without the requirement of an accurate system mathematical model. Its capability to learn by directly interacting with the system and adapt using experiences makes it an attractive alternative to other control techniques present in literature. Keywords: EMPC, Position Control, PMDC motors