Model reference adaptive predictive control of a variable-frequency oil-cooling machine

Abstract

This paper develops methodologies and techniques for the design, analysis and implementation of a model reference adaptive predictive temperature controller for a variable frequency oil-cooling machine, suited for cooling high-speed machine tools. The oil-cooling process is modeled experimentally as a first-order system model with a time-delay, and its system parameters are identified using the recursive least-square method. Based on this model, a model-reference adaptive predictive controller is proposed for achieving set-point tracking and disturbance rejection. A real-time model-reference adaptive predictive control algorithm is then presented and implemented utilizing a standalone digital signal processor TMS320F243 from Texas Instruments. The experimental results show that the proposed control method is proven capable of giving satisfactory performance under set-point changes, fixed loads and load changes.