Direct self-tuning model following predictive control of a variable-frequency oil-cooling machine

Abstract

This paper develops methodologies and techniques for design, analysis and implementation of a direct self-tuning model following predictive temperature controller for a variable-frequency oil-cooling machine, used 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-squares method. Based on this model, a novel adaptive predictive controller is proposed for achieving set-point tracking and disturbance rejection. A real-time direct self-tuning model following predictive control algorithm is then presented and implemented utilizing a standalone digital signal processor (DSP) 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.