TUNING OF IMC CONTROLLER USING LQR

Abstract

The controller design has been a prime focus since the evolution of control theory. Since then, various methodologies for controller design have come up. In classical controller design domain, one such technique is the Internal Model Control. This dissertation work presents a deep insight in the Internal Model Control (IMC) theory. The IMC theory is built around the internal model principle. The overall IMC strategy is analyzed thoroughly. Although there are many other advantages of IMC, one exciting fact about this technique is that the control is achieved via only one tuning parameter ( ). In spite of having some fine advantages, there is a particular drawback that there isn’t any systematic tuning rules for finding the value of  . In literature, some techniques have been developed so far for the evaluation of  but most of them have failed in some or the other way. Because of this, usually researchers opt for the hit and trial method. To overcome this difficulty, this dissertation presents a new approach in the quantitative computation of the tuning parameter  . This has been carried out by incorporating the advanced control techniques in the classical control, i.e. the Linear Quadratic Regulator (LQR) approach in IMC. A systematic algorithm for determining the tuning parameters is developed and elucidated in an orderly manner. The proposed approach was successfully applied on the different types of plant models and for Load Frequency Control (LFC) problem for power systems. The system responses are simulated and the results are neatly depicted. The simulation results are testimony to the efficacy of the proposed technique.