Self-Tuning Regulators

This chapter discusses some knowledge of stochastic control-theoretic concepts and recursive parameter estimation. It deals with implicit self-tuning regulators (STRs) and includes the minimum-variance STR and the generalized minimum-variance STR, as well as algorithms for the same. The chapter describes explicit self-tuning regulators with special reference to the pole placement approach as well as the polezero placement method. It also discusses the unification of different algorithms and equivalence between STR and model reference adaptive control (MRAC). The chapter considers linear-quadratic-Gaussian (LQG) self-tuning and outlines explicit and implicit approaches. It provides two design procedures to handle plants displaying non-minimumphase behavior which is commonly encountered in many industrial plants. The chapter also deals with the development of hybrid self-tuning and explains the convergence analysis. The self-tuning program is in the form of a collection of modules for initial parameter entry, sequence control, self-tuning, parameter dumps, and error processing.