A gain adaptive scheme for the generalised predictive control of an air-handling plant

This paper describes a gain-adaptive scheme developed for the generalised predictive control of an air-handling plant. CARMA models are used to generate j-step-ahead predictions of the process output instead of the more commonly used incremental parametric models. The use of standard and long range predictive RLS algorithms in estimating the parameters of these models are investigated. Some performance indices of such derived models in relation to different prediction horizons are revealed and their effects on control performance discussed. Experimental results show that the gain-adaptive algorithm developed can give significant improvements on the global control performance in the presence of a nonlinear process gain that is strongly linked to the operating conditions of the plant