Adaptive PIP control with application to greenhouse systems and dynamic traffic management

Proportional-Integral-Plus (PIP) controllers, based on Non-Minimal State-Space (NMSS) design methods have been successfully implemented in a number of difficult applications including, for example, the self-adaptive control of a non-linear temperature control system; control of glasshouse micro-climate; multivariable decoupling of a realistic high order, non-linear simulation model of the Harrier VSTOL aircraft at its most difficult flight condition; and the control of various agricultural crop growth and plant physiology experiments. The present short paper concentrates on adaptive versions of the controllers, where the identification and estimation of the control model exploits the special properties of the recursive Simplified Refined Instrumental Variable (SRIV) algorithm. To exemplify the methodology, two rather different non-linear systems are considered: in the first place, adaptive multivariable control of greenhouse micro-climate; and secondly, the adaptive control of flow dynamics on interurban traffic networks