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

Proportional-integral-plus (PIP) controllers, based on nonminimal state-space design methods have been successfully implemented in a number of difficult applications including, for example, self-adaptive control of a nonlinear temperature control system, control of glasshouse micro-climate, etc. The present 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 algorithm. To exemplify the methodology, two rather different nonlinear systems are considered: 1) adaptive multivariable control of greenhouse micro-climate; and 2) adaptive control of flow dynamics on inter-urban traffic networks.