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A non-minimal state variable feedback approach to multivariable control of glasshouse climate.

Research output: Contribution to journalJournal article


Journal publication date1995
JournalTransactions of the Institute of Measurement and Control
Journal number4
Number of pages12
Original languageEnglish


The paper discusses the multivariable modelling and control of a glasshouse micro-climate. A linear reduced-order control model is obtained from a nonlinear simulation model using novel data-based model reduction and linearisation techniques. This control model is then used to design two multivariable non-minimal state variable feedback (SVF) control systems. The first utilises an LQoptimal Proportional-Integral-Plus (PIP) design method incorporating multi-objective optimisation of the weighting matrices, achieving partial dynamic decoupling; while the second uses an algebraic approach to combined pole-assignment and full dynamic decoupling. These controllers are evaluated, to ensure robustness, using the nonlinear simulation model, prior to implementation and evaluation on the real glasshouse during the 1993-94 winter growing season. Control results are excellent with very tight control to the desired setpoints in all three climate variables. For example, air temperature is controlled to within 0.5°C of the setpoint for 85% of the validation period, and is shown to be very robust to model uncertainty and extreme weather conditions.