Multirate adaptive temperature control of greenhouses
A new adaptive technique is proposed for the control of the temperature in a greenhouse whose parameters vary with operating conditions. The proposed adaptive controllers are derived by solving either the pole-placement or the linear quadratic regulation (LQR) problem and use multirate controllers in which the greenhouse temperature is sampled many times over a fundamental sampling period. On the basis of the proposed control scheme, the problem is reduced to an associated discrete-time problem for which constant state feedback controllers are derived. Thus, the proposed technique essentially becomes one of computing a constant gain controller rather than one of deriving state observers or output feedback controllers, as in other indirect adaptive control techniques. As a consequence, the exogenous dynamics introduced in the control loop is of low order. Furthermore, the proposed adaptive controllers can be designed to possess any degree of stability, since their transition matrices can be chosen arbitrarily. The proposed scheme estimates the unknown parameters of the greenhouse on-line from sequential data on the greenhouse temperature and the heating power, which are recursively updated. Persistency of excitation of the controlled system is assured without making assumptions on the system under control, other than controllability, observability and known order. Simulation results of the greenhouse dynamics illustrate the effectiveness of the proposed scheme.
temperature control adaptive control greenhouse climate sampled-data control multirate sampling identification