American Journal of Applied Sciences 9 (7): 979-987, 2012 ISSN 1546-9239 © 2012 Science Publications Corresponding Author: Amine Chouchaine, Department of Electric Engineering, Laboratory of Analysis Conception and Control of Systems, National School of Engineering of Tunis, Tunisia 979 Thermal Control of a Greenhouse by Variation in Ventilation Rate using a Fuzzy Parallel Distributed Compensation Controller with an RST Regulator in Each Rule Elyes Feki, Amine Chouchaine and Abdelkader Mami Department of Electric Engineering, Laboratory of Analysis Conception and Control of Systems, National School of Engineering of Tunis, Tunisia Abstract: Problem statement: The greenhouse has uncontrollable inputs that affect its climate, which arises the difficulty to regulate its inside temperature. The solution can be found using a multi-system approach like the Takagi-Sugeno System from which a design of a Parallel Distributed Compensation (PDC) controller is performed. However, a stability problem arises and was negotiatesd in general based on a Lyapunov criterion. The latter isn’t appropriate in our case because of the great number of rules describing the greenhouse. Approach: An alternative solution is proposed using a PDC controller with a local RST regulator in each rule. The synthesis of each one is determined using pole placement avoiding the cross-coupling (that may cause instability) between the local regulators and the sub-models related to differents rules. Results: The proposed fuzzy controller was applied to an experimental greenhouse and was able to lead the inside temperature to the desired value despite the externals perturbations. Conclusion: The presented study offer a simple solution to the stability problem when using PDC controller and so can be mush more implementable than the others stabilization methods presented in the literature. In the agriculture field, it can replace the on-off control action that is widely used in the greenhouses because of the processus complexity. Key words: TS fuzzy models, PDC controller, greenhouse, lyapunov function INTRODUCTION The efficiency of fuzzy systems when dealing with complex and nonlinear process is well known in the literature. In fact, most of the systems in the industry have complicatedmathematical models that are barely exploitable and so the control of such process becomes very difficult. To solve this problem, fuzzy control were used in the beginning without the need of process model (Mamdani and Assilian, 1975). It’s structure is the fusion of control rules described by linguistic terms defined from the knowledge of the process. Very soon the fuzzy system where used also to models some process with successful results (Mamdani, 1977). Recently another fuzzy system has emerged named as the Takagi-Sugeno systems (Takagi and Sugeno, 1985). This latter differ from the former in the rules consequents: It’s not a fuzzy set but it’s a local model of the system to be approximated. His popularity in modeling and control is continually growing. Indeed, by fitting several local models representing multiples operating points of a process, TS fuzzy model adequately describe the system guaranteeing precision and stability. Moreover, several techniques were used to approximate the submodels parameters; such as weighted least-squares method (Chen and Pham, 2001) or neuro-adaptive learning techniques (Brown and Harris, 1994). Hence, large possibilities can be obtained in the control domain. Wang et al. (1995), a controller structure called Parallel Distributed Compensation (PDC) is introduced which consists in a linear controller developed for each local model. The final control action is obtained using the contribution of all the controllers outputs. Several proposals were presented using this means to control nonlinear processes; (Salaa et al., 2005; Wang et al., 2000; Seddiki et al., 2006) present a PDC control with state feedback in each rule. Le and Stability (2006) the same PDC control is used, with a simulation example, to control a rehabilitation device. In general, a stability problem appears when using PDC controller. In this case, the most used way to deal with it is applying the Lyapunov criteria with same positive defined Matrix to all rules (Tanaka and Sugeno,