A Comparative Analysis of Sliding Mode and Fuzzy Sliding Mode Controllers for Climate Control Application of a Greenhouse Flower Garden

This paper describes a comparative performance analysis of sliding mode and fuzzy sliding mode controllers for climate control application of a greenhouse flower garden. Various internal and external climate related factors affect the overall growth and health of flowers that needs robust controllers to control the humidity and temperature of the greenhouse flower garden. Review of related works show that for non-linear systems, sliding mode controllers can provide robust performance even though chattering is a major drawback of the controller. A number of approaches are used to solve the chattering problem of sliding mode controllers such as hybrid uses of other controllers along with sliding mode controller. In this paper, sliding mode controller and fuzzy sliding mode controllers are designed and implemented for the specified control application based on the linearized and decoupled model of the system. The performance evaluation has been done for the control problems of reference tracking and disturbance rejection with time domain performance measures of percentage overshoot, settling time and rise time. Accordingly, the overall system has been implemented in MATLAB/Simulink and the simulations for the control problems have been done. Thus, FSMC has got rise time of 5.89min, 10.59min settling time and almost negligible percentage overshoot for indoor temperature at 27°C and humidity at 22g/m3. And for humidity control, the FSMC has got 5.44min settling time and nearly zero percentage overshoot for set point tracking problem. For the disturbance of solar radiation, decrease in outside temperature and fixed set point of 27°C and humidity of 22g/m3, FSMC outperforms SMC. In summary, both quantitative and qualitative results analysis results reveal that fuzzy sliding mode controller (FSMC) outperforms sliding mode controller (SMC) for the indoor temperature and humidity control tasks of both set point tracking and disturbance rejection problems.