Biological-environment Adaptive Control System

Proceeding of 2013 International Seminar on Climate Change and Food Security ISCCFS 2013 Palembang, South Sumatra -Indonesia, 24-25 October,2013 117 Modification of the environment in plant house in order to produce qualified crops had been carried out by previous researchers [6][7][8]. For examples: the optimization of the lighting system by using a genetic algorithm in a plant house [9], controlling the moisture for optimum plant growth for Chrysanthemum in plant house [10], identifying system and analyzing the application of the identification system for controlling environment in plant house [11]. Furthermore, computer-based technology was developed to create the optimal condition for optimal plant growth [12][13]. A computer-based algorithm was also developed to control flowering plants [14], as well as automatic fertigation system for speaking plant approach in greenhouse [15]. There has been quite a lot of computer-based controls of the plants environment parameters in Indonesia. The software developed is still limited to the use of certain control mode and not yet available to the plant environment identification facilities. Biological-environmental identification is based on the understanding the model that describes the relationship between environmental factors with plant to be harvested. Understanding the response of plants in such a situation is termed asbiological-environment. It is still very difficult to develop a sensor that can be used to evaluate the performance of plants directly real time. Nevertheless, it is constantly evolving and there have been attempts to identify the biological- environment control system, namely through the control system based on plant responses speaking plant approach. Environmental-control systems are still rare in the form of biological software that combines with the facility of control mode selection, especially in Indonesia. It is still necessary to develop a system that is flexible, which provides a mechanism for the selection and identification of control mode and plant in an integrated environment. Biological-environment adaptive control system in the plant house was developed without the requirement of output sensor for the plant produce. In other words, real time control detection towards output plant produce is not required anymore. Due to the detection of plant produce properties is not required in the operation of real time control, the output data can be both destructively and non-destructively collected. It is possible to choose the plant produce properties as the target, and this flexibility makes biological-environment adaptive control is more applicable. This paper describes the perspective of biological-environment adaptive system in plant house as alternative technology to address the climate changes.

2. Biological-environment Adaptive Control System

Biological-environment adaptive control system is a software system that provides control facilities which reference or set point optimal environment can be adjusted to the desired condition of plant produce. The desired condition of plant produce can be based on the quantity, quality, or taste. This control system provides a facility that controls the variable mode selection to the set point, in other words, the error of the response is small and stable to control systems in all areas of operation. There are two optimization solutions, namely the optimal environment to be used as a reference and optimal control parameters to obtain the desired performance. Adaptive control is control parameters that can be adjusted to the real condition. Optimal control is a control that combines optimization based on theory for determining the performance of the control system, so it can respond as efficient as possible to the variables that change over time. There are two terms in biological-environment adaptive control system, namely the optimization environment that will serve as a reference, and optimization control parameters that control the response to get the performance associated with minimum error. The control design in adaptive control system includes four stages, namely measuring, comparing, counting, and correcting. Three stages of controlling system are grouped as controller which compares the reference with variable process, calculates how many corrections that needs to be done, and issues a correction signal in accordance with the results of the calculation. Algorithm is to calculate the magnitude of the correction that is done by the mode control, such as fuzzy and PID Proportional-Integral-Differential. Input of mode control is error and error change, while the output is signal correction or manipulation of variables that can be changed, therefore the magnitude of the variable control or process is equal to the reference. Each mode control has parameter in order to maintain Proceeding of 2013 International Seminar on Climate Change and Food Security ISCCFS 2013 Palembang, South Sumatra -Indonesia, 24-25 October,2013 118 the similarity of variable process to reference. These parameters should be optimized to avoid instability of the control system by reference change or disturbance. Biological-environment adaptive control system based on the identification of the optimal set point and the estimation of optimal control parameter consists of sub-system of optimal contro l parameter‘s determination and sub-system of real-time control. The results of those sub-systems can be applied on the real time controlling of biological environment in the plants house. There are two terms of biological-environment. Firstly, it is the relationship between environmental factors as inputs and plant produce as output. Secondly, the sensors for detecting the inputs and outputs are placed near the plant canopy in order to detect the surrounding conditions of plants related to photosynthesis, respiration and transpiration. The optimal environmental condition for plant growth has to be established prior to controlling by using a mathematical equation model.

3. Structure and Component of Biological-Environment Adaptive Control System