Intelligent control and adaptive control for interacting system

Level is one of the important parameters to be controlled in process control systems, irrigation and in industries. The process industries require liquids to be pumped, stored in tanks and then pumped to another tank. In agriculture, the level of the water must be controlled for irrigation in order to protect the plants. Always level of fluids in tanks must be controlled and the flow between tanks must be regulated. This is a laborious process and involves immense time and patience. So the paper has been taken up to make it an efficient process. This paper presents about the level control of the interacting system using PID control, neuro control and non-linear transformation control. First, the single tank (SISO) process is modeled and the level is controlled. Next, the interacting system with multiple input and multiple output (MIMO) process is taken and the levels in the two tanks are controlled. Because of the interactions, the levels of the two tanks are varied and there is a need for decoupler to minimize the interactions. The controller design is divided into two parts: firstly, a decoupling matrix is designed in order to minimize the interaction effects. Then, the controller design is obtained for the process + decoupler block. The reason is to meet design specifications for each loop independently. The modeling and controlling design is done using MATLAB R2008b tool box. So, with the help of conventional control, neural control and adaptive control the levels in the tanks are maintained as well as the interacting loops in the process is rendered non-interacting by the use of decouplers. The result shows that, neural controller replaces two PID controllers & two decouplers whereas adaptive controller is designed directly for the nonlinear process which minimizes the time very well.