An Associative Memory Based Learning Control Scheme with PI-Controller for SISO-Nonlinear Processes

The paper discusses the real-time implementation of an associative-memory-based learning control scheme with PI-controllers for nonlinear processes. Starting with a pre-assumed PI-controller which only has to stabilize the process the controller parameters are optimized on-line by a predictive optimization. This optimization uses for prediction the model of the process stored in an associative memory which is also learned on-line. The situation-dependent optimized controller parameters are also stored in an associative memory. The concept is a modification of the LERNAS-system (Ersü,1984), which is also shortly described and compared to the system described here. Some experimental results with a nonlinear pH-control demonstrate the performance of the system.