ASPECT-f
Advanced control algorithms for programmable logic controllers
Fuzzy-Gain Scheduling Controller with On-line Learning and Tuning
The controller is intended for control of highly nonlinear processes, where the process dynamics vary depending on the operating point. For example, a process exhibits very fast dynamics in a “high" region and slow dynamics in a "low" region. A standard PID controller tuned for good performance in the "high" region performs sluggishly in the "low" region. The mentioned operating point or region is specified by a so-called scheduling variable that may be selected either as the current process output value, the controller output signal, or an external signal.
The controller could be effectively used on processes:
- Heating exchangers
- Hydraulic plants
- Level control
- Chemical and bioreactors
- Neutralization
- Control of pH
FEATURES:
- Control system, intended for closed loop process control;
- Designed for efficient control of 'demanding' processes (nonlinear, slowly time variant, with dead time);
- Better performance than the conventional PID controller;
- Scheduling or switching of controller parameters;
- Automatic tuning of controller parameters using a nonlinear model of the process;
- Nonlinear process model: fuzzy set of local linear models;
- On-line learning of the nonlinear model by analyzing process signals during experiments or regular closed loop operation;
- On-line control performance monitoring;
- Control system implemented on a standard Mitsubishi PLC platform;
- No expensive hardware required;
- Operator interacion via standard industrial HMI similarly to conventional PID controllers;
- Connection to SCADA is possible;
- Simple commissioning procedure;
- Applied and tested on several types of industrial processes;
Application example: pressure difference control (nonlinear, time-variant process)
