IMPLEMENTATION OF AN ONLINE ADAPTIVE FUZZY CONTROLLER IN LOW-END HARDWARE

The implementation of art on-line adaptive fuzzy control algorithm in low-end hardware is described. The adaptive controller starts with a vacuous control policy, i.e. its initial control surface is derived from a vacuous rule base. The control surface is adapted autonomously in real time using control meta-knowledge and basic learning constructs. Limited system-dependent information is incorporated to tailor the Intel-8031-based hardware to specific applications. This information includes input and output signal magnitudes and time-scale information. Simulations and actual experiments indicate that the on-line adaptive controller is very robust and fault-tolerant. A relatively high learning rare enables the controller to learn to control plants in real time even while it is controlling them.