Neuro-Control Applications

Abstract

In this chapter we discuss several neuro-control techniques with applications to real physical processes; a water bath temperature control system, an inverted pendulum, an electric vehicle generator control system, and a multi-input multi-output furnace. For the water bath and furnace temperature control systems, the emulator and controller neuro-control scheme is applied. However, as these real processes are slow in nature, offline learning methods are used to train the neural networks at first and then on-line learning is applied using the architecture of Fig. 4.2.5 for fine-tuning their performances. In these applications comparison is made with several traditional control methods under varying complexities in the processes. As neuro-control is relatively new it is important to see how well it compares to the more established traditional control approaches.