- Project Summary
The proposed scheme consists of a fuzzy logic switching method within the Model Reference Adaptive Control (MRAC) framework without using any explicit identifier. The switching scheme is used for generating appropriate reference models on line so that effective overall performance of the adaptive controller is achieved. The scheme is based on Takagi-Sugeno fuzzy system and produces a ‘soft’ way of generating the reference model, combining a group of weighted reference models effective at each modal operation. The scheme can therefore be implemented as a Fuzzy Multiple Reference Model Adaptive Controller (FMRMAC). Following a rule base, the fuzzy switching scheme effectively monitors changes in plant operating conditions and mode changes due to any sudden ‘Jumps’ in the plant. A fuzzy inference engine then fires appropriate rules, which gives fuzzified output values. Defuzzification is then performed on line, monitoring the plant auxiliary states or derived measurements. The main contribution of such approach is that it can be performed online and is very well suitable for applications that show sudden movements viz., ‘Jumps’ in the plant operating conditions. Unlike static multiple model algorithms for switching (non-interacting individual model-based filters) or switching dynamic algorithms (susceptible to numeric overflow), this scheme provides an interactive multiple model environment with soft switching. The scheme is computationally feasible, effective and efficient. Further this method can be enhanced by additional learning strategy to modify the rule base depending on the expansion of the plant operating range. Moreover, due to its ability to functionally represent the modes at each control interval from the combination of the modes obtained based on the developed rules; the scheme is shown to yield a Fault Tolerant Controller.
- For further reading
S. Kamalasadan, Adel A. Ghandakly, K. S. Al-Olimat, “A Fuzzy Multiple Reference Model Adaptive Controller Design”, International Journal of Fuzzy Systems, Vol.8, No.3, pp.165-172, September 2006. []
S. Kamalasadan, “An Adaptive Controller for Multimodal systems based on Fuzzy Multiple Reference Model Generator”, In Press, Special Issue on Soft Computing on Artificial Intelligence, Web and Data Mining, Machine Learning, Journal of Engineering Letters, March 2007. []