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Identification and Control of a Triga Mark III Reactor Using Adaptive Fuzzy Control Systems
Erick Rojas-Ramirez, Jorge S. Benitez-Read and J. Armando Segovia-De Los Rios

An innovative approach to identify and control the power of a TRIGA-type reactor using adaptive fuzzy systems is presented. In the identification process, the learning method uses Particle Swarm Optimization (PSO) and Recursive Least Mean Square (RLSE) to update the antecedents and consequents of a Sugeno system identification scheme. On the other hand, a stable adaptive fuzzy control technique is used to regulate the power reactor. The waveform of the reference power profile is devised in such manner that the reactor period parameter is maintained above the lower safety limit value at all times. Lyapunov stability theory is used to adjust the free parameters of the fuzzy system that controls the reactor power. The results show the feasibility of using this approach as a new technique to identify and regulate the power in a TRIGA-type research nuclear reactor.

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