An automatic control system for large-scale systems that integrates methods in artificial intelligence, signal processing, and nonlinear control to provide fast and efficient diagnostics and reliable control is presented. The integrated system reduces the procedural load and facilitates the operator tasks by creating a condensed representation of plant status. Operator tasks are emulated by building computer-based algorithms which validate sensor signals, strategies, commands, and performance tracking and which generate reliable decisions and control actions. The advanced concepts on which the system is based are discussed. Also discussed are fault tolerance, signal and command validation, nonlinear control, and the system executive module. An application of the integrated control system to the Experimental Breeder Reactor-II (EBR-II) is described. The simulation results show that the advanced concepts yield efficient control strategies, including reactor control during startup.>
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Berkan et al. (1991) studied this question.
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