Intelligent knowledge-based control of multivariable plants

The architecturally relevant issues which arise in the development of expert proportional-integral controllers for multivariable plants are discussed, and the technical issues of representing the appropriate knowledge and using it effectively are addressed. It is shown that, by incorporating both nonrecursive identifiers and multivariable expert tuners in multivariable digital proportional-plus-integral control laws. highly effective digital set-point tracking controllers can be readily designed for multivariable plants. The effectiveness of the resulting general design methodology is illustrated an adaptive controller fold a two-input, two-output laboratory jet-engine model