MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL
Constrained stable generalised predictive control (CSGPC) provides a means for handling constraints within the predictive control context and has guaranteed stability properties. However, to guarantee stability, an assumption concerning the feasibility of making the output reach its set-point over a...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
IEE
1995
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| Summary: | Constrained stable generalised predictive control (CSGPC) provides a means for handling constraints within the predictive control context and has guaranteed stability properties. However, to guarantee stability, an assumption concerning the feasibility of making the output reach its set-point over a finite horizon is required. If the performance objective is changed from a two-norm of the predicted errors to an infinity-norm, then the finite horizon feasibility assumption is not needed to guarantee stability. As might be expected, though, performance under an infinity-norm objective is often not as good. Here we propose an algorithm which overcomes these difficulties by mixing the two- and infinity-norm objectives. |
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