Abstract
Within the framework of probabilistic description, the probabilistic robust optimization(PRO) method has been developed for parametric uncertain systems by replacing the conventional hard bounds with the soft bounds. The parameter space has been regarded as an entirety with probabilistic weighted performances as the optimization performance. Simulation results demonstrate the advantage of the new method over the conventional approaches as it takes all parametric perturbations into account.
Original language | English |
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Title of host publication | Information Intelligence and Systems |
Place of Publication | Beijing |
Pages | 2205-2209 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 1996 |
Event | IEEE International Conference on Systems, Man and Cybernetics - Beijing, China Duration: 14 Oct 1996 → 17 Oct 1996 |
Conference
Conference | IEEE International Conference on Systems, Man and Cybernetics |
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Country/Territory | China |
City | Beijing |
Period | 14/10/96 → 17/10/96 |
Keywords
- performance trade-offs
- probabilistic robust optimization (PRO)
- soft-bound description
- parametric uncertainty
- probabilistic weighting