Sliding Mode Fuzzy control-Theory and Verification on a Benchmark Structure

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration reduction of large structures. The rule base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the non-linear control algorithms. In general, fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation, and the non-linearity of the control rule makes the controller more effective than linear controllers. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator–structure interaction, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as Hmixed 2/∞, optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is efficient and attractive, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient. Copyright © 2000 John Wiley & Sons, Ltd.

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