Artificial Intelligence Based Synthesis of Semiactive Suspension Systems

This paper is concerned with the synthesis of control laws for semiactive suspension systems employing artificial intelligence. A review is made of a simple, 2-degree-of-freedom, quarter car model with passive, active, and semiactive control. An active linear quadratic Gaussian controller and a semiactive, balance logic derived controller are then used to develop two artificial intelligence based controllers-a semiactive neurocontroller and a semiactive fuzzy logic controller. This paper focuses on the advancement of balance semiactive logic using variable dry friction and the development of fuzzy semiactive controllers. The concerns in view are twofold: the reduction in cost of the control system and the antichattering nature of the logic. The development is from an engineering perspective and attempts to reduce the well-known schism between theoreticians and users of feedback control.

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