Computationally Efficient Design of Semiactive Structural Control in the Presence of Measurement Noise

Designing control strategies for smart structures, such as those with semiactive devices, is complicated by the nonlinear nature of the feedback control, secondary clipping control, and other additional requirements such as device saturation. The authors have previously developed an approach for semiactive control system design, based on a nonlinear Volterra integral equation (NVIE) that provides a low-order computationally efficient simulation of such systems, for state feedback semiactive clipped-optimal control. This paper expands the applicability of the approach by demonstrating that it can also be adapted to accommodate more realistic cases when, instead of full-state feedback, only a limited set of noisy response measurements is available to the controller. This extension requires incorporating a Kalman filter estimator, which is linear, into the nominal model of the uncontrolled system. The efficacy of the approach is demonstrated by a numerical study of a 100-DOF frame model, excited by a filtered Gaussian random excitation, with noisy acceleration sensor measurements to determine the semiactive control commands. The results show that the proposed method can achieve more than two orders of magnitude improvement in computational efficiency while retaining a comparable level of accuracy.