H∞ Adaptive Learning Vibration Controller for Steel Offshore Platform with Random Control Delay and Structural Uncertainty Compensation

Abstract In this paper, an adaptive learning H∞ controller is proposed to attenuate the wave-wind-induced vibration of a jacket offshore platform with varying control delay and structured uncertainty. A novel scheme is proposed regarding bounded H∞ performance and nonlinear uncertainty approximation online, incorporated with adaptive and fixed parts respectively. The adaptive part is self-adjusting based on neural network updating laws, and the fixed part is derived through minimizing the generalized H∞ disturbance attenuation index. In the presented scheme, accurate values of real-time control delay and upper-bounds of uncertainties are not necessarily required. The stability of controller is proved by Lyapunov functions following the simulation results. Comparable experiments efficiently illustrate feasibility and vibration-attenuation effectiveness of the proposed approach in both shallow and deep water.