Active flatness control of membrane structures using adaptive genetic algorithm

Abstract

Membrane structures are attracting attention as excellent candidates for lightweight large space structures, which can be utilized to improve the performance and reduce the cost of space exploration and earth observation missions. Membrane structures can be stowed to a small volume during launch and function as large structures after deployed. For many applications, maintaining surface accuracy of membranes is extremely important to achieve satisfactory performance, especially for membrane antennas and adaptive optics. Active flatness control is a vital technology to maintain surface accuracy of membrane structures. In this research, multiple shape memory alloy (SMA) actuators around the boundary of a rectangular membrane are used to apply tension forces to membrane structures to compensate wrinkle effects. The dynamics of membrane structures is nonlinear and computationally expensive, hence unfeasible to be used in real-time active flatness control. As a parallel direct searching method, genetic algorithm (GA) is used search optimal tension force combination on a high dimensional nonlinear surface. Due to increasing number of tension forces to search, the convergence is more difficult to attain. In order to increase responsiveness and convergence of genetic algorithm, an adaptive genetic algorithm (AGA) is proposed. Adaptive rules are incorporated in a modified genetic algorithm to regulate control parameters of genetic algorithm. Through numerical simulation and experimental studies, it is demonstrated that AGA can expedite its search process and prevent premature convergence.