Model-free adaptive optimal controller design for aeroelastic system with input constraints

Abstract

In this thesis, an innovative model-free adaptive control strategy based on a multi-observer technique that takes advantage of input/output measurement data is proposed for the aeroelastic system of the two degree of freedom pitch-plunge wing, and this unknown complicated nonlinear system is a general multi-input multi-output plant with input constraints. In this algorithm, the multi-observer technique is applied to estimate the value of the pseudopartial derivative parameter matrix in the approach of the compact form dynamic linearization designed to linearize the model of the two-dimensional wing-flap system with input constraints. At the same time, this model-free adaptive control method consists of the approximate internal model and the optimal controller. Moreover, this control scheme is based on the linear matrix inequalities, which is a kind of real-time computation. In the design process for controlling this two-dimensional wing-flap system in the condition that the control inputs are subjected to amplitude and change rate limits, the problem of the dynamic control is transformed into the optimization problem, which can minimize the performance index. Finally, simulation results for the two-dimensional wing-flap system with input constraints can demonstrate the availability and potential of the presented multi-observer-based model-free optimal control strategy for unknown nonlinear multi-input multi-output system with input saturation.