An Optimal Input Design for Online Aircraft Parameter Estimation and Its Application to Fault Tolerant Control

Abstract

In this dissertation, an optimal input design methodology is proposed for online parameter estimation of an aircraft with multiple control surfaces. To design the optimal input, a mathematical model for high performance aircraft with multiple control surfaces is developed. Using the developed mathematical model, the optimum input for parameter estimation is then designed to minimize the estimation error-variance of the parameters. The optimal input consists of multiple simultaneous orthogonal inputs that make the parameter estimation efficient. During the optimization process, input constraint is considered to prevent large input energy consumption, and the output constraint is considered to prevent aircraft divergence. These constraints are based on the military standard, MIL-F-8785C, the flying qualities of a piloted airplane. The accuracy of the parameter estimation result using the optimal input is compared with that of the parameter estimation using conventional doublet and 3211 inputs. Two online parameter estimation schemes are considered to evaluate the performance of the designed optimal input: a Bayesian method for the time domain and an equation-error method for the frequency domain. The recursive formula for the Bayesian method is also derived. Numerical simulation is conducted and the performance, convergence, and accuracy of the parameter estimation method using three different input types are compared. Using the optimal inputs, accuracy and convergence rate are improved for the online parameter estimation methods in both the time and frequency domains. The proposed online parameter estimation scheme is applied for indirect fault tolerant control of the aircraft with control surface damage case. The simulation result shows that the proposed online parameter estimation schemes could be also used in a various reconfigurable flight control law.