A QFT/EEAS Design of Multivariable Robust Adaptive Controllers

This paper presents a robust adaptive control design methodology for multi-input multi-output (MIMO) plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive System (EEAS), both of which are the novel ideas of Horowitz. Self Oscillating Adaptive Systems (SOAS) are proposed to mainly overcome the problem of large gain variations, which is important in certain applications. To further improve the SOAS design, the idea of EEAS was developed. Finally, combined QFT and EEAS proposed a robust adaptive controller for SISO uncertain plants. However, due to the complex design nature of the proposed combined methodology and the difficulty of an optimal design, this line of Horowitz’s research was not followed further. In this paper, to overcome the above mentioned problems the design procedure is reformulated as a set of cost functions and constraints. Genetic Algorithms are then used to solve the optimal design. Also, QFT/EEAS design is extended to multivariable uncertain plants. Sufficient conditions are derived to assure the achievement of given offdiagonal performance. Then, the given main channel performance could be achieved by using SISO QFT/EEAS method. Simulation studies indicate the effective performance of the proposed QFT/EEAS MIMO design methodology. It is shown that the proposed approach can handle large plant parameter uncertainties with lower loop bandwidths.