A Novel Algorithm for Antenna Azimuth Position Control System

The robust control design approaches have seen limitations due to exact knowledge of system dynamics, system non-linearity, modeling of input/output disturbances, faulty or mistaken ignorance towards stochastic dynamics etc. Robust control design approaches such as linear quadratic regulator (LQR), linear quadratic Gaussian (LQG), H∞, Fuzzy etc. are proposed and implemented but, all these methods suffered under disturbances e.g., LQR requires constant gain at each state, LQG/Fuzzy suffers from external disturbances and H∞ suffers due to unstructured uncertainty. Revisiting all these approaches and in order to address the drawbacks a novel QFT approach has been devised under interval constraints using singular value decomposition-principle component analysis-Euclidian norm (SVD-PCA-NORM) termed as Laxmikant-Arvind (LA) criteria and is implemented for a real time application. Simulation is done in MATLAB environment. LA criteria avoid iterative SVD and uses PCA-NORM approach which ultimately eliminates inconsistent and unimportant values which are not part of the effective solution. The algorithm is used under stochastic environment but, with appropriate controller under appropriate condition.