Mrs. Armita Fatemi Moghadam, Dr. Arash Sharifi, Dr. Mohammad Teshnelab,
Volume 5, Issue 2 (9-2011)
Abstract
Due to the status of Rotary Kiln Cements (RKCs) in different industries and lack of a mature model for these systems, identification and prediction of the Kiln system are necessary for any simulation and automation approaches. Intrinsically, RKCs are non-linear and time-variant systems. This paper proposes a novel approach of using ANSFI to predict the status of a RKC system in a scale of few minutes in advance. Since the data used in this research has been extracted from a real system, pre-analysis of data is one of the critical parts of identification process. In addition to the system inputs, dynamic of the system which has been selected according to the LIPSCHITZ method with a system’s genuine delay are applied as inputs for Neural Network system with one step phase lag. Genetic algorithm has been utilized as a characteristic selection and phasor rules reduction method due to the existing challenges on the number of rules in phasor systems specifically with a large number of variables to be applied to the Neural Network. To verify the performance of the proposed identification and prediction method on a non-linear industrial system, simulation results have been carried out on a real data extracted from SAVEH Cement Company
Mojtaba Hadi Barhaghtalab, Vahid Meigoli, Valiollah Ghaffari,
Volume 13, Issue 3 (12-2019)
Abstract
In this paper, an ANFIS+PID hybrid control policy has been addressed to control a 6-degree-of freedom (6-DOF) robotic manipulator. Then its error convergence has been also evaluated. The ability to formulate and estimate the system uncertainties and disturbances along with system dynamics and rejecting the disturbances effect are some advantages of the proposed method in comparing with the conventional ANFIS structures. The error convergence could not be proved in the ordinary ANFIS structures. But in the proposed method, the error convergence of the robot manipulator can be established under considering some mathematical conditions. The proposed control law is realized via parallel combination of ordinary ANFIS network and PID controller. The suggested method has been successfully applied in a 6-DOF robot manipulator system. Furthermore, in presence of uncertainties and external disturbances error convergence would be justified using the Lyapunov-like theorem and Barbalat lemma.
