Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/2186
Authors: Kumar, Yogesh
Issue Date: 2012
Abstract: The inverted pendulum is a classical control problem, which involves developing a control system to balance a pendulum. The aim of this study is to stabilize the Inverted Pendulum such that the position of the cart on the track is controlled quickly and accurately so that the pendulum is always erected in its inverted position during such movements. This thesis presents a methodology to design optimized and robust controllers for stabilization of non-linear IP (Inverted Pendulum) system. LQR is one of best controller for linear system. To design best controller for nonlinear best controller for linear system is used. Initially LQR controller is designed for linearized model of IP. Then Parameters of LQR are optimized to obtain best performance out of it. Fusion based fuzzy logic controller, Single input fuzzy logic controller and ANFIS controller is designed with parameters and data of optimized LQR controller. The proposed controllers not only give equivalent performance under no-disturbance condition, but are more robust than LQR controller. Experiments are carried out in MATLAB Simulink to demonstrate the performance of the proposed controllers. The design procedure is conceptually simple and natural. In this design procedure first LQR controller is designed and is optimized using genetic algorithm. Now training data is taken from this optimized controller, with which ANFIS controller is tuned. And in another controller four input variables are scaled by normalized gain matrix K of LQR and are then fused using sensory fusion technique to obtain FFLC controller. Then further work is carried out to reduce the numbers input variables from two to one, by using signed distance method. Systems are simulated in the presence of disturbance and are then compared with each other to find out best controller which gives optimum overshoot and settling time under disturbance condition.
Other Identifiers: M.Tech
Research Supervisor/ Guide: Mitra, R.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (E & C)

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