Control of transient flow in irrigation canals using Lyapunov fuzzy filter-based Gaussian regulator
An optimal fuzzy filter was applied to solve the state estimation problem of the controlled irrigation canals. Using linearized finite-difference model of the open-channel flow, a canal operation problem was formulated as an optimal control problem and an algorithm for gate openings in the presence of unknown external disturbances was derived. A fuzzy filter was designed to estimate the state variables at the intermediate nodes based upon measured values of depth at the points in the canal. A Lyapunov function was utilized as a performance index to formulate the fuzzy interference rules of the optimal fuzzy filter. A linear quadratic Gaussian (LQG) optimal controller for a multi-pool irrigation canal was considered as an example. The state estimation problem in the controller was simulated using two techniques: Kalman estimator and the proposed fuzzy filter. The performance of the fuzzy state estimator designed using the Lyapunov fuzzy technique was compared with the results obtained using the Kalman estimator technique. The obvious advantages of the fuzzy filter were the lower computational costs and ease of implementation. The results of this study demonstrated that proposed Lyapunov-type fuzzy filter provides both good stability and simplicity in the control of irrigation canals more than a Kalman filter. Copyright (c) 2005 John Wiley & Sons, Ltd.
open-channel flow kalman filter lyapunov fuzzy filter canal automation