Adaptive Kalman Filtering with Exact Linearization and Decoupling Control on Three-Tank Process
This addresses water treatment and liquid storage control, but it is incremental as it builds on existing linear and nonlinear methods.
The paper tackled the problem of maintaining water levels in a three-tank hydraulic system by combining linearization and decoupling control to track dynamic references, achieving successful tracking and using an adaptive Kalman filter to predict the true nonlinear system with rewarding performance.
Water treatment and liquid storage are the two plants implementing the hydraulic three-tank system. Maintaining certain levels is the critical scenario so that the systems run as desired. To deal with, the optimal linear control and the complex advanced non-linear problem have been proposed to track certain dynamic reference. This paper studies those two using the combination of linearization and decoupling control under some assumptions. The result shows that the designed methods have successfully traced the dynamic reference signals. Beyond that, the adaptive system noise Kalman filter (AKF) algorithm is used to examine the estimation performance of the true non-linear system and the performance yields a rewarding prediction of the true system.