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Item type:Publication, Adaptive Smith predictor controller design for industrial processes with time-varying time delay(Elsevier B.V., 2024-01-01)The design of an adaptive Smith predictor controller for control of industrial hydraulic processes subjected to the simultaneous effect of load disturbances and time-varying time-delay is developed in this paper. In order to improve the performance of the Smith predictor, an adaptive block is introduced into the control structure to estimate and update the current value of the time-varying time-delay. Furthermore, a disturbance compensator is introduced to reject the effect of load disturbances. Simulations of the control system are carried out with the proposed controller and with a classical Smith predictor. The comparison of the obtained results shows the higher performance of our proposed controller, both in rejecting load disturbances and in maintaining the closed-loop stability when the time-delay is time-varying. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhanced leakage detection and estimation via a hybrid genetic algorithm and high-order sliding modes observer approach(Institute of Electrical and Electronics Engineers Inc., 2024-01-01)This paper introduces a hybrid approach designed for both detecting and estimating the magnitude of leaks in oil pipelines. The method integrates a High Order Sliding Mode Observer(HOSMO) with a Super Twisting Algorithm to serve as an observer for state estimation of the system. A parameterized model based on momentum and mass balance equations with discretization is used, where the parameters are the location and magnitude of the leakage. To find these parameters, it incorporates the Genetic Algorithm to solve an optimization problem that relies on a function cost related to the error norm between measurements and states estimation from HOSMO in order to measure the difference between the model with an assumed leakage and the real leakage. The solution of the minimization problem represents the leak position and magnitude. The feasibility and effectiveness of this method are evaluated using a simulation model representing a 306 km sector of the North-Peruvian Oil Pipeline. The results demonstrate its robustness against noise, showcasing a precision of ±250 m in pinpointing the location of leaks.