This paper presents a novel iterative learning sliding mode controller (ILSMC) that can be applied to the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs) subject to model uncertainties and external disturbances. Here, the proposed ILSMC is integrated in the outer loop of a controlled system. The control development, conducted in the discrete-time domain, does not require a priori information of the disturbance bound as with conventional SMC techniques. It only involves an equivalent control term for the desired dynamics in the closed loop and an iterative learning term to drive the system state toward the sliding surface to maintain robust performance. By learning from previous iterations, the ILSMC can yield very accurate tracking performance when a sliding mode is induced without control chattering. The design is then applied to the attitude control of a 3DR Solo UAV with a built-in PID controller. The simulation results and experimental validation with real-time data demonstrate the advantages of the proposed control scheme over existing techniques.
Due to high nonlinearity with features of large time constants, delays, and interaction among variables, control of the wastewater treatment plants (WWTPs) is a very challenging task. Modern control strategies such as model predictive controllers or artificial neural networks can be used to deal with the non-linearity. Another characteristic of this system should be considered is that it works repetitively. Iterative learning control (ILC) is a potential candidate for such a demanding task. This paper proposes a method using ILC for WWTPs to achieve new results. By exploiting data from the previous iterations, the learning control algorithm can improve gradually tracking control performance for the next runs, and hence outperforms conventional control approaches such as feedback controller and model predictive control (MPC). The benchmark simulation model No.1-BSM1 has been used as a standard for performance assessment and evaluation of the control strategy. Control of the Dissolved Oxygen in the aerated reactors has been performed using the PD-type ILC algorithms. The obtained results show the advantages of ILC over a classical PI control concerning the control quality indexes, IEA and ISE, of the system. Besides, the conventional feedback regulator is designed in a combination with the iterative learning control to deal with uncertainty. Simulation results demonstrate the potential benefits of the proposed method.
This paper proposes a hybrid control system integrating a PID controller and a fuzzy logic controller, using the particle swarm optimization (PSO) algorithm to optimize control parameters. The control object is an excitation system for a large synchronous motor, which is widely used in large power transmission systems. In practice, the change in load and excitation source can affect the operating mode of the motor. Therefore, a hybrid controller is designed to stabilize the power factor, resulting in better working performance. In the control algorithm, a PID controller is initially designed using PSO to optimize the control coefficients. The FLC-Sugeno control is then integrated with the PID, in which PSO is utilized to optimize membership functions. Numerical simulation results demonstrate the advantages of the proposed approach. Doi: 10.28991/ESJ-2022-06-02-01 Full Text: PDF
Butter is one of the oldest forms of preserving fat components of milk. Its manufacture dates back to some of the earliest historical records. The evolution of the art of buttermaking has been associated with the development and use of equipment. The construction of creaming and buttermaking equipment in the eighteenth century led to the appearance of the barrel churn. Creaming was at first done by a method called shallow pan. This was followed by a deep‐setting system. This shortened process time and produced a better quality cream. In 1879, cream separators for fully continuous operation were produced. The Babcock test assisted in the development of the butter industry. This test determines the percentage of fat in milk and cream. Other developments included the use of pasteurization, the use of pure cultures of lactic acid and bacteria, and the use of refrigeration. Multiple butterfat products include butter oils, anhydrous butterfat, butterfat–vegetable oils, and fractionated butterfats. Preservation of butterfat today involves the processing of butterfat to anhydrous butter oil. Shelf life is improved because the butter oil is hermetically packaged under nitrogen. Recent times have seen a decline in the consumption of butter but this situation is being somewhat reversed more recently. This decline contradicts all historical patterns for butterfat consumption. Reasons for decline are noted. This article provides data on chemical composition, marketing, technology, processing, quality, legal restrictions, and uses.
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