ASSESSING CONTROL STRATEGIES FOR THE SUPERCRITICAL EXTRACTION FROM COFFEE BEANS: PROCESS-BASED CONTROL VERSUS PROPORTIONAL INTEGRAL DERIVATIVE

The significant challenges seen with the mathematical modeling and control of spatial parallel manipulators are its difficulty in the kinematic formulation and the inability to real-time control. The analytical approaches for the determination of the kinematic solutions are computationally expensive. This is due to the passive joints, solvability issues with non-linear equations, and inherent kinematic constraints within the manipulator architecture. Therefore, this article concentrates on an artificial neural network–based system identification approach to resolve the complexities of mathematical formulations. Moreover, the low computation time with neural networks adds up to its advantage of real-time control. Besides, this article compares the performance of a constant gain proportional–integral–derivative (PID), variable gain proportional–integral–derivative, model predictive controller, and a cascade controller with combined variable proportional–integral–derivative and model predictive controller for real-time tracking of the end-effector. The control strategies are simulated on the Simulink model of a 6-degree-of-freedom 3-PPSS (P—prismatic; S—spherical) parallel manipulator. The simulation and real-time experiments performed on the fabricated manipulator prototype indicate that the proposed cascade controller with position and velocity compensation is an appropriate method for accurate tracking along the desired path. Also, training the network using the experimentally generated data set incorporates the mechanical joint approximations and link deformities present in the fabricated model into the predicted results. In addition, this article showcases the application of Euler–Lagrangian formalism on the 3-PPSS parallel manipulator for its dynamic model incorporating the system constraints. The Lagrangian multipliers include the influence of the constraint forces acting on the manipulator platform. For completeness, the analytical model results have been verified using ADAMS for a pre-defined end-effector trajectory.

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Optimized Proportional-Integral-Derivative Control Strategies and Simulation for Lower Limb Functional Electrical Stimulation

2011 Fourth International Conference on Information and Computing ◽

10.1109/icic.2011.91 ◽

2011 ◽

Cited By ~ 1

Author(s):

Gu Chengwei ◽

Jun Qian

Keyword(s):

Electrical Stimulation ◽

Functional Electrical Stimulation ◽

Lower Limb ◽

Control Strategies ◽

Proportional Integral Derivative ◽

Proportional Integral ◽

Proportional Integral Derivative Control ◽

Derivative Control

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Position control and performance analysis of hydraulic system using two pump-controlling strategies

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651818813233 ◽

2018 ◽

Vol 233 (9) ◽

pp. 1093-1105 ◽

Cited By ~ 1

Author(s):

Gyan Wrat ◽

Prabhat Ranjan ◽

Mohit Bhola ◽

Santosh Kumar Mishra ◽

J Das

Keyword(s):

Control Strategy ◽

Position Control ◽

Control Strategies ◽

Speed Control ◽

Hydraulic Systems ◽

Proportional Integral Derivative ◽

Proportional Integral Derivative Controller ◽

Proportional Integral ◽

Actuation System ◽

Swash Plate

The role of hydraulic systems is quite evident especially in the case of heavy machineries employed in industries, where the utilisation of high forces amid large stiffness is the prerequisite. Nevertheless, there has been substantial effort put forward in the development of advanced control strategies which finally addressed the issue of the position control. Proportional–integral–derivative control strategy happens to be one among them, which is a versatile and widely renowned approach involved in the position control in this study. Although, it is quite frequently observed that the hydraulic actuation system possesses strong nonlinearities. In this article, two different actuator position control strategies, that is, swash plate control of main pump and speed control strategy of prime mover are compared. In swash plate control strategy, the proportional–integral–derivative controller adjusts the swash plate of main pump through servo mechanism, whereas in the speed control strategy, the proportional–integral–derivative controller adjusts the speed of the electric motor through variable-frequency drive. For this purpose, two MATLAB-Simulink models are developed and validated experimentally. It is found that swash plate control strategy has better dynamic and control performance than the speed control strategy catering same position demand of the linear actuator.

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Ziegler-Nichols Based Proportional-Integral-Derivative Controller for a Line Tracking Robot

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v9.i1.pp221-226 ◽

2018 ◽

Vol 9 (1) ◽

pp. 221 ◽

Cited By ~ 2

Author(s):

Kim Seng Chia

Keyword(s):

Pid Controller ◽

Control Strategies ◽

Tracking Task ◽

Pid Controllers ◽

Proportional Integral Derivative ◽

Proportional Integral ◽

Pid Algorithm ◽

Tracking Process ◽

Line Tracking ◽

Proportional Controller

Line tracking robots have been widely implemented in various applications. Among various control strategies, a proportional-integral-derivative (PID) algorithm has been widely proposed to optimize the performance of a line tracking robot. However, the motivation of using a PID controller, instead of a proportional (P) or a proportional-integral (PI) controller, in a line tracking task has seldom been discussed. Particularly, the use of a systematic tuning approach e.g. closed loop Ziegler Nichols rule to optimize the parameters of a PID controller has rarely been investigated. Thus, this paper investigates the performance of P, PI, and PID controllers in a line tracking task, and the ability of Ziegler Nichols rule to optimize the parameters of the P, PI, and PID controllers. First, the ultimate gain value, Ku and ultimate period of oscillation, Pu were estimated using a proposed approach. Second, the values of KP, KI and KD were estimated using the Ziegler Nichols formulae. The performance of a differential wheeled robot in the line tracking task was evaluated using three different speeds. Results indicate that the Ziegler Nichols rule coupled with the proposed method is able to identify the parameters of the P, PI, and PID controllers systematically in the line tracking task. Findings indicate that the mobile robot coupled with a proportional controller achieved the best performance compared to PI and PID controllers in the line tracking process when the estimated initial parameters were used.

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Design and analysis of a Proportional-Integral-Derivative controller with biological molecules

10.1101/303545 ◽

2018 ◽

Cited By ~ 4

Author(s):

Michael Chevalier ◽

Mariana Gómez-Schiavon ◽

Andrew Ng ◽

Hana El-Samad

Keyword(s):

Steady State ◽

Feedback Control ◽

Pid Control ◽

De Novo ◽

Control Strategies ◽

Biological Molecules ◽

Proportional Integral Derivative ◽

Integral Control ◽

Proportional Integral Derivative Controller ◽

Proportional Integral

SummaryThe ability of cells to regulate their function through feedback control is a fundamental underpinning of life. The capability to engineer de novo feedback control with biological molecules is ushering in an era of robust functionality for many applications in biotechnology and medicine. To fulfill their potential, feedback control strategies implemented with biological molecules need to be generalizable, modular and operationally predictable. Proportional-Integral-Derivative (PID) control fulfills this role for technological systems and is a commonly used strategy in engineering. Integral feedback control allows a system to return to an invariant steady-state value after step disturbances, hence enabling its robust operation. Proportional and derivative feedback control used with integral control help sculpt the dynamics of the return to steady-state following perturbation. Recently, a biomolecular implementation of integral control was proposed based on an antithetic motif in which two molecules interact stoichiometrically to annihilate each other’s function. In this work, we report how proportional and derivative implementations can be layered on top of this integral architecture to achieve a biochemical PID control design. We illustrate through computational and analytical treatments that the addition of proportional and derivative control improves performance, and discuss practical biomolecular implementations of these control strategies.

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Development of Proportional–Integral–Derivative and Fuzzy Control Strategies for Navigation in Agricultural Environments

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4038504 ◽

2017 ◽

Vol 140 (6) ◽

Cited By ~ 1

Author(s):

Stephanie Bonadies ◽

Neal Smith ◽

Nathan Niewoehner ◽

Andrew S. Lee ◽

Alan M. Lefcourt ◽

...

Keyword(s):

Fuzzy Logic ◽

Food Quality ◽

Pid Controller ◽

Fuzzy Logic Controller ◽

Control Strategies ◽

Working Hours ◽

Quality And Safety ◽

Proportional Integral Derivative ◽

Proportional Integral ◽

Food Quality And Safety

Farming and agriculture is an area that may benefit from improved use of automation in order to increase working hours and improve food quality and safety. In this paper, a commercial robot was purchased and modified, and crop row navigational software was developed to allow the ground-based robot to autonomously navigate a crop row setting. A proportional–integral–derivative (PID) controller and a fuzzy logic controller were developed to compare the efficacy of each controller based on which controller navigated the crop row more reliably. Results of the testing indicate that both controllers perform well, with some differences depending on the scenario.

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Composite disturbance rejection control for hydraulic classification

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331217693917 ◽

2017 ◽

Vol 40 (6) ◽

pp. 1863-1872

Author(s):

Dan Niu ◽

Xisong Chen ◽

Xiaojun Wang ◽

Xingpeng Zhou

Keyword(s):

Disturbance Rejection ◽

Disturbance Observer ◽

Control Strategies ◽

Water Pressure ◽

Feedback Regulation ◽

Disturbance Attenuation ◽

Proportional Integral Derivative ◽

Large Coupling ◽

Proportional Integral ◽

Hydraulic Classification

In the hydraulic classification, precise control for the flow rate of overflow water is vital to guarantee the uniformity and stability of the powder product size. Usually the multiple overflow tanks are supplied by a shared overflow pipeline, which gives rise to large coupling effects in the controls for the flow rates of multiple overflow tanks simultaneously. To solve this issue, it is necessary to keep the water pressure in the shared overflow pipeline accurately constant, which is not easy due to strong disturbances. Several control strategies have been proposed to control the constant water pressure. However, most of them (such as proportional-integral-derivative and model predictive control) reject disturbances just through feedback regulation and do not reject disturbances directly. This may cause poor control performances in the presence of strong disturbances. For improving the disturbance rejection performance, a control scheme based on proportional-integral-derivatives and disturbance observer is put forward in this paper. The scheme employs disturbance observer as feedforward compensation and a proportional-integral-derivative controller as feedback regulation. The disturbance rejection properties under both model mismatches and external disturbances are discussed. The test results illustrate that the proposed method can remarkably improve the disturbance attenuation property compared with the conventional proportional-integral-derivative method in the hydraulic classification process.

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Adaptive fractional order fuzzy proportional–integral–derivative control of smart base-isolated structures equipped with magnetorheological dampers

Journal of Intelligent Material Systems and Structures ◽

10.1177/1045389x17721046 ◽

2017 ◽

Vol 29 (5) ◽

pp. 830-844 ◽

Cited By ~ 11

Author(s):

Abbas-Ali Zamani ◽

Saeed Tavakoli ◽

Sadegh Etedali ◽

Jafar Sadeghi

Keyword(s):

Active Control ◽

Fractional Order ◽

Control Strategies ◽

Near Field ◽

Magnetorheological Damper ◽

Proportional Integral Derivative ◽

Isolation System ◽

Proportional Integral Derivative Controller ◽

Proportional Integral ◽

Multi Objective

The current semi-active or even active control strategies have been developed to address a few drawbacks, such as unwanted large displacements created at the base level and system deficiency in adaptation to different types of seismic excitations, in the base isolation systems. In this article, two control strategies, multi-objective modified clipped optimal and adaptive fractional order fuzzy proportional–integral–derivative, are proposed for semi-active control of a smart base-isolated structure equipped with a magnetorheological damper. The main objective is to reduce the displacement of isolation system without allowing significant increase in the acceleration of superstructure for both far-field and near-field earthquake excitations. Using proper fitness functions, the weighting matrices of the multi-objective modified clipped optimal controller are tuned using multi-objective optimization. Then, the parameters of the fractional order fuzzy proportional–integral–derivative controller are obtained. Next, the fuzzy rule weights of the fractional order fuzzy proportional–integral–derivative controller are updated online based on the values of ground motion and structural responses using an adaptive strategy. For comparison, two control cases in which the magnetorheological damper is in passive mode, passive-off and passive-on, are considered. Numerical simulations show that the proposed adaptive fractional order fuzzy proportional–integral–derivative controller better mitigates the seismic responses of a base-isolated structure excited by a range of real-data earthquakes.

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