A case study in intelligent vs. conventional control for a process control experiment

Zumberge, Jon; Passino, K.M.

doi:10.1016/s0967-0661(98)00067-7

Cited by 26 publications

(9 citation statements)

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“…One of the most successful expert system techniques applied to a wide range of control applications has been the Fuzzy Set Theory, which has made possible the establishment of "intelligent control". The fuzzy approach provides a good support for translating the heuristic skilled operator's knowledge about the process and control procedures expressed in imprecise linguistic sentences into numerical algorithms, [16], [18], [19], [21], [23], [24], [25], [26], [27], [28].…”

Section: Manual Tuning Methodsmentioning

confidence: 99%

Robotics Controller: A Literature Survey

Badoni¹

2015

IJERT

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Section: Manual Tuning Methodsmentioning

confidence: 99%

Robotics Controller: A Literature Survey

Badoni¹

2015

IJERT

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“…Intelligent controls including fuzzy logic (FL) [5][6], neural network (NN) control [7][8], and genetic algorithms (GA) [9] have also been applied to the coupled tanks system. Zumberge and Passino [10] have reported the comparison between conventional control and intelligent control applied to the process control. The controller must have the capability to adapt to changes in plant dynamics.…”

Section: Introductionmentioning

confidence: 99%

“…One of the most effective ways to solve the control problem is to use the technique of intelligent control system or hybrid technology of the conventional and intelligent control techniques. Fuzzy logic controller is one of the intelligent controllers and is a logical model of the human behavior of the process operator [10]. The fuzzy controller gives the better performance than those of the conventional controllers in terms of settling time, response time, overshoot and robustness.…”

Section: Introductionmentioning

confidence: 99%

A novel fuzzy based adaptive control of the four tank system

Prusty

Pati

Mahapatra

2015

Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)

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The paper has analyzed the four tank system (FTS) from the mechanism modeling and has also established the nonlinear and linear mathematical model. The FTS is a typical control system with nonlinear, coupling and time delay characteristics which can be used to test the applications of different control algorithms on complex systems. The aim of the process is to keep the liquid level in the tanks at the desired values. Here, Fuzzy Modified Model Reference Adaptive Control (FMMRAC) is proposed and is applied to the tank system to test its effectiveness. The response of the FMMRAC controller is verified and is compared with other control algorithms through simulation. The performance of the closed loop system is simulated using LabVIEW software. The method used here is validated using the simulated results.

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“…However, the conventional controllers need to be retuned if the operating range is changed or any disturbances are taking placed. Further the conventional controller may not provide better performance for the non-linear with dead time industrial process (Zumberge and Passino, 1998;Rajan and Nikil, 1999;Abdennour, 2000;Er and Sun, 2001;Abd El-Geliel and El-Khazendar, 2003). Recently, fuzzy logic controllers (FLCs) are preferred for various industrial processes because of its robustness, and performance is less sensitive to parametric variations.…”

Section: Introductionmentioning

confidence: 99%

A simple self-tuning scheme using fuzzy logic for a non-linear pressure regulating system

Kanagaraj

Sivashanmugam

Paramasivam³

2010

IJAAC

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A self-tuning control scheme using fuzzy logic has been studied for a pilot pressure regulating system. In this hierarchical control technique, a rulebase supervisory fuzzy system is designed to tune the input scaling factor (SF) of a direct fuzzy system according to the process condition. The proposed controller design concentrates more on improving the robustness and stability of the controller during process disturbances and changes in operating level. The proposed control scheme is implemented in an ARM7 microcontroller based embedded target board to study its applicability for real time pressure control application. The performance of the developed control scheme is compared with classical fuzzy controller under different operating level and process disturbance. Results show that the proposed self-tuning fuzzy controller outperforms the conventional method for pressure regulation.Reference to this paper should be made as follows: Kanagaraj, N., Sivashanmugam, P. and Paramasivam, S. (2010) 'A simple self-tuning scheme using fuzzy logic for a non-linear pressure regulating system', Int. He is also a Reviewer for many IEEE journals, Acta Press, Inderscience journals, Elsevier journals, Hindwai journals and IEEE conferences. His interests include power electronics, AC motor drives, DSP-and FPGA-based motor controls, powerfactor correction, magnetic design, fuzzy logic, neural networks and controller design for wind energy conversion systems.

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A case study in intelligent vs. conventional control for a process control experiment

Cited by 26 publications

References 0 publications

Robotics Controller: A Literature Survey

Robotics Controller: A Literature Survey

A novel fuzzy based adaptive control of the four tank system

A simple self-tuning scheme using fuzzy logic for a non-linear pressure regulating system

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