Design and Research Based on Fuzzy PID-Parameters Self-Tuning Controller with MATLAB

Wang, Xiaokan; Sun, Zhiyong; WangLei,; Dong-qing, Feng

doi:10.1109/icacte.2008.9

Cited by 22 publications

(9 citation statements)

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“…However, the main problem of the PID controller is the tuning parameters for higher perfect characters. Over the past years, many tuning methods such as optimal PSO [34], fuzzy tuning [35] and model-based optimal method [36,37] were developed. For a grouting system, the maximum pressure must be controlled dynamically.…”

Section: A Robust Tuning Methods Of the Pid Parameters Based On The Bpmentioning

confidence: 99%

A robust controlling methodology for a grouting process

Zhang

Guo

2019

Automatika

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The grouting technology is an effective and economic method in the grouting industry field. In this paper, a nonlinear model for the grouting dynamic process was established, and the controlling parameters were further modified through a robust method. Moreover, the grouting pressure system for the neural network was also modelled based on a sensitivity analysis algorithm, and in particular, the iterative learning algorithm and Lyapunov asymptotical theory. The results showed that such a robust controlling methodology was better than the normal manual operation method. The subsequent numerical simulations demonstrated that the tuning methodology could meet all the requirements for the grouting control with the maximum pressure variable in the range of 8.1%. The present study and the proposed method could be applied to various engineering projects and especially, to implement in the real control of damming grouting.

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Section: A Robust Tuning Methods Of the Pid Parameters Based On The Bpmentioning

confidence: 99%

A robust controlling methodology for a grouting process

Zhang

Guo

2019

Automatika

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“…27 However, the key problem of PID controller is the tuning parameters for higher perfect character. In the last years, many tuning methods such as optimal PSO, 28 fuzzy tuning, 29 and model-based optimal method. 30 On the grouting pressure control system, the maximum pressure must be controlled dynamically.…”

Section: Robust Tuning Methods Of the Pid Parameters Based On Bp Modelmentioning

confidence: 99%

A self-learning propotional–integral–derivative control of grouting pressure using the back-propagation model

Hou

Chen

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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For the security of grouting process of dam foundation, grouting pressure control is one of the most important problems. In order to avoid dangerous grouting pressure fluctuation and improve the control precision, a feedback propotional–integral–derivative control method was presented for the whole grouting system. Because the grouting pressure is affected by many factors such as grouting flow, grouts density, and geological conditions, the parameters of propotional–integral–derivative must be tuned. In this article, the adaptive tuning method is presented. The back-propagation artificial neural networks model was proposed to simulate the grouting control process, and sensitivity analysis algorithm based on orthogonal test method was adopted for the selection of input variables. To obtain the optimal propotional–integral–derivative parameters, an iteration algorithm was used in each sampling interval time and the discrete Lyapunov function of the tracking error. The simulation results showed that self-learning propotional–integral–derivative tuning was robust and effective for the realization of the automatic control device in the grouting process.

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“…There are two common approaches, for the finetuning of the PID gains as represented in [35 -37]. While the authors in [35,36] proposed the modifying method of the PID gains with a single parameter, the others in [37] used expert systems, which control ΔK p , ΔK i , ΔK d independently. In this work, the second approach is used because that has more degree of freedom in controlling parameters.…”

Section: The Self-tuning Fuzzy Pid Controllermentioning

confidence: 99%

Vision Based Autonomous Path/Line Following of a Mobile Robot Using a Hybrid Fuzzy PID Controller

Thuy¹,

Cường²

2016

Tuyển Tập Công Trình HNKH Toàn Quốc Lần Thứ 3 Về Điều Khiển &Amp; Tự Động Hoá VCCA - 2015

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Hội nghị toàn quốc lần thứ 3 về Điều khiển và Tự động hoá -VCCA-2015 VCCA-2015Rôbốt di động bám quỹ đạo tự động dựa trên xử lý ảnh sử dụng bộ điều khiển lai PID-mờ Tóm tắtTrong bài báo này, chúng tôi đề xuất một phương pháp điều khiển cho robốt tự hành để bám quỹ đạo cho trước trong môi trường trong nhà. Để bám được theo quỹ đạo, các kỹ thuật sử dụng logíc mờ với thông tin đầu vào từ hệ thống xử lý ảnh đã được nghiên cứu và áp dụng. Phương pháp điều khiển sử dụng trong hệ thống là sự kết hợp giữa bộ điều khiển lái -bộ điều khiển lai PID-mờ, và bộ điều khiển vận tốc tuyến tính -bộ điều khiển mờ. Để khẳng định tính đúng đắn của giải thuật điều khiển, chúng tôi đã tiến hành thử nghiệm trên một robốt tự hành, robốt thiết kế dựa trên cơ sở các linh kiện sẵn có trên thị trường. Thử nghiệm chỉ ra rằng, robốt sử dụng giải thuật chúng tôi đề xuất bám tốt theo quỹ đạo cho trước -bao gồm cả quỹ đạo cong và quỹ đạo thẳng. Từ khóa: Hệ thống điều khiển, robốt tự hành, hệ thống xử lý ảnh, logíc mờ, bộ điều khiển lái, bộ điều khiển tốc độ. AbstractIn this work, we propose a method for autonomous path/line following of differential-drive wheeled robot to track straight and curved paths in an indoor environment. In order to follow the path/line, fuzzy logic techniques are applied to generate movement with the information extracted from vision system. The control method in the system combines a steering controller, which is implemented by an intelligent hybrid fuzzy PID controller, controlling the steering angle of the robot, and fuzzy velocity controller, which controls the forward linear velocity with the purpose of safe tracking. We do experiments using an open source differential-drive wheeled robot platform (Figure 1). In the experiments, the robot is successfully able to follow a pre-defined path/line containing both straight and curved sections. The effectiveness of the control algorithm, combining steering and velocity controllers, is examined in these experiments. Keywords: Control systems, vision system, fuzzy logic, steering controller, velocity controller. List of Symbols

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Design and Research Based on Fuzzy PID-Parameters Self-Tuning Controller with MATLAB

Cited by 22 publications

References 0 publications

A robust controlling methodology for a grouting process

A robust controlling methodology for a grouting process

A self-learning propotional–integral–derivative control of grouting pressure using the back-propagation model

Vision Based Autonomous Path/Line Following of a Mobile Robot Using a Hybrid Fuzzy PID Controller

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