Results 191 to 200 of about 46,050 (232)
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Fuzzy precompensation of PID controllers
Proceedings of IEEE International Conference on Control and Applications, 2002While PID controllers are widely used in industrial applications, they exhibit poor performance when applied to systems containing unknown nonlinearities, such as deadzones, saturation, and hysteresis. In this paper, we propose a fuzzy logic-based precompensation approach for PID controllers. We demonstrate the performance of our scheme via experiments
null Jong-Hwan Kim +3 more
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Adaptive Neuro-Fuzzy-PID and Fuzzy-PID-Based Controller Design for Helicopter System
2019The paper presents designing and control of two-degree-of-freedom helicopter system, with two degrees of freedom. The helicopter is a combination of rotor motors which helps to lift the body of system. This is a nonlinear and unstable system in nature. The control techniques focused are adaptive neuro-fuzzy inference-PID and fuzzy-PID.
Rupam Singh, Bharat Bhushan
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Self-tuning fuzzy PID controller
2013 International Conference on Process Control (PC), 2013In this paper method of design of self-tuning fuzzy PID controller is addressed, proposed and tested. Fuzzy logic is used to tune each parameter of PID controller. The proposed controller is tested in control of the concentration in the chemical reactor, manipulating its flow rate.
Jana Paulusova +2 more
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An optimal fuzzy PID controller
IEEE Transactions on Industrial Electronics, 2001This paper introduces an optimal fuzzy proportional-integral-derivative (PID) controller. The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear structure of the proportional, integral, and derivative parts but has constant coefficient yet self-tuned control gains. Fuzzy logic is employed
K.S. Tang +3 more
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Fuzzy anti-reset windup for PID controllers
Control Engineering Practice, 1993Abstract In this paper anti windup schemes for PID controllers are proposed that consider not only actuator constraints but also process state constraints. The schemes are fuzzy generalizations and combinations of the traditional conditional integration anti windup schemes.
A. Hansson, P. Gruber, J. Tödtli
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Two-level tuning of fuzzy PID controllers
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2001Fuzzy PID tuning requires two stages of tuning; low level tuning followed by high level tuning. At the higher level, a nonlinear tuning is performed to determine the nonlinear characteristics of the fuzzy output. At the lower level, a linear tuning is performed to determine the linear characteristics of the fuzzy output for achieving overall ...
Mann, Georges K. I. +2 more
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Automation and Remote Control, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vassilyev, S. N. +6 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vassilyev, S. N. +6 more
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Intelligent Fuzzy PID Controller
2008This chapter aims to describe the development and two tuning methods for a self-organising fuzzy PID controller. Before application of fuzzy logic, the PID gains are tuned by conventional tuning methods. In the first tuning method, fuzzy logic at the supervisory level readjusts the three PID gains during the system operation.
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Improving Vegas Algorithm Using PID and Fuzzy PID Controllers
2006Since in the TCP protocol the source has no idea which congestion window size will result in the best performance, it tunes the window size according to parameters such as loss, duplicate acknowledge and etc. The Vegas algorithm is one of the most intelligent flow control algorithms that despite other protocols, tunes the window size by estimation of ...
Aria Shahingohar +3 more
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Flexible complexity reduced PID-like fuzzy controllers
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2000In this paper, a flexible complexity reduced design approach for PID-like fuzzy controllers is proposed. With the linear combination of input variables as a new input variable, the complexity of the fuzzy mechanism of PID-like fuzzy controllers is significantly reduced.
C W, Tao, J S, Taur
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