• Title/Summary/Keyword: PID-control with fuzzy logic control

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Design of a Fuzzy P+ID controller for brushless DC motor speed control (BLDCM 의 속도 제어를 위한 퍼지 P+ID 제어기 설계)

  • Kim, Young-Sik;Lee, Chang-Goo;Kim, Sung-Joong
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2161-2163
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    • 2002
  • The PID type controller has been widely used in industrial application doc to its simply control structure, ease of design and inexpensive cost. However control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (Fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuazy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controlled is better than that of the conventional controller.

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Adaptive Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.146-156
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

FUZZY SOGIC CONTROL FO DIRECT DRIVE ROBOT MANIPULATORS

  • Kang, Chul-Goo;Kwak, Hee-Sung
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.428-433
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    • 1994
  • This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

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Optimal Speed Control of Hybrid Electric Vehicles

  • Yadav, Anil Kumar;Gaur, Prerna;Jha, Shyama Kant;Gupta, J.R.P.;Mittal, A.P.
    • Journal of Power Electronics
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    • v.11 no.4
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    • pp.393-400
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    • 2011
  • The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

A Study on Improvement of Automatic Vehicle´s Comfortability using Fuzzy Controller

  • Il, Bae-Jong;Park, H.S.;Park, Yeon-Wook;Yeun, Hwnag-Yeong;Ha M.K.
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.128.4-128
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    • 2001
  • Based on fuzzy logic algorithm this paper constructed fuzzy logic controller for automated vehicles. For passenger´s convenience especially comfortability controller need to reduce the frequency of input variable´s changing. So we established membership functions for comfortability as well as speed following. It made possible to control comfortability directly. To demonstration the efficiency of fuzzy logic controller, we carried out simulation with a automobile´s transfer function. First, we designed the PID controller by using Ziegler-Nichols tunning method. Second, we calculated time response for each controller, then we compared the speed patterns of fuzzy controlled system and PID controlled system. Also we compared the difference of input variable ...

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A generalized ANFIS controller for vibration mitigation of uncertain building structure

  • Javad Palizvan Zand;Javad Katebi;Saman Yaghmaei-Sabegh
    • Structural Engineering and Mechanics
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    • v.87 no.3
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    • pp.231-242
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    • 2023
  • A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

A Quantitative Analysis of the Nonlinearity of Fuzzy Logic Controller (퍼지논리 제어기의 비선형성의 정량적 해석)

  • Lee, Chul-Heui;Seo, Seon-Hak
    • Journal of Industrial Technology
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    • v.16
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    • pp.231-237
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    • 1996
  • In this paper, the nonlinear I/O characteristic of fuzzy logic controller is analyzed by using cell concept. Sources of the nonlinearity in a fuzzy logic controller include the fuzzification, the fuzzy reasoning and the defuzzification. A closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity is analyzed with respect to the conventional PID control and the sliding mode control.

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Position Control by Fuzzy Logic Controller with Acceleration Converter

  • Park, Jin-Bae;Shohei, Niwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.108.4-108
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    • 2001
  • The integrated environment for the fuzzy logic controller with the acceleration converter to improve the dynamic characteristic of a one-axis moving table is proposed in the paper. The two inputs of the fuzzy logic controller are position error and velocity. The two inputs of the acceleration converter used to produce the acceleration input for the one-axis moving table are actual and setting rotational speeds. The proposed controller is implemented on a personal computer by using MATLAB and Visual Basic for a real time control via a motion control board. The position control results when the stair input is applied to control the position of the one-axis moving table, are shown. The experimental results of the proposed position control system are compared to the conventional PID ...

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On-line self-tuning PID power controller using fuzzy logic for CDMA cellular systems (퍼지 논리를 이용한 온라인 자기동조기능을 갖는 CDMA 셀룰러 시스템용 PID 전력제어기)

  • 김상민;한진욱;김성중
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.211-214
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    • 1997
  • This paper applies fuzzy self-tuning PID controller in DS/CDMA cellular system. Power control is essential in DS/CDMA to compensate for the differing received powers due to both the slowly varying long-term and fast varying short-term fading processes and co-channel interference. The controller proposed is adaptable for the variations of the system dynamics and especially for the variable time delay which exists in mobile radio systems. Accordingly the results is the smaller power control error, that is, the smaller average transmitting power of mobile compared with the conventional control schemes. Because interferences to the other mobiles are reduced, the capacity of CDMA can be increased.

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Design of Sophisticated Self-Tuning Fuzzy Logic Controllers Using Genetic Algorithms (유전알고리즘을 이용한 정교한 자기동조 퍼지 제어기의 설계)

  • Hwang, Yon-Won;Kim, Lark-Kyo;Nam, Moon-Hyon
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.509-511
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    • 1998
  • Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership function and fuzzy rule base, which is traditionally achieved by tedious trial-and-error process. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm(GA). The controller design space is coded in base-7 strings chromosomes, where each bit gene matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a do-servo motor control system. It was presented in discrete fuzzy linguistic value, and used a membership function with Gaussian curve. The performance of this control system is demonstrated higher than that of a conventional PID controller and fuzzy logic controller(FLC).

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