Stability Analysis and Proposal of a Simple Form of a Fuzzy PID Controller

Lee, Byung-Kyul,Kim, In-Hwan,Kim, Jong-Hwa The Korean Society of Marine Engineering 2004 한국마린엔지니어링학회지 Vol.28 No.8

This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

Design of Fuzzy PD+I Controller Based on PID Controller

Sea-June Oh,Heui-Han Yoo,Yun-Hyung Lee,Myung-Ok So 한국항해항만학회 2010 한국항해항만학회지 Vol.34 No.2

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.

Gain Tuning of a Fuzzy Logic Controller Superior to PD Controllers in Motor Position Control

Kim, Young-Real Korean Institute of Intelligent Systems 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.3

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

Gain Tuning of a Fuzzy Logic Controller Superior to PD Controllers in Motor Position Control

Young-Real Kim 한국지능시스템학회 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.3

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

Intelligent Prevent the Risk of Carcinoma of the Lung Progression

Sareh Mohammadi Jaberi,Farzin Piltan,Amirzubir Sahamijoo,Nasri b Sulaiman 보안공학연구지원센터 2015 International Journal of Bio-Science and Bio-Techn Vol.7 No.4

Smog hanging over cities is the most familiar and obvious form of air pollution. The effects of inhaling particulate matter have been studied in humans and animals and include asthma, lung cancer, cardiovascular issues, and premature death. There are, however, some additional products of the combustion process that include nitrogen oxides and sulfur and some un-combusted hydrocarbons, depending on the operating conditions and the fuel-air ratio. Tuning the fuel to air ratio caused to control the lung cancer. Lung cancers are tumors arising from cells lining the airways of the respiratory system. Design of a robust nonlinear controller for automotive engine can be a challenging work. This research paper focuses on the design and analysis of a high performance PID like fuzzy controller for automotive engine, in certain and uncertain condition. The proposed approach effectively combines of design methods from linear Proportional-Integral-Derivative (PID) controller and fuzzy logic theory to improve the performance, stability and robustness of the automotive engine. To solve system’s dynamic nonlinearity, the PID fuzzy logic controller is used as a PID like fuzzy logic controller. The PID like fuzzy logic controller is updated based on gain updating factor. In this methodology, fuzzy logic controller is used to estimate the dynamic uncertainties. In this methodology, PID like fuzzy logic controller is evaluated. PID like fuzzy logic controller has three inputs, Proportional (P), Derivative (D), and Integrator (I), if each inputs have linguistic variables to defined the dynamic behavior, it has ×× linguistic variables. To solve this challenge, parallel structure of a PD-like fuzzy controller and PI-like fuzzy controller is evaluated. In the next step, the challenge of design PI and PD fuzzy rule tables are supposed to be solved. To solve this challenge PID like fuzzy controller is replaced by PD-like fuzzy controller with the integral term in output. This method is caused to design only PD type rule table for PD like fuzzy controller and PI like fuzzy controller.

직류 전동기 속도 제어에서 PI 제어기보다 우수한 퍼지 논리 제어기의 이득 선정을 위한 연구

김영렬(Young-Real Kim) 한국조명·전기설비학회 2014 조명·전기설비학회논문지 Vol.28 No.6

Through a lot of papers, it has been concluded that fuzzy logic controller is superior to PI controller in motor speed control. Although fuzzy logic controller is superior to PI controller in motor speed control, the gain tuning of fuzzy logic controller is more complicated than that of PI controller. In this paper, using mathematical analysis of the PI and fuzzy controller, the design method of the fuzzy controller that has the same characteristics with the PI controller is proposed. After that, we can design the fuzzy controller that has superior performance than PI controller by changing the envelope of input of fuzzy controller to nonlinear, because the fuzzy controller has more degree of freedom to select the control gain than PI controller. The advantage of fuzzy logic controller is shown through mathematical analysis, and the simulation result using Matlab simulink has been proposed to show the effectiveness of these analysis.

퍼지 PI+D 제어기의 절계변수와 제어가 이득 자기동조에 관한연구

장철수,전정수,황준석,채석 금오공과대학교 2005 論文集 Vol.26 No.-

This paper describes the design of the Proportional-Integral(PI) plus a Derivative(D) controller using self-tuning of the design variables and controller gains. First, the fuzzy PI+D controller is derived from the conventional continuous time linear PI+D controller. Then, the fuzzification, control-rule base, and defuzzification in the the fuzzy controller are discussed in detail. The resulting controller .is a discrete time fuzzy version of the conventional PI+D controller, which has the same linear structure, but is nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the fuzzy PI+D controller is applied. First, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding design variables and adjust controller gains. So the proposed method has the capability of the high speed inference and can be adapted to increasing the number of the fuzzy input variables easilly and has the advantage to reduce a reconstruction(digital sampling reconstruction) error. This controller has better efficiency and improvement by using a design variables and controller gains. 이 논문에서는 설계변수와 제어기 이득의 자기 동조를 사용하는 PI+D 제어기 설계에 대하여 기술한다. 사용된 퍼지 PI+D 제어기는 일반적인 연속 시간 선형 PI+D 제어기를 근사화하여 사용하였고 퍼지화는 퍼지싱글톤으로, 비퍼지화는 간략화된 무게중심법을 사용하였다. 제안된 제어기는 제어대상이 비선형일 때 자기 동조 성능이 개선된다. 퍼지 PI+D 제어기가 적용되면 퍼지추정 결과는 분리된 퍼지 변수로서 다른 작용 성분으로 계산되고, 그 결과는 설계변수에 해당히는 함수의 형태로 결정되어 제어이득을 결정한다. 따라서 제안된 방법은 빠른 속도 추정의 성능을 가지며, 퍼지 입력변수의 증가에도 쉽게 적용될 수 있고, 재생 오차를 줄이는 이점을 가진다. 이 제어기는 설계변수와 제어기 이득의 사용으로 보다 높은 효율성과 개선점을 가지고 있다.

Gain Tuning of a Fuzzy Logic Controller Superior to PD Controllers in Motor Position Control

김영렬 한국지능시스템학회 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.3

Although the fuzzy logic controller is superior to the proportional integral derivative (PID)controller in motor control, the gain tuning of the fuzzy logic controller is more complicatedthan that of the PID controller. Using mathematical analysis of the proportional derivative (PD)and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller thathas the same characteristics as the PD controller in the beginning. Then a design method of afuzzy logic controller was proposed that has superior performance to the PD controller. Thisfuzzy logic controller was designed by changing the envelope of the input of the of the fuzzylogic controller to nonlinear, because the fuzzy logic controller has more degree of freedom toselect the control gain than the PD controller. By designing the fuzzy logic controller usingthe proposed method, it simplified the design of fuzzy logic controller, and it simplified thecomparison of these two controllers.

Design of Fuzzy PD+I Controller Based on PID Controller

오세준,유희한,소명옥,이윤형 한국항해항만학회 2010 한국항해항만학회지 Vol.34 No.2

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.

Design of Fuzzy PD+I Controller Based on PID Controller

Oh, Sea-June,Yoo, Heui-Han,Lee, Yun-Hyung,So, Myung-Ok Korean Institute of Navigation and Port Research 2010 한국항해항만학회지 Vol. No.

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains and to analyse the stability compared to conventional PID controllers. This paper proposes a fuzzy PD+I controller for tracking control which uses a linear fuzzy inference(product-sum-gravity) method based on a conventional linear PID controller. In this scheme the fuzzy PD+I controller works similar to the control performance as the linear PD plus I(PD+I) controller. Thus it is possible to analyse and design an fuzzy PD+I controller for given systems based on a linear fuzzy PD controller. The scaling factors tuning scheme, another topic of fuzzy controller design procedure, is also introduced in order to fine performance of the fuzzy PD+I controller. The scaling factors are adjusted by a real-coded genetic algorithm(RCGA) in off-line. The simulation results show the effectiveness of the proposed fuzzy PD+I controller for tracking control problems by comparing with the conventional PID controllers.