• Title, Summary, Keyword: Adaptive PID controller

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An Effective Adaptive Autopilot for Ships

  • Le, Minh-Duc;Nguyen, Si-Hiep;Nguyen, Lan-Anh
    • 제어로봇시스템학회:학술대회논문집
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    • pp.720-723
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    • 2005
  • Ship motion is a complex controlled process with several hydrodynamic parameters that vary in wide ranges with respect to ship load condition, speed and surrounding conditions (such as wind, current, tide, etc.). Therefore, to effectively control ships in a designed track is always an important task for ship masters. This paper presents an effective adaptive autopilot ships that ensure the optimal accuracy, economy and stability characteristics. The PID control methodology is modified and parameters of a PID controller is designed to satisfy conditions for an optimal objective function that comprised by heading error, resistance and drift during changing course, and loss of surge velocity or fuel consumption. Designing of the controller for course changing process is based on the Model Reference Adaptive System (MRAS) control theory, while as designing of the automatic course keeping process is based on the Self Tuning Regulator (STR) control theory. Simulation (using MATLAB software) in various disturbance conditions shows that in comparison with conventional PID autopilots, the designed autopilot has several notable advantages: higher course turning speed, lower swing of ship bow even in strong waves and winds, high accuracy of course keeping, shorter time of rudder actions smaller times of changing rudder direction.

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A Design of Steering Controller for AGV using Immune Algorithm (면역 알고리즘을 이용한 AGV의 조향 제어기 설계에 관한 연구)

  • Lee, Chang-Hoon;Lee, Jin-Woo;Lee, Young-Jin;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • pp.2824-2826
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    • 2002
  • Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etcetera. Immune algorithm is the modeling of this systems response that has adaptation and reliability when disturbance occur. In this paper, immune algorithm is proposed to control four wheels steering AGV(Automated Guided Vehicle) in container yard. The adaptive immune system is applied to the PID controller. For design the PID controller using immune algorithm, we tune PID parameters by off-line manner, in order to avoid the damage from abrupt control force. Repeatedly, the PID parameters are adjusted to be accurate by on-line fine tuner of immune algorithm. And then the computer simulation result from the viewpoint of yaw rate and lateral displacement are analyzed and compared with result of conventional PID controller.

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A Study on the Load Frequency Control of Two-Area Power System using ANFIS Precompensated PID Controller (ANFIS 전 보상 PID 제어기에 의한 2지역 전력계통의 부하주파수 제어에 관한 연구)

  • Chung, Mun-Kyu;Chung, Kyeong-Hwan;Joo, Seok-Min;An, Byung-Chul
    • Proceedings of the KIEE Conference
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    • pp.1314-1317
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    • 1999
  • In this paper, we design an Adaptive Neuro-Fuzzy Inference System(ANFIS) Precompensator for the performance improvement of conventional proportional integral derivative (PID) controller that the governor system of power plant constantly maintains the load frequency of two-area power system. The ANFIS Precompensator is expressed as the membership functions of premise parameters and the linear combination of consequent parameters by Sugeno's fuzzy if-then rules using nonlinear input-output relation for the set point automatic modification maintaining conventional PID controller. The proposed compensation design technique is hoped to be satisfactory method overcome difficulty of exact modelling and arising problems by the complex nonlinearities of power system, and our design shows merit that is easily implemented by adding an ANFIS precompenastor to an existing PID controller without replacement.

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A Design of An Active PID control using Immune Algorithm for Vibration Control of Building Structure (구조물 진동제어를 위한 Immune Algorithm을 이용한 Active PID 제어기 설계)

  • Lee, Young-Jin;Cho, Hyun-Cheol;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • pp.72-74
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    • 2005
  • In this paper, we propose an adaptive PID controller using a cell-mediated immune response to improve a PID control performance. The proposed controller is based on the specific immune response of the biological immune system that is cell-mediated immunity. The immune system of organisms in the real body regulates the antibody and the T-cells to protect an attack from the foreign materials like virus, germ cells, and other antigens. It has similar characteristics that are the adaptation and robustness to overcome disturbances and to control the plant of engineering application. We first build a model of the T-cell regulated immune response mechanism and then designed an I-PID controller focusing on the T-cell regulated immune response of the biological immune system. We apply the proposed methodology to building structures to mitigate vibrations due to strong winds for evaluation of control performances. Through computer simulations, system responses are illustrated and additionally compared to traditional control approaches.

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A Design of Hybrid Controller Using Self-Learning Fuzzy Controller (자기학습 퍼지제어기를 사용한 하이브리드 제어기 설계)

  • Yang, H.W.;Lee, H.H.
    • Proceedings of the KIEE Conference
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    • pp.207-209
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    • 1995
  • The PID controller is widely used due to its fast response and robustness. But its performance is not so good compared with modem controllers such as adaptive, robust, fuzzy, neural controller. Therefore, it is natural to replace PID controller by modem controllers. But, the problem is that modem controller can not be easily applied to the real time process. Hence, this paper proposes such a structure that PID controller and Self-Learning Fuzzy Controller(SLFC) are in parallel with each other. The parameter of SLFC will be updated by gradient descent method using neuro - identifier. The usefulness of this hybrid controller will be proved by simulation results.

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An intelligent Speed Control System for Marine Diesel Engine (선박용 디젤기관의 지능적인 속도제어시스템)

  • 오세준
    • Journal of the Korean Society of Marine Engineering
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    • v.22 no.3
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    • pp.320-327
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    • 1998
  • The purpose of this study is to design the intelligent speed control system for marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. Recently for the speed control of a diesel engine some methods using the advanced control techniques such as LQ control Fuzzy control or H$\infty$ control etc. have been reported. However most of speed controllers of a marine diesel engine developed are still using the PID control algorithm But the performance of a marine diesel engine depends highly on the parameter setting of the PID controllers. The authors proposed already a new method to tune efficiently the PID parameters by the Model Mathcing Method typically taking a marine diesel engine as a non-oscillatory second-order system. It was confirmed that the previously proposed method is superior to Ziegler & Nichols's method through simulations under the assumption that the parameters of a diesel engine are exactly known. But actually it is very difficult to find out the exact model of the diesel engine. Therefore when the model and the actual diesel engine are unmatched as an alternative to enhance the speed control characteristics this paper proposes a Model Refernce Adaptive Speed Control system of a diesel engine in which PID control system for the model of a diesel engine is adopted as the nominal model and a Fuzzy controller is adopted as the adaptive controller, And in the nominal model parameters of a diesel engine are adjusted using the Model Matching Method. it is confirmed that the proposed method gives better performance than the case of using only Model Matching Method through the analysis of the characteristics of indicial responses.

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The phase angle driving adaptive control of single-induction motor using one-chip micro controller (원칩 마이컴을 이용한 단상유도전동기의 위상각 구동 적응제어)

  • 이형상;김정도;김이경;이택종
    • 제어로봇시스템학회:학술대회논문집
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    • pp.675-679
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    • 1992
  • In industry, the speed control of single-phase induction motor in domestic use is generally controlled by a simple ON-OFF or PID control method. However, in this case, in order to have a good speed regulating characteristics, itself should be modified in accordance with the optimum PID factors which are varied each time operating speed changes. Shortening the development time and saving the cost which are needed to modify the controller is a major problem to be solved now in industry. In order to alleviate the above difficulties, it is proposed to apply adaptive control technique using MRFAC(Model Reference Following Adaptive Control) for the speed control of single-phase induction motor which has scarcely been studied. In this paper, the above speed control technique is achieved using MCS-96 one chip micro controller with a good speed control characteristics and it is expetted to open a wide application field in the speed control of single-phase induction motor in the future.

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A Study on Adaptive-Tuning of PID Controller Using a Neural Network (신경망을 이용한 PID제어기의 적응동조에 관한 연구)

  • Kim, Sang-Won;Lee, Hong-Kyu
    • Proceedings of the KIEE Conference
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    • pp.690-692
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    • 1999
  • In this thesis, We implement the controller system only using the neural network to identify the plant characteristics with keeping the PID controller structure. The neural network has learned by the adaptive learning rates that has suggested by Chao-Chee Ku and the DBP algorithm. We proposed the on-line tuning algorithm about the unknown plant using the adaptive tuning technique. As a result of executing the parameters has tuned from the initial value to more suitable ones and the output of the Plant has improved and also it is appeared that the convergence is guaranteed.

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A Study on the Real Time Adaptive Controller for SCARA Robot Using TMS320C31 Chip (TMS320C31 칩을 사용한 스카라 로봇의 실시간 적응제어데 관한 연구)

  • 김용태
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • pp.79-84
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    • 1996
  • This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

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Design of a Real Time Adaptive Controller for SCARA Robot Using Digitl Signal Process (디지탈 신호처리기를 사용한 스카라 로보트의 실시간 적응제어기 설계)

  • 김용태;서운학;한성현;이만형;김성권
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • pp.472-477
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    • 1996
  • This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

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