• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.503-509
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• 2014

In this paper, a PID controller with adaptive neural network compensator is proposed to control the formations of mobile robot. The control system is composed of a kinematic controller based on the leader-following robot and dynamic controller for considering the dynamics of the mobile robot. The dynamic controller is constituted by a PID controller and the adaptive neural network compensator for improving the performance and compensating the change in dynamic characteristics. Simulation results show the performance of the PID controller and the neural network compensator for the circular trajectory and linear trajectory. And it is verified that by improving the performance of a PID controller via the adaptive neural network compensator, the following robot's tracking performance is improved.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5B
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• pp.442-448
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• 2006

This paper considers a home gateway(HG) that processes VOD services and controls home appliances. This paper proposes a PID algorithm-based adaptive bandwidth control method used in the HG, which guarantees QoS of incoming traffic such as VOD and real-time control data via control of outgoing traffic and have little effects on the CPU computation time. The proposed method is validated via implementation of real test environment.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.105-110
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• 1990

In this paper, a compliance robot control algorithm using a PID adaptive controller is proposed. The compliance robot is suitable for the tasks in contact with environment, such as assembly operation or surface processing. A hybrid robot control method can control force and position simultaneously and two independant feedback closed loops are formed in this method. Because the compliance robot is operated in contact with environment, it is very difficult to obtain linear model of dynamics for this robot. In order to overcome this difficulty, a PID adaptive controller independant of robot dynamics is applied to the compliance robot. The proposed control algorithm for the compliance robot was analyzed and conformed by simulating the surface processing task by a two-joint robot.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.11
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• pp.720-726
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• 1988

This paper deals with an applicaton of some adaptive algorithms to a heat exchanger using a microcomputer and reviews the experimental results obtained. The heat exchanger prepared for experments was identified as a non-minimum phase system and its exact mathematical models was hardly obtainable with direct computation. Thus, classical strategies, such as PID, needed many trial and errors to determine parameters of the controllers. Furthermore such strategies could not guarantee good performance when system parameters vary. To overcome these difficulties and improve performance, two adaptive methods applicable to a non-minimum phase system were chosen and put to the test. In this paper the performance of adaptive controllers is compared with that of conventional PID controller. The final objective of this paper is to construct a controller readily applicable to industrial processes using a microprocessor.

• Journal of Drive and Control
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• v.14 no.4
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• pp.37-44
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• 2017

This paper introduces a control algorithm for trajectory control of an electro-hydrostatic rotary actuator. A key feature of this paper is that an adaptive PID based on sliding mode is used to control the nonlinearity and uncertainty factor of single input/output system. Accurate knowledge of rotary actuator angle can result in high-performance and efficiency of electro hydraulic system. First, the position control is formulated using the adaptive PID with sliding mode technique and uncertainties in the hydraulic system. Second, the controller can update the PID gains on-line based on error caused by external disturbance and uncertain factors in the system. Finally, three experimental cases were studied to evaluate the proposed control method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.197-203
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• 1997

In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.609-616
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• 2003

The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference 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 Fuzzy controller and derivative operator are adopted as the adaptive controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.185-188
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• 2009

In this paper, Position Controller for balance of Seesaw System design using PID Algorithm. Seesaw System is that it's system use widely to analyze of ship or flight dynamics, Inverted Pendulumand, Robot System, manage system for theory of modern control system and all sorts of analysis. In case of Seesaw System, it's necessity that understand and analysis of system and correct selection of parameter because the system is strong nonlinear control system. It guarantees efficiency and stability to adapt quickly for disturbance or change of controller from PID Algorithm of guarantee safe from simple and long history and PSO(Particle Swarm Optimization) that sort of metaheuristic optimization that need to accuracy and fast PID parameter tuning.