• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.8
• /
• pp.1299-1312
• /
• 2004

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.

• The Journal of Korea Robotics Society
• /
• v.16 no.1
• /
• pp.35-40
• /
• 2021

As the robot industry develops, industrial automation uses industrial robots in many parts of the manufacturing industry. However, rigidity-based conventional robots have a disadvantage in that they are challenging to use in environments where they grab fragile objects or interact with people because of their high rigidity. Therefore, researches on soft robot have been actively conducted. The soft robot can hold or manipulate fragile objects by using its compliance and has high safety even in an atypical environment with human interaction. However, these advantages are difficult to use in dynamic situations and control by the material's nonlinear behavior. However, for the soft robot to be used in the industry, control is essential. Therefore, in this paper, real-time PD control is applied, and the behavior of the soft actuator is analyzed by providing various waveforms as inputs. Also, Iterative learning control (ILC) is applied to reduce errors and select an ILC type suitable for soft actuators.

• Journal of Mechanical Science and Technology
• /
• v.16 no.12
• /
• pp.1643-1651
• /
• 2002

Magnetic levitation systems are required to have a large operating range in many applications. As one method to solve this problem, Time Delay Control (TDC) is applied to a single-axis magnetic levitation system in this paper A reduced-order observer is utilized to estimate states excluding measurable states in the control law. The system consists of a square air-core solenoid and a circular permanent magnet attached on a plastic ball. Theoretical magnetic forces of the system are obtained on the basis of the location of the magnet around the solenoid. The magnetic levitation force is obtained by the experiment, and then compared with the theoretical one. As the results of the control experiments, the nonlinear controller (TDC : 1-2 ㎜) has a larger operating range than the linear controller (PD control : 1-1.4 ㎜), and is superior to linear. control in the robustness to the modeling uncertainty and the performance of the disturbance rejection.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.12
• /
• pp.3073-3082
• /
• 1993

A magnetically suspended robot joint is developed, which is free of dust and oil generation. Two radial bearings consisting of cone-shaped magnet cores control the rotor motion in the axial and radial directions. A linearized dynamic model is developed for active control of the magnetic bearing system. The control algorithm is constructed such that the axial displacement of the joint is controlled by radial control current to the pairs of facing radial bearings. The stability and control performance is tested through numerical simulation based on the nonlinear model. Experiments are also performed to verify the theoretical development.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.687-692
• /
• 1990

The purpose of this study is ID form the required force for measurements of the performances of the equipments or testpieces. For the generation of the required force, ft difference of pressures in each chamber of the hydraulic cylinder was controlled and Variable Structure Control theory was adopted to control it. Besides, observers -Luenberger Observer and nonlinear Variable Structure Observer - were designed to estimate the derivative of the load pressure which is necessary ID determine the sliding surface in VSC theory. As a consequence of the computer simulation, it was shown that VSC had better performance than classical control theory(P, PD control) and VSO performed better than the Luenberger Observer at the load pressure control.

• Proceedings of the KIEE Conference
• /
• 1998.11b
• /
• pp.558-560
• /
• 1998

The operation of robot manipulators has a restriction that the operator must reside at the factory, where the manipulator is used. To overcome this restriction, we propose a remote control system using the internet, the system which runs on the Window 95 environment is composed of the remote client which transfers commands to the server which control and manage the manipulator in the factory. In the control of Hong-ik Direct Drive Arm, it is necessary to consider the complex nonlinear parameters causing the mutual interaction between joints, so we use two TMS320C31 DSP chips in the controller for the real time dynamic control algorithms. For the test of system integrity and the verification of the mathematical modeling, we apply CTM, PD and VSS control algorithms and the simulation results are satisfactory.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.2
• /
• pp.150-159
• /
• 2010

The approach and landing phase of a re-entry vehicle is composed of Steep Glideslope phase, Circular Flare phase, Flare Maneuver phase. The trajectory planning algorithm with geometric parameters is studied in this paper for on-board trajectory planning. This algorithm generate reference trajectory rapidly considering safe landing of re-entry vehicle. In this paper, the Mamdani Fuzzy PD type controller for longitudinal and lateral control is designed which has robustness of nonlinear system. In addition, the simulation is performed including initial downrange and crossrange errors, and the results shows that the proposed fuzzy logic controller has good performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.3
• /
• pp.375-382
• /
• 2004

This paper presents control designs using neural networks (NN) for a XY positioning table. The proposed neuro-controller is composed of an outer PD tracking loop for stabilization of the fast flexible-mode dynamics and an NN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NN weights, so that the NN compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded weight estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The proposed neuro-controller is implemented and tested on an IBM PC-based XY positioning table, and is applicable to many precision XY tables. The algorithm, simulation, and experimental results are described. The experimental results are shown to be superior to those of conventional control.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.705-709
• /
• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2240-2245
• /
• 2003

In this paper, the controller design by coefficient diagram method (CDM) for controlling the trolley position, load-swing angle and hoisting rope length of the overhead crane system simultaneously is proposed. The overhead crane system is a MIMO system consisting of two inputs and three outputs. Its mathematical model is nonlinear with coupling characteristics. This nonlinear model can be approximated to obtain a linear model where the first input mainly affects the trolley position and the load-swing angle while the second input mainly affects the hoisting rope length. In order to utilize the CDM concept for assigning the controllers, namely PID, PD and PI controllers separately, the model is approximated to be three transfer functions in accordance with trolley position, the load-swing angle and the hoisting rope length controls respectively. The satisfied performances of the overhead crane system controlled by the these controllers and fast rejection of the disturbance effect occurred at the trolley position are shown by simulation and experimental results.