• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.598-603
• /
• 2004

An optical head actuator of an optical disk drive consists of two servo mechanisms for the focusing and the tracking to acquire data from disk. As the rotational speed of the disk grows, the utilized lag-lead-lead compensator has known to be above its ability for precisely controlling the optical head actuator. To overcome the difficulty, this paper propose a new controller design method for optical head actuator based fuzzy proportional-integral-derivative (PID) control and the genetic algorithm(GA). It employs a two-stage control structure with a fuzzy PI and a fuzzy PD control and is optimized by the GA to yield the suboptimal fuzzy PID control performance. It is shown the feasibility of the proposed method through a numerical tracking actuator simulation.

• Composites Research
• /
• v.17 no.4
• /
• pp.18-24
• /
• 2004

In this paper, active shape control of composite structures actuated by shape memory alloy (SMA) wires is presented. The thermo-mechanical behaviors of SMA wires were experimentally measured. Hybrid composite structures were established by attaching SMA actuators on the surfaces of graphite/epoxy composite beams using bolt-joint connectors. SMA actuators were activated by phase transformation, which induced by temperature rising over austenite finish temperature. In this paper, electrical resistive heating was applied to the hybrid composite structures to activate the SMA actuators. For (aster and more accurate shape/deflection control of the hybrid composite structure, PID feedback controller was designed from numerical simulations and experimentally applied to the SMA actuators.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.288-291
• /
• 1999

The PID (Proportional-Integral-Derivative) controller is widely used in the industries for more than fifty years with the well known Ziegler-Nichols tuning method and others varieties. However, most of the PID controller being used in the real practice still require trial and error adjustment for each process after the tuning method is done, which is consuming of time and needs the operator experiences to obtain the best results for the controller parameter. In order to reduce the inconvenience in the controller tuning, this paper presents a design of an automatic PID controller parameter analyzer being used as a support instrument in the industrial process control. This analyzer is designed based on the tuning formula of Dahlin to synthesize the PID controller parameter. Using this analyzer, the time to be spent in the trial and error procedures and its complexity can be neglected. Experimental results using PID controller parameter synthesized from this analyzer to the liquid level control plant model and the fluid flow control plant model show that the responses of the controlled systems can be efficiently controlled without any difficulty in mathemathical computation.

• Journal of Korea Technical Association of The Pulp and Paper Industry
• /
• v.43 no.3
• /
• pp.1-10
• /
• 2011

Proportional.Integral.Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, and Particle Swarm Optimization and Ant colony optimization. The proposed algorithm is used to tune the PID parameters and its performance has been compared with the conventional methods like Ziegler Nichols and Lambda method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on Machine Direction of basics weight control in pulp and paper industry. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the soft computing based tuning method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.11
• /
• pp.1134-1142
• /
• 2008

In this paper, a model-based stick-slip compensation for the micro-positioning is proposed using an enhanced stick-slip model based on statistical rough surface contact model. The smart structure is comprised with PZT(lead (Pb) zirconia(Zr) Titanate(Ti)) based stack actuator incorporating with the PID(proportional-integral-derivative) control algorithm, mechanical displacement amplifier and positioning devices. For the stick-slip compensation, the elastic-plastic static friction model is used considering the elastic-plastic asperity contact in the rough surfaces statistically. Mathematical model of system for the positioning apparatus was derived from the dynamic behaviors of structural parts. PID feedback control algorithms with the developed stick-slip model as well as feedforward friction compensator are formulated for achieving the accurate positioning performance. Experimental results are provided to show the performances of friction control using the developed positioning apparatus.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.1
• /
• pp.1-8
• /
• 2008

A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.758-761
• /
• 2004

This paper proposes a design and implementation of multiplierless digital PID (Proportional-Integral-Derivative) controller using FPGA (Field Programmable Gate Array) for controlling the speed of DC motor in digital system. The multiplierless PID structure is based on Distributed Arithmetic (DA). The DA is an efficient way to compute an inner product using partial products, each can be obtained by using look-up table. The PID controller is designed using MATLAB program to generate a set of coefficients associated with a desired controller characteristics. The controller coefficients are then included in VHDL (Very high speed integrated circuit Hardware Description Language) that implements the PID controller onto FPGA. MATLAB program is used to activate the PID controller, calculate and plot the time response of the control system. In addition, the hardware implementation uses VHDL and synthesis using FLEX10K Altera FPGA as target technology and use MAX+plusII program for overall development. Results in design are shown the speed performance and used area of FPGA. Finally, the experimental results can be shown when compared with the simulation results from MATLAB.

• Journal of Mechanical Science and Technology
• /
• v.14 no.4
• /
• pp.418-425
• /
• 2000

Recently, many passenger cars have adopted automatic transmissions for shifting gears, and thus the smooth and precise control of gear shifts of passenger car automatic transmissions has become more and more essential for the riding comfort of vehicles equipped with automatic transmissions. In this article, a neural network-based supervisor for an automotive shift controller considering the throttle opening, variations in throttle opening, and the driving load is presented. For using the driving load information, an observer-based driving load estimation algorithm is proposed. A proportional-integral-derivative controller along with an open loop controller is used as a low level controller for controlling the gear shifts, and a supervisory controller for properly adapting the shift control parameters of the low level shift controller is designed using ANFIS. To evaluate the control performance of the proposed supervisor-based shift controller, both simulation studies and experimental studies are performed for various shifting situations.

• International Journal of Aeronautical and Space Sciences
• /
• v.12 no.3
• /
• pp.274-282
• /
• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

• International Journal of Aeronautical and Space Sciences
• /
• v.12 no.3
• /
• pp.252-259
• /
• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.