• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• Journal of Drive and Control
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• v.11 no.4
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• pp.1-7
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• 2014

This paper presents the development of a compact position generator to be used for industrial purposes based on a pump controlled Electro-Hydraulic Actuator (EHA), which is closed-loop controlled by an embedded based Iterative PID controller. The controller is designed by combining the PID controller and the iterative learning scheme to perform tracking control for periodically desired references. Control algorithm is implemented on an embedded computer (AD 7011-EVA) which makes the implementation and application in industrial environments easier.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.335-338
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• 1996

In this paper, we are going to design an iterative learning controller with the robust properties for initial error. For this purpose, the PID-type learning law will be considered and the design guide-line will be presented for the selection of the learning gain. Also, we are going to suggest a condition for the convergence of control input for a plant with input delay. Several simulation results are presented, which shows the effectiveness of the proposed algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.74-83
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• 1996

An iterative tuning technique is derived for PID controllers which are widely used in industries. The tuning algorithm is based upon a fuzzy indirect reasoning method and an iterative technique. The PID gains for the first tuning action are determined by a method which is modified from the Ziegler-Nichols step response method. The first PID gains are determined to obtain a control performance so close to a design performance that the following tuning process can be made effectively. The design paramaters are given as time-domain variables which human is familiar with. The results of simulation studies show that the proposed tuning method can produce an effective tuning for arbitrary design performances.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.117-127
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• 2007

Many real world control systems usually track several control objectives, simultaneously. At the moment, it is desirable to meet all specified goals using the controllers with simple structures like as proportional-integral (PI) and proportional-integral-derivative (PID) which are very useful in industry applications. Since in practice, these controllers are commonly tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specifications. This paper addresses a new method to bridge the gap between the power of optimal multiobjective control and PI/PID industrial controls. First the PI/PID control problem is reduced to a static output feedback control synthesis through the mixed $H_2/H_{\infty}$ control technique, and then the control parameters are easily carried out using an iterative linear matrix inequalities (ILMI) algorithm. Numerical examples on load-frequency control (LFC) and power system stabilizer (PSS) designs are given to illustrate the proposed methodology. The results are compared with genetic algorithm (GA) based multiobjective control and LMI based full order mixed $H_2/H_{\infty}$ control designs.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1143-1148
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• 2007

LRE(Liquid propellant Rocket Engine) is one of the important parts to control the motion of rocket. For operation of rocket in error boundary of the set-up trajectory, it is necessarily to control the thrust of LRE according to the required thrust profile and control the mixture ratio of propellants fed into combustor for the constant mixture ratio. It is not easy to control thrust and mixture ratio of propellants since there are co-interferences among the components of LRE. In this study, the dynamic model of LRE was constructed and the dynamic characteristics were analyzed with control system as PID control and PID+Q-ILC(Iterative Learning Control with Quadratic Criterion) control. From the analysis, it could be observed that PID+Q-ILC control logic is more useful than standard PID control system for control of LRE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2009-2014
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• 2007

A novel method of minimizing video quality variation is proposed for a real-time frame-layer rate control algorithm with a transmission buffer. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize variation in distortion between frames. In order to reflect the buffer status, we use well-known PID control method. Computational complexity of PID control is very low, so the proposed algorithm is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better PSNR performance than the existing rate control method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1612-1617
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• 2008

Since most disturbance observer (DOB) approaches have been limited to minimum-phase systems (or systems having no zero dynamics), we propose a new DOB structure that can be applied to non-minimum phase systems. The new structure features an additional system, which is called as V-filter, whose role is to yield a minimum phase system when connected with the plant in parallel. In order to design the V-filter systematically we first consider a class of linear systems that can be stabilized via PID controller. By inverting the controller's transfer function, we can simply construct the filter. A convenient way of designing V-filter is presented by using an iterative linear matrix inequality (LMI) algorithm. With an illustrative example the simulation result shows that substantial improvement in the performance has been achieved compared with the control system without the DOB.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.29-34
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• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.307-310
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• 2003

In this paper, an iterative learning control method is applied to suppress the vibration of a 2-mass system which has a flexible coupling between a load an a motor. More specifically, conditions for the load speed without vibration are derived based on the steady-state condition. And the desired motor position trajectory is synthesized based on the relation between the load and motor speed. Finally, a PD-type learning iterative control law is applied for the desired motor position trajectory. Since the learning law applied for the desired trajectory guarantees the perfect tracking performance, the resulting load speed shows no vibration. In order to handle the initial position error, the PD-type learning law is changed to PID-type and a weight function is added to suppress the residual vibration caused by the initial error. The simulation results show the effectiveness of the proposed learning method.