• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.475-481
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• 2013

The control system of a direct drive servo valve is a nonlinear system, and the flow force effect on the spool motion is significant and dependent on the load pressure. To satisfy the control system design requirements, the optimal parameters of the lead-lag controller and the derivative feedback controller are searched for using a genetic algorithm and a complex constrained direct search type method. The obtained controller parameters successfully perform their role to satisfy the control system design requirements.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.500-502
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• 1999

This thesis deals with study and implementation of a cross-coupling controller which can enhance the path-tracking performance of optically guided AGV(Automated Guided Vehicle). The AGV in this thesis is differential drive type and has front-side and rear-side optical sensors, which can identify the guiding path. When AGV from the path due to the inevitable error and the deviation must be corrected. It has been shown that compensation only the first term can lead to undesirable oscillatory results and even instability but compensating only the second term leads to a steady state offset error. Cross-coupling control directly minimizes the error by coordinating the motion of the two drive wheels. The cross-coupling controller is analyzed to evaluate its performance. The cross-coupling controller enhances transient performance of the controller is demonstrated by simulation and is compared with that of individual loop controller.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.285-289
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• 2013

In switching from the track-seeking or track-jumping control mode to track-following control mode in hard disk drives or optical disk drives, initial values of the feedback controller are tuned to improve the transient response. In general, all the initial values of the controller have been compensated for this purpose. In this paper, by partially compensating initial values of digital controllers, we achieve a good performance of the transient response. In the proposed method for IVC (Intial Value Compensation), LMIs (Linear Matrix Inequalities) are used, which includes conditions for improving the performance of the transient response such as reducing a tracking error and control efforts. We obtain optimal initial values of the controller by solving an optimization problem with constraints represented by only one LMI. Although initial values of the controller are partially compensated, we can show that not only a sufficient performance of the transient response is obtained but also control efforts are diminished. The feasibility of the method is verified by simulation studies.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.3
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• pp.25-30
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• 2005

Nonlinear optimal control problems lead to Hamilton-Tacobi equations which are not analytically solvable for most practical problems. This difficulty has led to the development of suboptimal nonlinear design techniques such as controller design based on feedback linearization(FL). In this paper, we present some simple examples where the optimal answer can be found for the optimal controller, FL controller and linear controller and determine its relative performance. As a result, we get the condition of a nonlinear system for the FL controller to an optimal design.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.680-687
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• 2012

One of the frequent problems in the stabilized gimbal system is the rejection of disturbances associated with moving components. Very often such disturbances have non-linear characteristics. In a typical gimbal system, each gimbal and platform are connected by a mutual bearing which induces inevitable friction. Particularly, the non-linear Coulomb friction causes position errors as well as slow responses that lead to unfavorable performance. In this paper, a modified PID controller that is augmented by Coulomb friction estimator is presented. Through constantly estimating the Coulomb friction torque, it is applied to the output of the existing PID controller. The effectiveness of the proposed controller is evaluated through a series of experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• Smart Structures and Systems
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• v.21 no.1
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• pp.99-111
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• 2018

Wind induced large bending oscillation amplitudes in tall and slender telecommunication steel towers may lead to precocious fatigue cracks and consequent risk of collapse of these structures, many of them installed in rural areas alongside highways and in highly populated urban areas. Varying stress amplitudes at hot spots may be attenuated by means of passive control mechanical devices installed in the tower. This paper gives an account of both mathematical-numerical model and the technique applied to design and evaluate the performance of a double controller installed in existing towers which is composed by a nonlinear pendulum and a novel type of passive controller described herein as a planar motion disk mounted on shear springs. Results of experimental measurements carried out on two slender tubular steel towers under wind action demonstrate the efficiency of the double controllers in attenuating the towers bending oscillation amplitudes and consequent stress amplitudes extending the towers fatigue life.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.795-797
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• 1995

In this paper, we present a simple auto-tuning PID controller using genetic algorithms. The basic idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a single parameter ${\alpha}$, then to use GA to select optimal tuning parameter. Also, simple rule mechanisms make the controller adapt against large variations in parametric and dynamics uncertainties in the plant. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with long delay-time and nonminimum phase systems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.11
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• pp.1072-1078
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• 2001

The real time optimal control algorithm of the DDC controller for chilled water and supply air temperature set-point of heating, ventilating, air-conditioning and refrigeration systems has been researched for minimization of the total power which is consumed by the chiller, chilled water pump and air handing unit fan. The study has been done by using TRNSYS program in order to analyze the central cooling system in terms of the environmental variables such as indoor cooling lead and wet-bulb temperature. This optimal control alogorithm saves more energy and is suitable for real time on-line control in comparison with conventional method.