• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1202-1209
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• 2018

This paper is concerned with the problem of setting controller's parameters when applying the intelligent PID (i-PID), which has recently been proposed and had many successful results, to the two-degree-of-freedom (2DoF) PID controller structure. Generally, the parameter settings of conventional PID controllers are known to be quite difficult and be dependent on the characteristics of the plants. In addition, it is less known how the two 2DoF parameters are set up for the improvement of transient characteristics. Here, we are going to present one of the criteria for parameter setting in the case of using a 2DoF i-PID, by evaluating the error signals to the set-point and disturbance. That is, we first, obtain parameters of i-PID by optimizing the disturbance responses, and then determine two parameters of 2DoF component through optimizing set-point response. The standard values of all parameters are calculated for the 7 types of test batches and rounded up as a table.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.1
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• pp.5-13
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• 2014

Number of components and payload systems installed in satellites were found to be exposed to various disturbance sources such as the reaction wheel assembly, the control moment gyro, coolers, and others. A micro-level of vibration can introduce jitter problems into an optical payload system and cause significant degradation of the image quality. Moreover, the prediction of on-orbit vibration effects on the performance of optical payloads during the development process is always important. However, analyzing interactions between subsystems and predicting the vibration level of the payloads is extremely difficult. Therefore, this paper describes the analytical and experimental approach to microvibration effects on satellite optical payload performance with integrated jitter analysis frame-work, microvibration emulator and satellite structure testbed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.407-412
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• 2004

This paper presents a new algorithm for the closed-loop $H_{\infty}$ composite control of singularly perturbed nonlinear systems with a exogenous disturbance, using the successive Galerkin approximation(SGA). The singularly perturbed nonlinear system is decomposed into two subsystems of a slow-time scale and a fast-time scale via singular perturbation theory, and two $H_{\infty}$ control laws are obtained to each subsystem by using the SGA method. The composite control law that consists of two $H_{\infty}$ control laws of each subsystem is designed. One of the purposes of this paper is to design the closed-loop $H_{\infty}$ composite control law for the singularly perturbed nonlinear systems via the SGA method. The other is to reduce the computational complexity when the SGA method is applied to the high order systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.58-64
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• 1997

FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the intialized value is excellent. In case an unknown process or the mathematical modeling of a complicated system is impossible, a fit control quantity can be acquired by the Fuzzy inference. But FLC can not converge correctly to the desirable value because the FLC's output value by the size of the quantization level of the Fuzzy variable always has a minor error. There are many ways to eliminate the minor error, but I will suggest GA-FLC and EP-FLC Hybrid controller which csombines FLC with GA(Genetic Algorithm) and EP(Evo1ution Programming). In this paper, the output characteristics of this Hybrid controller will be compared and analyzed with those of FLC, it will he showed that this Hybrid controller converge correctly to the desirable value without any error, and !he convergence speed performance of these two kinds of Hyhrid controller also will be compared.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.135-142
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• 2005

This paper presents an adaptive repetitive control scheme for optical disk drives to track a variable periodic reference signal. Periodic disturbances can be adequately attenuated using the concept of repetitive control, provided the period is known. Because optical disk drives support various speeds, they have the varying periodic disturbances. Based on repetitive control to change sampling frequency to follow the change of reference period, an adaptive repetitive control is proposed in order to deal with such disturbances. The proposed control consists of the repetitive controller and the frequency generator. The former uses a varying sampler operating at fixed multiple times of the disturbance frequency and the latter generates the changeable sampling frequency based on the disturbance frequency. The experimental results on the control of an optical disk drive demonstrate the effectiveness of the proposed schemes and the improvement of random access time as well.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.85-92
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• 2017

Recently, electric propulsion systems are used for unmanned surface vehicle, fish finder boat, etc. Some of these propulsion systems can be constructed of two electric motors and propellers for advanced impellent force. In this case, the speed difference generated between two propellers, namely, the synchronous error has a bad influence on the energy efficiency and course error. In this study, a synchronous control system is designed to restrain synchronous error caused by disturbance and mismatched dynamic characteristics. The control system is composed of the reference model, pre-filters, speed controllers, and synchronous controllers. The reference model is used for calculating the decoupled synchronous error and control input for each propulsion system. The pre-filters and speed controllers are designed in order that the propulsion system may follow the reference signal without overshoot and input saturation. And the synchronous controllers are designed from the viewpoint of stable and quick synchronization through root locus mothed approach. Finally, the simulation results show that the designed control system is effective for the disturbance.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.41-49
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• 2014

Detection and processing techniques for small objects on seabed by the active synthetic aperture sonar can be increased the detection performance because it can be used by short sensor array in small unmanned underwater systems that are spatially constrained. But the limited conditions on constant speed and straight movement of the platform cause a large error in the number of external environmental factors and exact phase synthesis process. In this study, analyzed the applicability of active synthetic aperture processing that is mounted on such a system, and compared detection resolution change in accordance with the phase difference mismatch caused by the along track disturbance. Various simulations were performed as a coherently focus processing model by adding along track disturbance mismatched parameter on the configuring simulator. As the result, detection performance of active synthetic processing for small objects on seabed was found a number of changes by the phase difference mismatch errors according to track disturbances and S/N ratio variations.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.453-459
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• 2008

The neural network is currently being used throughout numerous control system fields. However, it is not easy to obtain an input-output pattern when the neural network is used for the system of a single feedback controller and it is difficult to obtain satisfactory performance with when the load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object for control and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The real plant object for controlling of this mode implements a simple neural network controller replacing the activation function and provides the error back propagation path to calculate the error at the output node. As the controller is designed using a simple structure neural network, the input-output pattern problem is solved naturally and real-time learning becomes possible through the general error back propagation algorithm. The new algorithm applied neural network controller gives excellent performance for initial and tracking response and shows a robust performance for rapid load change and disturbance, in which the permissible error surpasses the range border. The effect of the proposed control algorithm was verified in a test that controlled the speed of a motor equipped with a high speed computing capable DSP on which the proposed algorithm was loaded.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.387-392
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• 2020

This paper proposes a flow-rate control system for industrial valves. Industrial valves are used in piping systems to control the flow rate and pressure. In general, valves used in pipelines are classified into globe valves, butterfly valves, and ball valves according to the shape. Motor, hydraulic, and pneumatic systems are used for operating valves. The flow meter should measure the flow rate when configuring the flow-rate control system. On the other hand, because the flow rate of the valve can be expressed by flow coefficient, a control scheme is proposed using the pressure deviation, which measures at the front and rear of the valve. The transfer function for the valve, according to the control input, was estimated using the signal compression method. Based on the induced transfer function, the disturbance observer was designed to improve the command following the performance of the valve stem. The performance of the proposed control method is compared with the flow-rate control result using the flow meter used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.