• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.137-146
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• 2001

A robust controller with the sliding mode is proposed for stable dynamic walking of the biped robot in this paper. For the robot system to be controlled, which is modeled as 14 DOF rigid bodies by the method of multi-body dynamics, the joint angle trajectories are determined by the velocity transformation matrix. Also Hertz force model and Hysteresis damping element are utilized for the ground reaction and impact forces during the contact with the ground. The biped robot system becomes unstable since those forces contain highly confused noise components and some discontinuity, and modeling uncertainties such as parameter inaccuracies. The sliding mode control is applied to solve above problems. Under the assumption of the bounded estimation errors on the unknown parameters, the proposed controller provides a successful way to achieve the stability and good performance in spite of the presence of modeling imprecisions of uncertainties.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.95-107
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• 2001

This paper is devoted to the parameter optimization of unmanned aerial vehicle's (UAV) flight control laws. Optimization procedure is based on the ideas of mixed $H_2/H_{\infty}$ control of multi-model plants. By using this approach, some partial $H_2$-terms defining the performance of nominal and parametrically perturbed Flight Control System (FCS) responses to deterministic command signals in stochastic atmosphere as well as $H_{\infty}$-terms defining robustness of the FCS can be incorporated in the composite cost function. Special penalty function imposed on the location of closed-loop system's poles keeps the speed of response and oscillatory properties for both nominal and perturbed FCS in reasonable limits. That is the reason why this procedure may provide reasonable trade-off between the performance and robustness of FCS that are very important especially for UAV. Its practical importance is illustrated by case studies of lateral and longitudinal control of small UAV.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.9
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• pp.997-1005
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• 1990

Integral Error and State Feedback (IESF) controller which incorporates state feedback as a modern control scheme and integral action as a classical control scheme has better performance than that of conventional PID controller in linear time invariant system. But the structure of the IESF controller requires all the state variables of the system and is applicable only to pole assignable linear time invariant systems without time delay. Many industrial processes have large time delay and it is impossible to directly apply IESF control scheme to those processes. In this paper, a new controller structure, Modified Integral Error and State Feedback (MIESF) has been suggested in order to effectively control processes having time delay and its performance has been analyzed and its effectiveness has also been confirmed. As the proposed controller uses output feedback scheme based on integral error and state feedback (IESF) method, it can be simply designed by pole assignment algorithm irrespective of the order of the process. The MIESF controller can follow setpoint changes without overshoot. It is robuster than conventional Smith-Predictor plus PI(D) controller in case of occurring time delay mismatch and extra parameter mismatches between the process and the model. It can enhance control performance by intentional time delay mismatch.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.353-362
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• 2006

This paper illustrates the practical design procedure on a position control of an electrical fin actuator for the guided missile using Time Delay Control(TDC) and Enhanced Time Delay Observer(ETDO). Since TDC is robust to the model uncertainties such as the parameter variation and the external disturbance, it has been frequently used in nonlinear control systems. For a position control of an electrical fin actuator in the missile system, TDC requires the velocity sensor as well as the position sensor. To resolve the problems of the cost, the space and the malfunction due to the velocity sensor, ETDO is used as the velocity observer. ETDO is enhanced version of TDO that has the problems of the reconstruction errors and the restriction on selecting its gains. To maximize the control performance, the parameters of ETDO are optimized by using the genetic algorithm. The effectiveness of this approach is proved through a series of simulation studies and experiments, and the designed controller is compared with the typical TDC and TDC using the reduced oder observer.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.429-434
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• 2016

This paper introduces a stabilization condition for polynomial fuzzy systems that guarantees $H_{\infty}$ performance under the imperfect premise matching. An $H_{\infty}$ control of polynomial fuzzy systems attenuates the effect of external disturbance. Under the imperfect premise matching, a polynomial fuzzy model and controller do not share the same membership functions. Therefore, a polynomial fuzzy controller has an enhanced design flexibility and inherent robustness to handle parameter uncertainties. In this paper, the stabilization conditions are derived from the polynomial Lyapunov function and numerically solved by the sum-of-squares (SOS) method. A simulation example and comparison of the performance are provided to verify the stability analysis results and demonstrate the effectiveness of the proposed stabilization conditions.

• Journal of Power Electronics
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• v.4 no.4
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• pp.217-227
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• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.908-925
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• 2014

Induction Motor (IM) has several desirable features for high performance adjustablespeed operation. This paper presents the design of a robust controller for vector control induction motor drive performances improvement. Proposed predictive speed controller, which is aimed to guarantee the stability of the closed loop, is based on the Poisson-Laguerre (PL) models for the association vector control drive and the induction motor; without necessity of any mechanical parameter, and requires only two control parameters to ensure implicitly the integrator effect on the steady state error, load torque disturbances rejection and anti-windup effect. In order to improve robustness, insensitivity against external disturbances and preserve desired performance, adaptive control is added with the aim to ensure an online identification of controller parameters through an online PL models identification. The proposed control is compared with the conventional approach using PI controller. Simulation with MATLAB/SIMULINK software and experimental results for a 1kW induction motor using a dSPACE system with DS1104 controller board are carried out to show the improvement performance.

• Journal of Power System Engineering
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• v.15 no.5
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• pp.91-96
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• 2011

The handling ability of containers at the terminal strongly depends on the performance of the cargo handling system such as RTGC(Rubber Tired Gantry Crane) and RMGC(Rail Mounted Gantry Crane). This paper introduces a guide line measurement system on the operating condition, in which two camera are installed to detect the guide line. Because the line tracking is the basic technique for control system design of RTGC, it is necessary to develop a useful and reliable measurement system. If the displacement and angle of the RTGC relative to a guide line as the trajectory to follow is obtained, the position of RTGC is automatically calculated. Therefore, in this paper, a camera-based measurement system is introduced. The proposed measurement system is robust against light fluctuation and cracks of the guide line. This system consists of two camera and a PC which are installed at the lower side of the RTGC. Two edges of the guide line are detected from an input image taken by the cameras in the moving state, and these positions are determined in a Hough parameter space by using the Hough transformation method. From the experimental results, the accuracy and usefulness of the proposed system is evaluated by comparing other instruments.

• Smart Structures and Systems
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• v.31 no.1
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• pp.69-78
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• 2023

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

• Geomechanics and Engineering
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• v.31 no.3
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• pp.265-279
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• 2022

Tunnel convergence prediction is essential for the safe construction and design of tunnels. This study proposes five machine learning models of deep neural network (DNN), K-nearest neighbors (KNN), Gaussian process regression (GPR), support vector regression (SVR), and decision trees (DT) to predict the convergence phenomenon during or shortly after the excavation of tunnels. In this respect, a database including 650 datasets (440 for training, 110 for validation, and 100 for test) was gathered from the previously constructed tunnels. In the database, 12 effective parameters on the tunnel convergence and a target of tunnel wall convergence were considered. Both 5-fold and hold-out cross validation methods were used to analyze the predicted outcomes in the ML models. Finally, the DNN method was proposed as the most robust model. Also, to assess each parameter's contribution to the prediction problem, the backward selection method was used. The results showed that the highest and lowest impact parameters for tunnel convergence are tunnel depth and tunnel width, respectively.