• Smart Structures and Systems
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• v.20 no.2
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.543-547
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• 1994

In this paper, the new approach and technique are introduced and derived from the original Lyapunov direct method which is used to decide the stability of system conveniently. This proposed technique modifies the formal concepts of the sufficient conditions of Lyapunov stability and is able to generate the methods for the robust design of control systems. Also, it applies to the dynamic systems with bounded perturbations and the results of the computer program using the new concept are compared with those of previous research papers and conventional Lyapunov direct method. It is possible to recognize the practical improvements of the estimation of robustness bounds of the systems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.125-130
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• 1997

In this paper, it is presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C3x is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, andsuitable for implementation of robust control.

• Smart Structures and Systems
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• v.6 no.1
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• pp.57-72
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• 2010

This paper presents the most significant results obtained within a broad-ranging experimental program aiming to evaluate both the effectiveness and the robustness of a Base Isolation (BIS) and a Tuned Mass Damper (TMD) combined control strategy (BI & TMD). Following a brief description of the experimental model set-up and the adopted kinematic scaling technique, this paper describes the identification procedures carried out to characterize the system''s model. The dynamic response of a small-scale model to recorded earthquake excitations, which has been scaled by using the Buckingham pi-theorem, are later presented and discussed. Finally, the effectiveness and robustness of the combined control strategy is evaluated by comparing the model's dynamic response. In particular, reduction in relative displacements and absolute accelerations due to the application of different mass damping systems is investigated.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.11
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• pp.563-567
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• 2001

ln this paper, the designed DVSC(Discrete Variable Structure Controller) is applied to the robust control of voltage controlled APF(Active Power Filter). The voltage controlled APF has good characteristics of reducing harmonic current and harmonic voltage simultaneously. However, voltage controlled APF with large capacitor has slow dynamic response. For improving the dynamics and robustness against to disturbances, DVSC is adopted. According to the results of experiment and simulation, it is proved that the proposed system has the performance of improving dynamic response and robustness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.835-840
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• 2010

This study develops a variable structure controller using nonlinear surface instead of the fixed, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. reaching time of the system trajectory is faster than the fixed method. This proposed scheme has better performance than the conventional method in reaching time, parameter variation and extraneous disturbance. The effectiveness of the proposed control scheme is verified by simulation results.

• Journal of Power Electronics
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• v.17 no.4
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• pp.983-990
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• 2017

This paper proposes a model predictive control based on the discrete Lyapunov function to improve the performance of power electronic converters. The proposed control technique, based on the finite control set model predictive control (FCS-MPC), defines a cost function for the control law which is determined under the Lyapunov stability theorem with a control error compensation. The steady state and dynamic performance of the proposed control strategy has been tested under a single phase AC/DC voltage source rectifier (S-VSR). Experimental results demonstrate that the proposed control strategy not only offers global stability and good robustness but also leads to a high quality sinusoidal current with a reasonably low total harmonic distortion (THD) and a fast dynamic response under linear loads.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1504-1508
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• 1996

In this paper, we derive dynamic equation of helicopter and design controller based on variable structure system. It is difficult to control helicopter because it has non-linear coupling between input and output of system and is MIMO system. The design of control law is considered here using variable structure methodology giving the robustness to parameter variations and invariance to some subsets of external disturbance. However we derive dynamic equations of helicopter and design stabilizing variable structure controller. Also, simulation results are given in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1113-1119
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• 1989

Neural network control has many innovative potentials for intelligent adaptive control. Among many, it promises real time adaption, robustness, fault tolerance, and self-learning which can be achieved with little or no system models. In this paper, a dynamic robot controller has been developed based on a backpropagation neural network. It gradually learns the robot's dynamic properties through repetitive movements being initially trained with a PD controller. Its control performance has been tested on a simulated PUMA 560 demonstrating fast learning and convergence.