• International Journal of Naval Architecture and Ocean Engineering
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• 제11권1호
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• pp.584-596
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• 2019

This paper presents a Modified Adaptive Complementary Sliding Mode Control (MACSMC) system for the longitudinal motion control of the Fully-Submerged Hydrofoil Craft (FSHC) in the presence of time varying disturbance and uncertain perturbations. The nonlinear disturbance observer is designed with less conservatism that only boundedness of the derivative of the disturbance is required. Then, a complementary sliding mode control system combined with adaptive law is designed to reduce the bound of stabilization error with fast convergence. In particularly, the modified complementary sliding mode surface which contains the estimation of the disturbance can reduce the switching gain and retain the normal performance of the system. Moreover, a hyperbolic tangent function contained in the control law is utilized to attenuate the chattering of the actuator. The global asymptotic stability of the closed-loop system is demonstrated utilizing the Lyapunov stability theory. Ultimately, the simulation results show the effectiveness of the proposed approach.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.758-771
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• 2021

This paper presents a novel control scheme for the three-dimensional (3D) path following of underactuated Autonomous Underwater Vehicle (AUVs) subject to unknown internal and external disturbances, in term of the time scale decomposition method. As illustration, two-time scale motions are first artificially forced into the closed-loop control system, by appropriately selecting the control gain of the integrator. Using the singular perturbation theory, the integrator is considered as a fast dynamical control law that designed to shape the space configuration of fast variable. And then the stabilizing controller is designed in the reduced model independently, based on the time scale decomposition method, leading to a relatively simple control law. The stability of the resultant closed-loop system is demonstrated by constructing a composite Lyapunov function. Finally, simulation results are provided to prove the efficacy of the proposed controller for path following of underactuated AUVs under internal and external disturbances.

• Ocean Systems Engineering
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• 제12권2호
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• pp.159-172
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• 2022

To ensure stable performance, adaptive regulators with new theories are designed for steel-covered offshore platforms to withstand anomalous wave loads. This model shows how to control the vibration of the ocean panel as a solution using new results from Lyapunov's stability criteria, an evolutionary bat algorithm that simplifies computational complexity and utilities. Used to reduce the storage space required for the method. The results show that the proposed operator can effectively compensate for random delays. The results show that the proposed controller can effectively compensate for delays and random anomalies. The improved prediction method means that the vibration of the offshore structure can be significantly reduced. While maintaining the required controllability within the ideal narrow range.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.100-104
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• 1998

This paper describes the real-time implementation of an adaptive controller fur the robotic manipulator. Digital signal processors(DSPs) are special purpose micro-processors that are particularly powerful for intensive numerical computations involving sums and products of variables. TMS320C50 chips are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the direct adaptive control theory. The adaptive controller consists of an adaptive feedforward controller and feedback controller. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a assembling robot.

• Structural Engineering and Mechanics
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• 제81권1호
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• pp.51-57
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• 2022

The problem of optimal stochastic GA control of the system with uncertain parameters and unsure noise covariates is studied. First, without knowing the explicit form of the dynamic system, the open-loop determinism problem with path optimization is solved. Next, Gaussian linear quadratic controllers (LQG) are designed for linear systems that depend on the nominal path. A robust genetic neural network (NN) fuzzy controller is synthesized, which consists of a Kalman filter and an optimal controller to assure the asymptotic stability of the discrete control system. A simulation is performed to prove the suitability and performance of the recommended algorithm. The results indicated that the recommended method is a feasible method to improve the performance of active tuned mass damper (ATMD) shear buildings under random earthquake disturbances.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 추계학술대회
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• pp.168-169
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• 2022

In this study, we investigates the auto-berthing problem for the underactuated surface vessel in the presence of constraints of dynamic uncertainties, finite time, transmission load, and environmental disturbance. A novel control scheme is proposed by fusing the finite time control technology and the event-triggered input algorithm. In the algorithm, differential homeomorphism coordinate the transformation is used to solve the problem of underactuation. Then, we apply the finite time technology and event triggered to save the time of the berthing vessel and relieve transmission burden between the controller and the vessel respectively. Moreover, a radial basis function network is used to approximate unknown nonlinear functions, and minimum learning parameters are introduced to lessen the computational complexity. A sufficient effort has been made to verify the stability of the closed-loop system based on the Lyapunov stability theory. Finally, simulation results display the effectiveness of the proposed scheme.

• Ocean Systems Engineering
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• 제14권1호
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• pp.73-84
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• 2024

In order to achieve the best performance, the automatic control with advanced technology is made of sheathed steel to withstand a wide range of wave loads. This model shows how to control the vibration of the fiber panel as a solution using the new results from the Lyapunov stability question, a modification of the bat that making it easy to calculate and easy to use. It is used to reduce the storage space required in this system. The results show that the planned worker can compensate effectively for the unplanned delay. The results show that the proposed controller can compensate for delays and errors. Fuzzy control (predictive control) demonstrated the external vibration can be reduced.

• 한국항해항만학회지
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• 제47권4호
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• pp.256-270
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• 2023

본 연구에서는 선박 또는 해양구조물에 설치되는 터렛(Turret)과 같이 제어 대상의 무게 중심 주변이 아닌 임의 지점을 운동 중심으로 선정하여 제어할 수 있는 동적위치유지(Dynamic positioning; DP)용 슬라이딩모드(Sliding mode) 제어기를 연구하였다. 이러한 슬라이딩모드 제어기는 선박 및 해양구조물 동역학 모델의 불확실성, 시공간에서 변화하는 미지의 해양환경에 의한 외력, DP 제어시스템의 과도 성능을 고려한 제어가 가능하다. 선박 및 해양구조물의 임의 지점을 기준으로 제어하기 위해 제어 대상의 기구학 방정식에 포함되는 자코비안(Jacobian) 행렬을 수정하여 슬라이딩모드 제어기를 설계하였다. 제어기의 강건성(Robustness)을 확보하기 위해 슬라이딩모드 제어기 설계에 리아프노프(Lyapunov) 안정도 판별 이론을 적용하였다. 일반적으로 DP 제어에서 제어기의 강건성 확보를 위해 PD(Proportional derivative) 제어 알고리즘 기반의 이득 스케줄링(Gain scheduling)을 사용한다. 그러나 이득 스케줄링을 적용하기 위한 적절한 이득을 찾는 것은 DP 시스템 적용을 복잡하게 만든다. 따라서 본 연구에서는 이러한 선박 및 해양구조물 DP 제어기의 복잡성을 해소하기 위해 슬라이딩모드 제어 알고리즘을 고려하였다. 제안된 슬라이딩모드 제어 알고리즘의 유효성을 검증하기 위해 시간 영역 시뮬레이션을 구현하였으며, 제어 알고리즘의 성능평가에 활용되었다. 제안된 슬라이딩모드 제어기의 유효성 검토를 위해 일반적인 PD 제어 알고리즘을 적용한 DP 제어 시뮬레이션 결과와 비교하였다.

• 지능정보연구
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• 제4권1호
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• Journal of Electrical Engineering and Technology
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• 제9권5호
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• pp.1686-1693
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• 2014

In this paper, oil-paper samples composed of transformer windings were used to investigate the insulation degradation process subjected to partial discharge (PD), with artificial defects inside to simulate the PD induced insulation degradation. To determine appropriate test voltages, the breakdown time obtained through a group of accelerated electrical degradation tests under high voltages was firstly fitted by two-parameter Weibull model to acquire the average breakdown time, which was then applied to establish the inverse power law life model to choose advisable test voltages. During the electrical degradation process, PD signals were synchronously detected by an ultra-high frequency (UHF) sensor from inception to breakdown. For PD analysis, the whole degradation process was divided into ten stages, and chaos theory was introduced to analyze the variation of three chaotic parameters with the development of electrical degradation, namely the largest Lyapunov exponent, correlation dimension and Komogorov entropy of PD amplitude time series. It is shown that deterministic chaos of PD is confirmed during the oil-paper degradation process, and the obtained results provide a new effective tool for the diagnosis of degradation of oil-paper insulation subjected to PD.