• 한국자동차공학회논문집
• /
• 제8권6호
• /
• pp.142-155
• /
• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• 한국해양공학회지
• /
• 제16권1호
• /
• pp.8-15
• /
• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• International Journal of Control, Automation, and Systems
• /
• 제2권3호
• /
• pp.374-383
• /
• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• Wind and Structures
• /
• 제36권3호
• /
• pp.215-220
• /
• 2023

We study the progressive full-scale wind tunnel tests on a high solidity vertical axis wind turbine (VAWT) for various tip speeds and pitch angles to understand the VAWT shaft system's dynamics using 0-1 Test for chaos. We identify that while varying rotor speed (tip speed) of the turbine, the system's dynamics change from periodic to chaotic through quasiperiodic and strange non-chaotic (SNA) states. The present study is the first experimental evidence for the existence of these states in the VAWT shaft system to the best of our knowledge. Using the asymptotic growth value Kc in 0-1 test, when the turbine operates at the low tip speeds and high pitch angles for low incoming wind speeds, the system behaves periodic (Kc ≈ 0). However, when the incoming wind speed increases further the system's dynamics shift from periodic to chaotic vibrations through quasi-periodic and SNA. This phenomenon is due to the dynamic stalling of blades which induces chaotic vibration in the VAWT shaft system. Further, the singular continuous spectrum method validates the presence of SNA and differentiates the SNA from chaotic vibrations.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.574-578
• /
• 2004

In this paper, a nonlinear feedback system is analyzed for a surface micromachined resonant accelerometer. For this, a brief illustration of the plant dynamics is given. In the analysis, the periodic signal in the nonlinear feedback loop is obtained by the limit cycle point, which is best approximated via the describing function method. Considering the characteristic feature of plant dynamics, a simple phase shifted relay with finite slope is designed for the nonlinearity implementation. With a describing function for random plus sinusoidal input, we analyzed the effect of a white Gaussian noise on oscillation frequency. Finally, simulation and experimental result is given.

• 한국유체기계학회 논문집
• /
• 제16권2호
• /
• pp.42-47
• /
• 2013

Ship stability prediction is very complex in reality. In this paper, risk based approach is applied to predict the probability of a certified ship, which is effected by the forces of sea especially the wave loading. Safety assessment and risk analysis process are also applied for the probabilistic prediction of ship stability. The survival probability of ships encountering with different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.

• 전기학회논문지
• /
• 제67권2호
• /
• pp.261-269
• /
• 2018

In this paper, we propose a Takagi-Sugeno (T-S) fuzzy-model-based design for the tracking control of a class of nonlinear underwater glider. By using the partial linearization and the sector nonlinearity, the underwater glider with six degrees of freedom (6 DOF) is modelled by the T-S fuzzy model. The concerned tracking control problem with $H_{\infty}$ performance is converted into the stabilization one for the error dynamics between the given nonlinear underwater glider and the reference time-varying input. Sufficient conditions are derived for the asymptotic stabilizability of the error dynamics in the format of matrix inequality. Simulation results demonstrate the effectiveness of the proposed design methodology.

• Journal of Information Processing Systems
• /
• 제14권2호
• /
• pp.455-468
• /
• 2018

The concepts of graph theory are applied to model and analyze dynamics of computer networks, biochemical networks and, semantics of social networks. The analysis of dynamics of complex networks is important in order to determine the stability and performance of networked systems. The analysis of non-stationary and nonlinear complex networks requires the applications of ordinary differential equations (ODE). However, the process of resolving input excitation to the dynamic non-stationary networks is difficult without involving external functions. This paper proposes an analytical formulation for generating solutions of nonlinear network ODE systems with functional decomposition. Furthermore, the input excitations are analytically resolved in linearized dynamic networks. The stability condition of dynamic networks is determined. The proposed analytical framework is generalized in nature and does not require any domain or range constraints.

• Journal of applied mathematics & informatics
• /
• 제26권3_4호
• /
• pp.739-750
• /
• 2008

A phenomenon which is seen in some of the manufacturing systems and production planning is chaos and the butterfly effect. The butterfly effect points out that in case of the presence of nonlinear relations in system and incorrect estimation of initial values of variables, the error in the estimates of system state will be intensified, and after a while there will be a large distance between available state of system and reality. Using mathematical means and computer simulation, we have tried to demonstrate that in a production system the numerical combination of Cycle Time (CT), Adjustment Time between existing and desired Work In Progress (WIP), and Adjustment Time between current and desired inventory can lead to chaos and butterfly effect in the behavior of the inventory state variable. Our paper concludes with a discussion of a hypothesis that emerged from this research.

• 소음진동
• /
• 제6권5호
• /
• pp.653-660
• /
• 1996

There have been many studies to control holonomic and/or nonholonomic systems, and nonlinear control problems. However, their approaches require complicated intermediate procedures. Using the Generalized Inverse Method derived by Udwadia and Kalaba in 1992, this study provides two applications to the control of holonomically and/or nonholonomically constrained systems. These applications illustrate the ease with which the equation by the Generalized Inverse Method can be utilized for the purpose of (a) control of highly nonlinear systems without depending on any linearization, (b) maintaining precision tracking motions with the presence of known disturbances, and (c) explicit determination of control forces under the circumstances (a) and (b).