• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.2
• /
• pp.175-184
• /
• 1996

In this paper the newly developed discrete-time adaptive sliding mode control method is proposed and applied to the power system stabilization problem. In contrast to the conventional continuous-time sliding mode controller, the proposed method is developed in the discrete-time domain and based on the input/output measurements instead of the continuous-time and the full-states feedback, respectively. Because the proposed control method has the adaptivity property in addition to the natural robustness property of the sliding mode control, it is possible to design the power system stabilizer which can overcome both the minor variations of the parameters of the power system and the diverse operating conditions and faults of the power system. Mathematical proof and the various computer simulations are done to verify the performance and stability of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.807-810
• /
• 1997

Digital control of robot manipulator employs discrete-time robot models. It is important to explore effective discrete-time robot models and to analyze their properties in control system designs. This paper presents a new type discrete-time robot model. The model is derived by using trapezoid rule to approximate the convolution integral term, then eliminating nonlinear force terms from robot dynamical equations. The new model obtained has very simple structure, and owns the properties of independence to the nonlinear force terms. According to evaluation criteria, three aspects of the model properties: model accuracy, model validity range and model simplicity are examined and compared with commonly used discrete-time robot models. The validity of the proposed model and its advantages to control system designs are verified by simulation results.

• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.4
• /
• pp.45-52
• /
• 2011

In the real-field of control cases for robot manipulators, there always exists a modeling error, which results the model has the uncertainties in its parameters and/or structure. In many modem applications, digital computers are extensively used to implement control algorithms to control such systems. The discretization of the nonlinear dynamic equations of such systems results in a complicated discrete dynamic equations. Therefore, it will be difficult to design a discrete-time controller to give good tracking performances in the presence of certain uncertainties. In this paper, a discrete-time sliding mode control algorithm for nonlinear and time varying robot manipulators with uncertainties is presented. Sufficient conditions for guaranteeing the convergence of the discrete-time SMC system are derived. As example simulations, the proposed SMC algorithm is applied to a two-link robotic manipulator with unknown dynamics. The results of the simulation indicate that the developed control scheme is effective in manipulators and electro-mechanical system control.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.2
• /
• pp.112-124
• /
• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Journal of Advanced Marine Engineering and Technology
• /
• v.24 no.1
• /
• pp.94-103
• /
• 2000

This paper describes the model identification and the discrete-time sliding mode control of electro-hydraulic servo systems which are composed of servo valves, double-rod cylinder and load mass. The controlled plant is identified as a 3th-order discrete-time ARMAX model obtained from the prediction error algorithm, where a nominal model and modeling errors are zuantitatively constructed. The discrete sliding mode controller for 3th-order ARMAX model is designed in discrete-time domain, where all states are observed from Kalman filter. The discrete sliding mode controller has better tracking performance than that obtained from continuous-time sliding mode controller, in experiment.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1414-1417
• /
• 2003

In this paper, sliding mode controller for discrete-time nonlinear systems with uncertainties and disturbances are proposed. The concept of time-delay control (TDC) which consists of estimating the uncertain dynamics of the system through past observations of the system response is used. The proposed controller guarantees that the closed-loop system states are globally uniformly ultimately bounded (GUUB). It is also shown that the closed-loop system states are globally uniformly asymptotically stable (GUAS) if uncertainties are constant.

• Journal of the Society of Naval Architects of Korea
• /
• v.45 no.6
• /
• pp.656-668
• /
• 2008

When it comes to design and acquire underwater vehicles such as a submarine and a torpedo according to the process of SBA(Simulation Based Acquisition)/SBD(Simulation Based Design), it is necessary to predict the performance of interest precisely and to perform the test over and over again using the M&S(Modeling and Simulation) of the engineering and the engagement level. In this paper, we research the DEVS(Discrete Event System Specification) and DTSS(Discrete Time System Specification) formalism based standard model architecture for the underwater vehicle which can support both the heterogeneous level of the M&S(Engineering/Engagement) and the different system of the M&S(Discrete Event System and Discrete Time System). To validate this standard modeling architecture, we apply it to the submarine normal diving simulation.

• Journal of Power System Engineering
• /
• v.9 no.4
• /
• pp.175-180
• /
• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.2
• /
• pp.147-153
• /
• 2007

The stability robustness problem of linear discrete-time systems with delayed time-varying perturbations is considered. Compared with continuous time system, little effort has been made for the discrete time system in this area. In the previous results, the bounds were derived for the case of non-delayed perturbations. There are few results for delayed perturbation. Although the results are for the delayed perturbation, they considered only the time-invariant perturbations. In this paper, the sufficient conditions for stability can be expressed as linear matrix inequalities(LMIs). The corresponding stability bounds are determined by LMI(Linear Matrix Inequality)-based algorithms. Numerical examples are given to compare with the previous results and show the effectiveness of the proposed results.

• Journal of Advanced Navigation Technology
• /
• v.18 no.5
• /
• pp.501-507
• /
• 2014

A dynamic system is called positive if any trajectory of the system starting from non-negative initial states remains forever non-negative for non-negative controls. In this paper, new sufficient conditions for asymptotic stability of the interval positive time-varying linear discrete-time systems with time-varying delay in states are considered. The considered time-varying delay time has an interval-like bound which has minimum and maximum delay time. The proposed conditions are established by using a solution bound of the Lyapunov equation and they are expressed by simple inequalities which do not require any complex numerical algorithms. An example is given to illustrate that the new conditions are simple and effective in checking stability for interval positive time-varying discrete systems.