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

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.71-80
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• 2007

A control approach for the sensorless speed control of interior permanent magnet synchronous motor(IPMSM) based on adaptive integral the binary is proposed. With a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. However, the width of the constant boundary limits the steady state estimation accuracy and robustness. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral augmented switching the hyperplane equation. By mean of integral characteristics, the rotor speed can be finely estimated and utilized for a sensorless speed controller for IPMSM. The proposed adaptive integral binary observer applies an adaptive scheme, because the parameters of the dynamic equations such as the machine inertia or the viscosity friction coefficient is not well known and these values can be easily changed generally during normal operation. Therefore, the observer can overcome the problem caused by using the dynamic equations, and the rotor speed estimation is constructed by using the Lyapunov function. The experimental results of the proposed algorithm are presented to demonstrate the effectiveness of the approach.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.70-77
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• 2005

This paper presents sensorless speed control of a cylindrical permanent magnet synchronous motor (PMSM) using the adaptive integral binary observer. In view of the composition with a main loop regulator and an auxiliary loop regulator, the normal binary observer has the feature of chattering alleviation in the constant boundary layer. However, the steady state estimation accuracy and robustness are dependent upon the thickness of the constant boundary layer. In order to improve the steady state performance of the binary observer, a new binary observer is formed by the addition of extra integral dynamics to the existing switching hyperplane equation. Also, because the parameters of the dynamic equations such as machine inertia or viscosity friction coefficient are not well known and these values can be changed during normal operations, there are many restrictions in the actual implementation. The proposed adaptive integral binary observer applies an adaptive scheme so that the observer may overcome the problems caused by using dynamic equations. The rotor speed is constructed by using the Lyapunov function. The observer structure and its design method are described. The experimental results of the proposed algorithm are presented to prove the effectiveness of the approach.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.495-508
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• 1995

The self-excited vibrations of airfoil is related to the classical flutter problems, and it has been studied as a system with linear stiffness and small damping. However, since the actual aircraft wing and the many mechanical elements of airfoil type have various design variables and parameters, some of these could have strong nonlinearities, and the nonlinearities could be unexpectedly strong as the parameters vary. This abrupt chaotic behavior undergoes ordered routes, and the behaviors after these routes are uncontrollable and unexpectable since it is extremely sensitive to initial conditions. In order to study the chaotic behavior of the system, three parameters are considered, i.e., free-stream velocity, elastic distance and zero-lift angle. If the chaotic parameter region can be identified from the mathematically modeled nonlinear differential equation system, the designs which avoid chaotic regions could be suggested. In this study, by using recently developed dynamically system methods, and chaotic regions on the parameter plane will be found and the safe design variables will be suggested.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.73-82
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• 1992

An industrial robot, installed real manufacturing processes an element of the system autmation, can be considered as an uncertain system due to dynamic uncertainties in inertial parameters and varying payloads. Most difficuties in controlling a robot manipulator are caused by the fact that the dynamic equations describing the motions of the manipulator are inherently nonlinear and heavily coupled effects between joints and associated links. Existing robot conrol systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severly limited in range of application, speed of operation and variation of payload. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the desinger. The proposed manipulator studied has two loops, an inner loop of model reference adaptive controller and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstailiy approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in practical working environment, various load variations and parameter uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.6-11
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• 2014

Repetitive control is a specialized control scheme to track and/or attenuate a periodic reference trajectory and/or disturbance. Most researches about repetitive control have been performed in the frequency domain. Recently, several approaches to deal with repetitive control systems in the state space are developed by representing a q filter as a state-space equation. This paper presents a design method of a repetitive control system in the state space to satisfy $H_{\infty}$ performance. The overall system is composed of a plant, a repetitive controller, and a state-feedback controller, which can be converted to a standard form used in $H_{\infty}$ control. A LMI (Linear Matrix Inequality)-based stability condition is derived for fixed state-feedback gains. Under a given q filter, another LMI condition is derived to improve $H_{\infty}$ performance and is employed to find state-feedback gains by solving an optimization problem. Finally, to verify the feasibility of the proposed method, a numerical example is demonstrated.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.4
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• pp.85-102
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• 1990

Up to now, most robot control systems are very naive. They consist of a number of independent position-servo loops to control each joint angle separately. Those control systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severely limited in range of application, speed of operation and variation of payload. This study proposed a new method to design a robot manipulator controller capable of tracking the reference trajectories of joint angles in a reasonable accuracy to cope with actual situations of varying payload, uncertain parameters. The adaptive model following control method has been used to improve existing robot manipulator controllers. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the designer. The stability of adaptive controller is based on the Second Method of Lyapunov. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance under various load varia- tion and parameter uncertainties.

• Journal of Power Electronics
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• v.16 no.2
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• pp.598-609
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• 2016

The good control performance of permanent magnet linear synchronous motor (LSM) drive systems is difficult to achieve using linear controllers because of uncertainty effects, such as fictitious forces. A backstepping control system using adaptive modified recurrent Laguerre orthogonal polynomial neural network uncertainty observer (OPNNUO) is proposed to increase the robustness of LSM drive systems. First, a field-oriented mechanism is applied to formulate a dynamic equation for an LSM drive system. Second, a backstepping approach is proposed to control the motion of the LSM drive system. With the proposed backstepping control system, the mover position of the LSM drive achieves good transient control performance and robustness. As the LSM drive system is prone to nonlinear and time-varying uncertainties, an adaptive modified recurrent Laguerre OPNNUO is proposed to estimate lumped uncertainties and thereby enhance the robustness of the LSM drive system. The on-line parameter training methodology of the modified recurrent Laguerre OPNN is based on the Lyapunov stability theorem. Furthermore, two optimal learning rates of the modified recurrent Laguerre OPNN are derived to accelerate parameter convergence. Finally, the effectiveness of the proposed control system is verified by experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.697-702
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• 2016

To control permanent magnet synchronous motors smoothly, it is important to know the exact parameter values of the stator resistance, various inductances, and the flux linkage of the permanent magnet. In practice, these parameters vary due to a variable operating point, temperature change, or a fault. This paper proposes a MRAS (Model Reference Adaptive System) based parameter estimator and adaptive control scheme. Owing to the non-linearity of the system equation with respect to these parameters, although many schemes proposed previously assumed that some parameters are known, all the parameters were assumed to be unknown. The simulation results revealed the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.50-55
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• 2016

This paper discusses a sampled-data controller design problem for nonlinear systems including singular perturbation. The concerned system is assumed to be modeled in Takagi--Sugeno (T--S) form. By introducing a novel Lyapunov function and an identity equation, the stability of the sampled-data closed-loop dynamics of the singularly perturbed T--S fuzzy system is analyzed. The design condition is represented in terms of linear matrix inequalities. A few discussions on the development are made that propose future research topics. Numerical simulation shows the effectiveness of the proposed method.