• Journal of Institute of Control, Robotics and Systems
• /
• 제20권3호
• /
• pp.323-332
• /
• 2014

Stepper motor is widely used in positioning applications due to its durability and high torque to inertia ratio as well as low cost and ability to be easily controlled with open-loop. Due to increased resolution of position control and improved stability of motion control, microstepping has drawn attention in industry since it was introduced in 1970s. With the increase in computational power and decrease in cost of embedded processors in recent years, drives and control systems for stepper motors have become more sophisticate than ever. Thus, closed-loop control methods have been developed to improve the performance of the stepper motors. In this paper, we review not only basic principles of conventional control methods used for stepper motors but also that of microstepping control. In addition, we surveyed recent development in nonlinear control methods applied to stepper motors. The nonlinear control methods are presented in the view of Lyapunov stability. Nonlinear torque disturbance observer, sliding mode control, and nonlinear phase compensation are also presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
• /
• pp.60-63
• /
• 1996

This study deals with the nonlinear H$_{\infty}$ control problem of linear system using nonlinear weight. Generally the solvable condition of nonlinear H$_{\infty}$ control problem is given by the Hamilton Jacobi equality or inequality, but it is very difficult to solve. In this study, some constraints of nonlinear weight reduce the solvable condition to linear Riccati equation. Some examples of the control system design using nonlinear weight are shown.n.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.979-984
• /
• 2005

In this study, we suggest a tilt rotor aircraft and attempt to apply a nonlinear model matching control method for its maneuver. The proposed method is very simple and useful to construct the control law for the complicated nonlinear system such as aircraft motion.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.384-384
• /
• 2000

In adaptive neuro-control, neural networks are used to approximate the unknown plant nonlinearities. Until now, most of the papers in the field of controller design fur nonlinear system using neural networks considers the affine system with fixed number of neurons. This paper considers nonaffne nonlinear systems and dynamic variation of the number of neurons. Control laws and adaptive laws for weights are established so that the whole system is stable in the sense of Lyapunov.

• Proceedings of the KIEE Conference
• /
• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
• /
• pp.675-677
• /
• 2004

This paper presents a nonlinear controller design for optical disk drive systems to improve anti-shock performance. The nonlinear anti-shock controller is added parallel to the original linear servo control loop. In the previous work, dead-zone nonlinear element is used for nonlinear controller and PID control method is used for linear controller. Although this strategy improves anti-shock performance, it has a narrow stability bound. In this paper, we propose dead-zone with saturation nonlinear element for the nonlinear controller. Since this nonlinear element improves stability margin, we can use higher gain of dead-zone than the controller with dead-zone only. In the linear controller design, we show that lead-lag control has improved stability margin over PID control. Numerical simulation results show that the proposed method can get better performance to the external shock than previously proposed method.

• Transactions on Control, Automation and Systems Engineering
• /
• 제2권3호
• /
• pp.175-181
• /
• 2000

This paper investigates the robust nonlinear H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for nonlinear discrete time-varying uncertain systems represented by the state-space model having parameter uncertainty. Firstly, when there is no parameter uncertainty in the system, the discrete-time nominal nonlinear H$_{\infty}$ FIR filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, which corresponds to the standard nonlinear H$_{\infty}$ filter. Secondly, when the system has the parameter uncertainty, the robust nonlinear H$_{\infty}$ FIR filter is proposed for the discrete-time nonlinear uncertain systems.

• Journal of Institute of Control, Robotics and Systems
• /
• 제15권9호
• /
• pp.929-938
• /
• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• Smart Structures and Systems
• /
• 제5권1호
• /
• pp.69-79
• /
• 2009

A non-clipped semi-active stochastic optimal control strategy for nonlinear structural systems with MR dampers is developed based on the stochastic averaging method and stochastic dynamical programming principle. A nonlinear stochastic control structure is first modeled as a semi-actively controlled, stochastically excited and dissipated Hamiltonian system. The control force of an MR damper is separated into passive and semi-active parts. The passive control force components, coupled in structural mode space, are incorporated in the drift coefficients by directly using the stochastic averaging method. Then the stochastic dynamical programming principle is applied to establish a dynamical programming equation, from which the semi-active optimal control law is determined and implementable by MR dampers without clipping in terms of the Bingham model. Under the condition on the control performance function given in section 3, the expressions of nonlinear and linear non-clipped semi-active optimal control force components are obtained as well as the non-clipped semi-active LQG control force, and thus the value function and semi-active nonlinear optimal control force are actually existent according to the developed strategy. An example of the controlled stochastic hysteretic column is given to illustrate the application and effectiveness of the developed semi-active optimal control strategy.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.460-465
• /
• 2004

In this paper, we present some properties on receding horizon $H_{\infty}$ control for nonlinear discrete-time systems. First, we propose the nonlinear inequality condition on the terminal cost for nonlinear discrete-time systems. Under this condition, noninceasing monotonicity of the saddle point value of the finite horizon dynamic game is shown to be guaranteed. We show that the derived condition on the terminal cost ensures the closed-loop internal stability. The proposed receding horizon $H_{\infty}$ control guarantees the infinite horizon $H_{\infty}$ norm bound of the closed-loop systems. Also, using this cost monotonicity condition, we can guarantee the asymptotic infinite horizon optimality of the receding horizon value function. With the additional condition, the global result and the input-to-state stable property of the receding horizon value function are also given. Finally, we derive the stability margin for the saddle point value based receding horizon controller. The proposed result has a larger stability region than the existing inverse optimality based results.

• Journal of the Korean Institute of Intelligent Systems
• /
• 제13권5호
• /
• pp.606-613
• /
• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.