This paper presents an anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. The proposed ARW method is motivated by the concept of equilibrium point. The design parameters of the ARW scheme is derive explicitly by minimizing a reasonable performance index. In the event of saturation, the resulting dynamics of the compensated controller reflects the dynamics of the linear closed-loop system. The proposed method guarantees the total stability o fthe resulting control systems under a certain condition. An illustrative example is given to show the effectiveness of the proposed method. The paper is an extension of the results in Park and Choi[10].

본 논문에서는 기계적 위치 제어계에서 다단계 뱅-뱅 액츄에이터의 비선형성에 의한 목표 위치에서의 리미트 사이클을 방지하는 제어방법을 제안한다. 다단계 뱅-뱅 액츄에이터의 선형화된 모델인 기술함수를 이용하여 비선형성을 보상한다. 강인성을 확보하기 위해 루프 형성 기법에 의한 H/sub .inf./ 제어기가 설계된다. 제안된 제어방법은 기존의 선형제어기보다 비선형성이 보상되어 사역대가 작아지므로 최소 제어 가능 구간을 줄일 수 있다. 1축 위치 제어계의 실험을 하여 제안된 제어방법이 리미트 사이클을 줄이고 제어정도를 향상 시키는데 유효함을 입증하였다.

본 논문에서는 디스트리뷰션 인테그랄 서브매니폴드에 의하여 표현되는 마찰이 없는 면을 따라 강체 로봇 매니퓰레이터의 모션 제어에 대한 새로운 힘.위치 제어법칙은 힘/위치가 제어되는 방향으로 투영된 앤드 이팩트의 비선형 항을 정확하게 상쇄하도록 설계하였으며, 미분기하학을 이용하여 스무스 디스트리뷰션의 인테그랄 서브매니폴드 상에서의 새로운 모션 방정식을 제안하고 제안된 힘/위치 제어법칙에 대한 타당성을 컴퓨터 시뮬레이션을 통하여 검증한다.

복잡한 비선형성과 불확실한 변수를 가지는 유연 죠인트 로봇의 견실한 관측기 설계에 관한 연구이다. 시간 불변 또는 시간 가변성의 불확실한 변수들을 가지는 시스템에 적용한 경우이며 로봇 링크의 각도와 각속도들을 출력으로 하였다.본 견실 관측기는 리아프노프 방법에 기초를 두었으며 불확실한 변수들은 그값을 모르나 그 값들은 지정된 집합내에 존재한다. 제안된 견실 관측기는 실용적인 안정성을 보장한다. 관측기설계의 알고리즘을 2링크 유연 죠인트 로봇에 적용하여 시뮬레이션을 수행하여 우수한 성능을 가짐을 확인할수 있었다.

In this paper, variable structure control(VSC) based on reaching law method with fuzzy inference for nonlinear systems is proposed. The reaching law means the reaching condition which forces an initial state of system to reach switching surface in finite time, and specifies the dynamics of a desired switching function. Since the conventional reaching law has fixed coefficients, the chattering can be existed largely in sliding mode. In the design of a proposed fuzzy reaching law, we fuzzify RP(representative point)'s orthogonal distance to switching surface and RP's distance the origin of the 2-dimensional space whose coordinates are the error and the error rate. The coefficients of the reaching law are varied appropriately by the fuzzy inference. Hence the state of system in reaching mode reaches fastly switching surface by the large values of reaching coefficients and the chattering is reduced in sliding mode by the small values of those. And the effectiveness of the proposed fuzzy reaching law method is showen by the simulation results of the control of a two link robot manipulator.

본 논문에서는 퍼지추정기와 슬라이딩 모드제어이론이 고려되었다. 비선형시스템에 대한 슬라이딩 모드 제어기 설계 시에 그 시스템의 비선형함수를 추정하기 위하여 퍼지논리시스템이 사용되는 두가지의 적응처지슬라이딩 모드제어방식을 제안한다. 첫번째 방식에서는 비선형시스템, x/sup (n)/=f(x under bar, t) + b(x under bar, t)u 의 알지 못하는 함수 f를 추정하기 위하여 하나의 퍼지논리시스템이 사용되어진다. 두번째 방식에서는 비선형시스템의 f와 b에 대한 추정기로서의 두개의 퍼지논리시스템이 각각 사용되어진다. 각각의 방식에 대하여 제어시스템의 안정도를 보장하도록 하는 적응법칙을 설계하며 퍼지추정기와 비선형함수와의 추정오차를 줄이기 위해 각각에 대한 강인한 제어법칙을 제안한다. 제안된 네 가지의 제어법칙에 대한 안정성을 증명하고 컴퓨터시뮬레이션에서 역진자시스템에 적용하여 그에 대한 타당성과 각각의 비교를 보인다.

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

This paper discusses the maintenance of the water level of steam generators at its programmed value. The process, the water level of a steam generator, has the nonminimum phase property. So, it causes a reverse dynamics called a swell and shrink phenomenon. This phenomenon is severe in a low power condition below 15 %, in turn makes the start-up of the power plant too difficult. The control algorithm used here incorporates a pole-assignment scheme into the minimum variance strategy and we use a parallel adaptation algorithm for the parameter estimation, which is robust to noises. As a result, the total control system can keep the water level constant during full power by locating closed-loop poles appropriately, although the process has the characteristics of high complexity and nonlinearity. Also, the extra perturbation signals are added to the input signal such that the control system guarantee persistently exciting. In order to confirm the control performance of a proposed pole-assignment self-tuning controller we perform a computer simulation in full power range.

This paper proposes a neural network controller with the computed torque method. The neural network is used not to learn the inverse dynamic model but to compensate the uncertainties of robotic manipulators. When training the neural network, we use the signals present in the proposed controller, which is simpler than that proposed by Ishiguro et al., whose teaching signals of the neural network come from the robot model.

The speed of SR(Switched Reluctance) motor can be controlled by switching angle. However, since the relation between speed and switching is nonlinear, it is difficult for simple adjustment schemes to achieve the desired performances. In this paper, an error.feedback nonlinear compensator with robustness is proposed for improving the performances of the switching angle controlled SR motor. The proposed controller consists of integral type control and relay type control. The integral type controller which operates regulation, is derived by the steady.state I/O(input/output) map and the relay type controller which works tracking, is designed by Lyapunov stability theory. The validities of the proposed controller are confirmed with the experimental results.

In this paper, we present a vision algorithm to extract the tire information markings on the sidewall of tires. Since the appearance of tire marks is the same as its background, a primary feature to distinguish tire marks from their background is the roughness. Generally, the roughness of tire marks is different from that of its bakground: the surface of tire marks is smoother than the backgrounds. Light incident on the tire surface is reflected differently according to the roughness. For smoother surfaces, the surface irradiance is much stronger than that of rough surfaces. Based on these phenomena and observation, we propose an optimal illumination condition based on Torrance-Sparrow reflection model. We also develop an efficient reflectance-ratio based operator to extract the boundary of tire marks. Even with a very simple masking operation, we were able to obtain remarkable boundary extraction results from real experiments using many tires. By explicitly using the surface reflection model to explain the intensity variation on the black tire surface, we demonstrate that a physics-based vision method is powerful and feasible in extracting surface markings on tires.

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

In this paper, we investigate the defect detection by making use of pre-made reference image data and classify the defects by using the artificial neural network. The approach is composed of three main parts. The first step consists of a proper generation of two reference image data by using a low level morphological technique. The second step proceeds by performing three times logical bit operations between two ready-made reference images and just captured image to be tested. This results in defects image only. In the third step, by extracting four features from each detected defect, followed by assigning them into the input nodes of an already trained artificial neural network we can obtain a defect class corresponding to the features. All of the image data are formed in a bit level for the reduction of data size as well as time saving. Experimental results show that proposed algorithms are found to be effective for flexible defect detection, robust classification, and high speed process by adopting a simple logic operation.

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

A variable structure controller is developed for an AC servo motor used in CNC milling machines. The designed controller is implemented as an outer loop controller to a factory designed motor-servopack system. The robustness parameter is tuned for a fast response when the speed tracking error is large, while it is tuned for small oscillations when the speed tracking error is small. The designed controller is installed on a CNC machine using a PC. Cutting experiments show improved performance over the factory-designed controller.