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

• International Journal of Control, Automation, and Systems
• /
• v.2 no.2
• /
• pp.144-155
• /
• 2004

This paper addresses the issue of position control of a chain of multiple mass-spring-damper (CMMSD) units which can be found in many physical systems. The dynamic model of a CMMSD system with any degrees of freedom is expressed in a closed-form for the convenience of the controller design. Backstepping and model reference adaptive control (MRAC) approaches are then used to develop two adaptive output feedback controllers to control the position of a CMMSD system. The proposed controllers rely on the measurements of the input (force) and the output (position of the mass unit at the end of the chain) of the system without the knowledge of its parameters and internal states. Simulations are used to verify the effectiveness of the controllers

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.29-34
• /
• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1640_1641
• /
• 2009

Dynamic friction and force ripple are the most predominant factors that affect the positioning accuracy of permanent magnet synchronous motor(PMSM) servo drives system, and it is desirable to compensate them in finite time with a continuous control law. In this paper, based on LuGre dynamic friction model, a robust adaptive skidding mode controller is proposed to compensate the nonlinear effect of friction and force ripple. The controller scheme consists of a PD component and a robust adaptive sliding mode controller for estimating the unknown system parameter. Using Lyapunov stability theorem, asymptotic stability analysis and position tracking performance are guaranteed. Simulation results well verify the feasibility and the effectiveness of the proposed scheme for high0precision motion trajectory tracking.

• Proceedings of the KIEE Conference
• /
• 1990.07a
• /
• pp.504-509
• /
• 1990

This paper presents a decentralized adaptive control scheme for multi-Joint robot manipulators based on the independent joint control scheme. The control object is to achieve accurate tracking of desired Joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simple by a feedback controller which ensure stable and also a position-velocity-acceleration feedforward controller and also auxiliary signal, with adjustable gains. Simulation results are given for a two-link manipulator under independent control, proposed decentralized adaptive control of manipulator is feasible. In spite of a pay load variation and strong static and dynamic couplings that exist between the joints.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.199-204
• /
• 2006

In this paper, we propose an adaptive control algorithm to improve the position accuracy and reduce the nonlinear friction effects for linear motion servo system. Especially, the considered system includes not only the variation of the mass of the mover but also the friction change by the normal force. To adapt to these problems, we designed the controller with the mass estimator and the compensator by observing the variation of normal force. Finally, the numerical simulation results are presented in order to show the effectiveness of the proposed method to improve the position accuracy compared to other control methods.

• Smart Structures and Systems
• /
• v.31 no.5
• /
• pp.437-454
• /
• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• Advances in aircraft and spacecraft science
• /
• v.7 no.1
• /
• pp.1-17
• /
• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Restorative Dentistry and Endodontics
• /
• v.42 no.1
• /
• pp.34-38
• /
• 2017

Objectives: The aim of this study was to evaluate the cyclic fatigue resistance of the ProTaper Universal D1 file (Dentsply Maillefer) under continuous and adaptive motion. Materials and Methods: Forty ProTaper Universal D1 files were included in this study. The cyclic fatigue tests were performed using a dynamic cyclic fatigue testing device, which had an artificial stainless steel canal with a $60^{\circ}$ angle of curvature and a 5 mm radius of curvature. The files were randomly divided into two groups (Group 1, Rotary motion; Group 2, Adaptive motion). The time to failure of the files were recorded in seconds. The number of cycles to failure (NCF) was calculated for each group. The data were statistically analyzed using Student's t-test. The statistical significant level was set at p < 0.05. Results: The cyclic fatigue resistance of the adaptive motion group was significantly higher than the rotary motion group (p < 0.05). Conclusion: Within the limitations of the present study, the 'Adaptive motion' significantly increased the resistance of the ProTaper Universal D1 file to cyclic facture.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.148-153
• /
• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.