• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.12
• /
• pp.2353-2363
• /
• 1994

This paper is concerned with the design of a robust digital controller using reduced-order observer on a robotic manipulator under the disturbance. In most cases of robotic manipulator since all state vectors are not measurable, the unmeasurable state vectors must be estimated or reconstructed. Other problems are caused by the nonlinear element like as nondifferentiable Coulomb friction, disturbance due to the gravitational pull, and the torsional spring effect of a link between the drive motor and the manipulator arm. The controller is based on feeding back the observable variables and the estimated state variables which are generated by the observer, and augmenting the system by additional discrete integrators. The feedback gain parameters are obtained by first applying the optimal control theory and then readjusting the feedback parameters to eliminate the limit cycle by using describing Function for nonlinear hybrid system.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.10
• /
• pp.34-43
• /
• 1990

An improved parameter adaptation and control law for robot manipulator are proposed based on a linearized parametric system equation and augmented error vectors. In view of the modeling error and parasitics with small time constants which inevitably introduced during modelling process, their effects on the robustness of the system performance are reviewed and as an conutermearsure, adaptation mechanism with low pass filter is proposed. Proposed parameter adaptation and control low assure the stability of the robot manipulator in the large without further assumption. Computer simulation shows its effectiveness of the proposed adaptation mechanism to improve the robustness of the system in presence of the parasitics in the system and superior performance for high speed operations make it an attractive option in application of the adaptive control field for robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.8
• /
• pp.563-569
• /
• 1988

This research presents several velocity modification methods for collision avoidance of two manipulators in a common workspace. Due to the distinct nature of collision avoidance between the two manipulators, a new classification of collision situations is presented and utilized in planning a collision-free path. Concepts of a collision map and velocity modification are applied for realizing collision-free motion planning. An example is shown for velocity modification of a trajectory, which shows the significance of the proposed approaches in collision-free motion planneng of two moving robots.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.15 no.4
• /
• pp.295-300
• /
• 1990

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield, Tank's neural network. The states of neurons represent joint velocities, and the connection weights are determined from the current value of the Jacobian matirx. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint positon. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.11
• /
• pp.1186-1193
• /
• 1991

This paper proposed a trajectory controlmethod for a robot manipulator by using neural networks. The total torque for a manipulator is a sum of the linear feedback controller torque and the neural network feedfoward controller torque. The proposed neural network is a multilayer neural network with time delay elements, and learns the inverse dynamics of manipulator by means of PD(propotional denvative)controller error torque. The error backpropagation (BP) learning neural network controller does not directly require manipulator dynamics information. Instead, it learns the information by training and stores the information and connection weights. The control effects of the proposed system are verified by computer simulation.

• Journal of the Korean Society for Precision Engineering
• /
• v.10 no.4
• /
• pp.54-63
• /
• 1993

This paper presents the dynamic modeling and control methodology to arrest structural deflections of industrial robotic manipulators featuring elastic members retrofitted with surface bonded pizoelectric actuators and sensors. The cynamic modeling is accomplished by employing a variational theorem, prior to developing a finite element formulation. This finite element formulation accounts for both original robot member elements and also bonded piezoelectric material elements. The governing equation of motion is then modified by condensing the electric potential vectors and subsequently two different negative velocity feedback controllers are established; a constant-gain feedback controller and a constant- amplitude feedback controller. By adopting a Model P50 articulating industrial robot manufactured by Gerneral Electric Company, conputer simulations are underlaken in order to demonstrate superior performance characteristics to be accrued from this proposed methodology such as smaller deflections at the end-effector.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.5
• /
• pp.25-32
• /
• 1996

This paper will propose the direct adaptive learning control scheme based on adaptive control technique and intelligent control theory for a nonlinear system. Using the proposed learning control scheme, we will apply to on-line control an uncertain but for model perfect matching, it's structure condition is known. The effectiveness of the proposed control schem will be illustrated by simulations of a robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.3
• /
• pp.316-325
• /
• 1991

This paper presents the design of a new sliding mode controller to improve the rate of convergence by Lyapunov's stability analysis. The proposed controller shows that the elimination of the steady state position errors can be achieved by replacing the desired trajectory by the virtual reference trajectory. The proposed control scheme which consists of the upper bounded and estimated values of eac term of the manipulator dynamic equation does not require good knowledge of the parameters and the computation of matrix inversion. The performance of proposed controller is evaluated by the simulation for a two-link manipulator.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.428-433
• /
• 1993

An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We use the view-time concept, especially the adaptive view-time. First. we introduce the adaptive view-time and analyze its properties. Next, we propose a view-time based motion planning method. The proposed method is applied and simulated for the collision-free motion planning of a 2 DOF robot manipulator. We simulate the robot motion under several different view-time systems. Generally, the motion planning with the adaptive view-time systems has some advantages over that with the fixed view-time systems.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.734-738
• /
• 1996

An adaptive output feedback controller is designed for tracking control of an n-link robot manipulator with unknown load. High-gain observers with same structure as error dynamic systems are used to estimate joint velocities. The parameter adaptation is achieved by the smoothed projection algorithm. The control inputs are saturated outside a domain of interest. Simulation results on a 2-link manipulator illustrate that when the speed of the high-gain observer is sufficiently high, the proposed controller recovers the performance under state feedback control.