• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.6
• /
• pp.510-518
• /
• 2004

The PID trajectory tracking controller for robotic systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point can not be defined for the control system involving performance limitation, we define newly the quasi-equilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide us the auto-tuning method for PID controller. Also, the quasi-equilibrium region is used as the target performance of auto-tuning PID trajectory tracking controller. The auto-tuning law is derived from the direct adaptive control scheme, based on the extended disturbance input-to-state stability and the characteristics of performance limitation. Finally, experimental results show that the target performance can be achieved by the proposed automatic tuning method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.4
• /
• pp.479-486
• /
• 1998

In this paper, the design and the implementation of a robust adaptive controller for trajectory tracking of robot manipulator is presented. The proposed control scheme ensures that tracking errors are converged to some boundaries in the presence of a state-dependent input disturbances as well as the ideal case without any prior knowledge of the robot manipulator parameters. The 3 DOF robot manipulator including actuator dynamics is used for the implementation of the proposed control scheme. The experimental results show that the proposed control scheme is valid for trajectory tracking of the robot manipulator.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.1
• /
• pp.22-29
• /
• 2004

This paper studies the coordinated trajectory control of an excavator as a kind of robotic manipulators driven by hydraulic actuators. Hydraulic robot system has many non-linearity in dynamics and kinematics, and strong coupling among joints(or hydraulic cylinders). This paper proposes a combined controller frame of the adaptive robust control(ARC) and the sliding mode control(SMC) for the trajectory tracking control of the excavator to preserve the advantages of the both methods while overcoming their drawbacks, namely, asymptotic stability of adaptive system for parametric uncertainties and guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbance. The suggested control technique is applied for the tracking of a straight-line motion of end-effector of manipulators, and through computer simulations, its trajectory tracking performances and the robustness to payload variation and uncertainties are illustrated.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.745-750
• /
• 2008

Uncertain dynamic parameters and joint flexibility have been problem to control robot manipulator precisely. Hence, even if the controller tracks the desired trajectory well with the feedback of the motor encoders, it is hard to achieve the desired behavior at the end-effector. In this paper, robot trajectory is taught by a general heuristic iterative learning control (ILC) algorithm in order to reduce tracking error of the tool center point (TCP) and the results of tracking with 6 DOF industrial robot manipulator are presented. The performance is verified based on ISO 9283.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1652-1653
• /
• 2007

가변제어구조로 동작하는 슬라이딩모드제어(SMC)는 플렌트의 파라미터 변동과 부하왜형에 관계없이 스위칭 제어 알고리즘에 의해 위상 평면에서 미리 예측된 궤적 또는 기준모델을 따라 구동응답을 주어진 슬라이딩 면을 따라 강제로 추종시키는 것이다. 여기서 슬라이딩 평면을 찾아내는 방법의 하나로 SVM(Suppot Vector Machine) 을 사용한다. 그런데 SVM을 사용하여 슬라이딩 평면을 찾아내는 과정에서, 초기치의 변동이 있을 경우, SVM 모델을 재구성해야 해야 한다. 이에 본 논문에서는 SVM 모델을 재구성할 필요 없이, 기존 초기치에 의한 SVM 모델에서, 원하는 초기치의 SVM모델로 변경할 수 있는 방법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.4
• /
• pp.77-86
• /
• 1995

The new architecture that fuzzy logic control(FLC) with difficulties for tuning membership function (MF) is parallel with neural networks(NN) to be learned from the output of FLC is proposed. Therefore proposed scheme has the characteristics to utilize the expert knowledge in design process, to be learned during the operation without any learning mode. In this architecture, the function of the FLC is to supply the sliding surface which is constructed on the phase plane by rule base for giving the desired control characteristics and learning criterion of NN and the stabilization of the control performance before NN is learned, The function of the NN is to let the system trajectory be tracked to the sliding surface and reached to the stable point.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.4
• /
• pp.350-358
• /
• 2009

This paper describes a result of the guidance and control for re-entry vehicle during TAEM phase. TAEM phase (Terminal Aerial Energy Management phase) has many conditions, such as density, velocity, and so on. Under these conditions, we have optimized trajectory and other states for guidance in TAEM phase. The optimized states consist of 7 variables, down-range, cross range, altitude, velocity, flight path angle, vehicle's azimuth and flight range. We obtained the optimized reference trajectory by DIDO tool, and used feedback linearization with neural network for control re-entry vehicle. By back propagation algorithm, vehicle dynamics is approximated to real one. New command can be decided using the approximated dynamics, delayed command input and plant output, NARMA-L2. The result by this control law shows a good performance of tracking onto the reference trajectory.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.6
• /
• pp.12-20
• /
• 1998

As an approach to develope a control system with high robustness in changing control environment conditions, this paper will propose a robust control system, using multilayer neural network and biological immune system. The proposed control system adjusts weights of the multilayer neural network(MNN) with the immune algorithm. This algorithm is made up of two major divisions, the innate immune algorithm as a first line of defence and the adaptive immune algorithm as a barrier of self-adjustment. Using the proposed control system based on immune algorithm, we will work out a design for the controller of a robot manipulator. And we will demonstrate the effectiveness of the control system of robot manipulator with computer simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.5
• /
• pp.448-454
• /
• 2008

This paper deals with a behavior based decentralized control strategy for UAV swarming utilizing the artificial potential functions and the sliding mode control technique. Individual interactions for swarming behavior are modeled using the artificial potential functions. The motion of individual UAV is directed toward the negative gradient of the combined potential. For tracking the reference trajectory of UAV swarming, a swarming center is considered as the object of control. The sliding-mode control technique is adopted to make the proposed swarm control strategy robust with respect to the system uncertainties and the varying mission environment. Numerical simulation is performed to verify the performance of the proposed controller.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.7 no.3
• /
• pp.103-109
• /
• 2008

The work to raise the bridge plate by using two hydraulic cylinders is very dangerous when generating the unbalance state between cylinders. For solving this problem, one cylinder is forced to follow the trajectory of another cylinder instead of applying the same trajectory to two cylinders at once. In this paper, the control method for dynamic stable on lifting the bridge plate is proposed. The simulation model is derived by using commercial software, AMESim and MatLab/simulink. The PID controller is designed on one cylinder for following the reference trajectory and the adaptive controller is designed on another cylinder for tracking the displacement of one cylinder. The performance improvement is shown by comparing the simulation results through computer simulation.