• 한국산업융합학회 논문집
• /
• 제22권6호
• /
• pp.807-819
• /
• 2019

In this paper, it is proposed a new approach to motion control and kinematics analysis of articulated manipulator attachment with five degree of freedom for excavator. Unlike the well-established theory for the control of linear systems, there is little general control theory relatively for a robust control of nonlinear systems. The control technique is essential for providing a stable and robust performance for application of articulated manipulator control. The proposed control algorithm is one of robust control methods based on error informations of the position and velocity error informations using stability analysis of dynamic model. Through simulation test, the proposed control scheme is illustrated to be a efficient control technique for real-time control.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 춘계학술대회논문집A
• /
• pp.529-535
• /
• 2000

This paper propose the method to obtain the inverse kinematics and the Jacobian of the 5-bar parallel robot and apply the nonlinear controller to the 5-bar parallel robot with the dynamic analyses using the Jacobian of the Passive joints with respect to the active ones and singular value decomposition(SVD). It also experimentally shows that we can do high-speed and accuracy tasks using nonlinear control method. And it explains the relation between the property of the position control and manipulability using a new performance index.

• 한국산업융합학회 논문집
• /
• 제25권2_1호
• /
• pp.161-168
• /
• 2022

This study proposed a new approach to impliment a robusut control of comsumer-friendly flexible manipulator with five joint for untact working in filed work-site. The output redefinition approach was used to overcome the non minimum phase characteristic of the system. The new output is defined so that the zero dynamics related to this output are stable. The control strategy is based on an computed torque method which is applicable to a class of time-invariamt phase linear systems whose uncertainties appear in output loop stable. The controller is composed of a stabilizing joint controller and an output redefinition tracking controller. Experimental results are also presented to verify the effectiveness of the proposed control scheme.

• 한국정밀공학회지
• /
• 제12권5호
• /
• pp.57-68
• /
• 1995

A general procedure for the numerical solution of coupled, nonlinear, differential two-point boundary-value problems, solutions of which are crucial to the controller design, has been developed and demonstrated. A fixed-end-points, free-terminal-time, optimal-control problem, which is derived from Pontryagin's Maximum Principle, is solved by an extension of Davidenko's method, a differential form of Newton's method, for algebraic root finding. By a discretization process like finite differences, the differential equations are converted to a nonlinear algebraic system. Davidenko's method reconverts this into a pseudo-time-dependent set of implicitly coupled ODEs suitable for solution by modern, high-performance solvers. Another important advantage of Davidenko's method related to the time-optimal problem is that the terminal time can be computed by treating this unkown as an additional variable and sup- plying the Hamiltonian at the terminal time as an additional equation. Davidenko's method uas used to produce optimal trajectories of a single-degree-of-freedom problem. This numerical method provides switching times for open-loop control, minimized terminal time and optimal input torque sequences. This numerical technique could easily be adapted to the multi-point boundary-value problems.

• 제어로봇시스템학회논문지
• /
• 제5권1호
• /
• pp.95-104
• /
• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• 제어로봇시스템학회논문지
• /
• 제1권2호
• /
• pp.88-93
• /
• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• 한국통신학회논문지
• /
• 제14권5호
• /
• pp.486-502
• /
• 1989

본 논문에서는 로보트 매니퓰레이터의 정밀한 경로 제어를 위해서, 두가지 형태의 로보트 관절 각도 및 관절 속도의 예측 알고리즘을 제시하고, 이를 이용한 제어 방법을 기술하고자 한다. 구체적으로, 로보트 메니퓰레이터의 동특성을 Computed torque방법으로 선형화 시킨후에, 선형화된 모델을 근거로 한 이산시간 상태변수 예측기를 제안한다. 또한, 현재의 관절 위치 및 관절 속도와 과거 및 개의 위치 및 속도 등을 최소 자승법의 의미로 가장 잘 부합시키는 직선을 찾고, 그 직선으로부터 상태를 예측하는 예측기를 제안한다. 이 후에 이들 두 예측기로부터 정보를 이용하여, 예측된 궤적과 원하는 궤적 사이의오차에 적절한 이득을 곱해서 입력 토오크에 보정되어 사용됨으로써 궤적 오차를 줄일 수 있음을, 2자유도를 갖는 SCARA 로보트를 대상으로 컴퓨터 모의 실험을 통하여 보이고자 한다.

• 제어로봇시스템학회논문지
• /
• 제4권1호
• /
• pp.10-18
• /
• 1998

불확실한 변수와 비선형성을 가지는 유연조인트 로봇의 견실제어 방안을 제시한다. 그리고 본 시스템에서 불확실구조는 일치성을 유지하지 않는 불일치성 불확실 시스템이다. 제어기는 리아노프의 방안에 근거를 두고있다. 견실제어는 연산토크법을 사용하고 삽입제어기법을 통하여 좌표변환을 통해 구성된다. 제어기 설계과정은 우선 연산토크방법에 의해 시스템 동역학에서 정격부분을 선형으로 2개의 부분시스템으로 구성한다. 이후 좌표변환을 이용하여 각 부분시스템에 제어기를 구축한다. 이 방안을 통하여 관성 행렬이 알려진 값인 경우 이 행렬의 상위한계 조건없이 제어기를 설계할 수 있다. 따라서 임의의 형태의 로봇에도 적용 가능한 제어알고리즘이 된다. 설계된 견실제어는 변환된 시스템이나 원시스템 모두 실용적 안정성을 보장한다. 이 변환은 단지 불확실변수의 최대 한계값의 정보만을 요구한다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1996년도 하계학술대회 논문집 B
• /
• pp.1205-1207
• /
• 1996

The computed-torque method (CTM) shows good trajectory tracking performance in controlling robot manipulator if there is no disturbance or modelling errors. But with the increase of a payload or the disturbance of a manipulator, the tracking errors become large. So there have been many researchs to reduce the tracking error. In this paper, we propose a new control algorithm based on the CTM that decreases a tracking error by generating new reference trajectory to the controller. In this algorithm we used a fuzzy system based on the rule bases. For the numerical simulation, we used a 2-link robot manipulator. To simulate the disturbance due to a modelling uncertainty, we added errors to each elements of the inertia matrix and the nonlinear terms and assumed a payload to the end-effector. In the simulations of several cases, our method showed better trajectory tracking performance compared with the CTM.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
• /
• pp.1960-1961
• /
• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.