• Title/Summary/Keyword: Joint algorithm

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A Sequential Joint Maximum Likelihood Algorithm for Blind Co-Channel Signal Separation (블라인드 동채널 신호 분리를 위한 순차적인 Joint Maximum Likelihood 알고리듬)

  • Inseon Jang;Park, Seungjin
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.85-88
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    • 2001
  • In this paper we consider a problem of blind co-channel signal separation, the goal of which is to estimate multiple co-channel digitally modulated signals using an antenna array. We employ the joint maximum likelihood estimation and present a sequential algorithm, which is referred to as sequential joint maximum likelihood (SJML) algorithm. It separates multiple co-channel signal on-line and converges fast in overdetermined noisy communication environment. And the computational complexity of SJML for M-QAM (M=8, 16, 64,...) signals is less expensive compared to the SLSP. Useful behavior of this algorithm are confirmed by simulations.

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Resolution of kinematic redundancy using contrained optimization techniques under kinematic inequality contraints

  • Park, Ki-Cheol;Chang, Pyung-Hun
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.69-72
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    • 1996
  • This paper considers a global resolution of kinematic redundancy under inequality constraints as a constrained optimal control. In this formulation, joint limits and obstacles are regarded as state variable inequality constraints, and joint velocity limits as control variable inequality constraints. Necessary and sufficient conditions are derived by using Pontryagin's minimum principle and penalty function method. These conditions leads to a two-point boundary-value problem (TPBVP) with natural, periodic and inequality boundary conditions. In order to solve the TPBVP and to find a global minimum, a numerical algorithm, named two-stage algorithm, is presented. Given initial joint pose, the first stage finds the optimal joint trajectory and its corresponding minimum performance cost. The second stage searches for the optimal initial joint pose with globally minimum cost in the self-motion manifold. The effectiveness of the proposed algorithm is demonstrated through a simulation with a 3-dof planar redundant manipulator.

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A classification techiniques of J-lead solder joint using neural network (신경 회로망을 이용한 J-리드 납땜 상태 분류)

  • Yu, Chang-Mok;Lee, Joong-Ho;Cha, Young-Yeup
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.8
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    • pp.995-1000
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    • 1999
  • This paper presents a optic system and a visual inspection algorithm looking for solder joint defects of J-lead chip which are more integrate and smaller than ones with Gull-wing on PCBs(Printed Circuit Boards). The visual inspection system is composed of three sections : host PC, imaging and driving parts. The host PC part controls the inspection devices and executes the inspection algorithm. The imaging part acquires and processes image data. And the driving part controls XY-table for automatic inspection. In this paper, the most important five features are extracted from input images to categorize four classes of solder joint defects in the case of J-lead chip and utilized to a back-propagation network for classification. Consequently, good accuracy of classification performance and effectiveness of chosen five features are examined by experiment using proposed inspection algorithm.

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Control of Redundant Manipulators Using Null-Space Dynamics (여유자유도 로보트 충격제어)

  • Kim, Il-Hwan
    • Journal of Industrial Technology
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    • v.15
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    • pp.63-70
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    • 1995
  • This paper presents an impact control algorithm for reducing the potentially damaging effects by interation of redundant manipulators with their environments. In the proposed control algorithm, the redundancy is resolved at the torque level by locally minimizing joint torque, subject to the operational space dynamic formulation which maps the joint torque set into the operational forces. For a given pre-impact velocity of the manipulator, the proposed approach is on generating joint space trajectories throughout the motion near the contact which instantaneously minimize the impulsive force which is a scalar function of manipulator's configurations. The comparative evaluation of the proposed algorithm with a local torque optimization algorithm with a local torque optimization algorithm without reducing impact is performed by computer simulation. The simulation results illustrate the effectiveness of the algorithm in reducing both the effects of impact and large torque requirements.

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A hybrid algorithm for classifying rock joints based on improved artificial bee colony and fuzzy C-means clustering algorithm

  • Ji, Duofa;Lei, Weidong;Chen, Wenqin
    • Geomechanics and Engineering
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    • v.31 no.4
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    • pp.353-364
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    • 2022
  • This study presents a hybrid algorithm for classifying the rock joints, where the improved artificial bee colony (IABC) and the fuzzy C-means (FCM) clustering algorithms are incorporated to take advantage of the artificial bee colony (ABC) algorithm by tuning the FCM clustering algorithm to obtain the more reasonable and stable result. A coefficient is proposed to reduce the amount of blind random searches and speed up convergence, thus achieving the goals of optimizing and improving the ABC algorithm. The results from the IABC algorithm are used as initial parameters in FCM to avoid falling to the local optimum in the local search, thus obtaining stable classifying results. Two validity indices are adopted to verify the rationality and practicability of the IABC-FCM algorithm in classifying the rock joints, and the optimal amount of joint sets is obtained based on the two validity indices. Two illustrative examples, i.e., the simulated rock joints data and the field-survey rock joints data, are used in the verification to check the feasibility and practicability in rock engineering for the proposed algorithm. The results show that the IABC-FCM algorithm could be applicable in classifying the rock joint sets.

A Novel Algorithm of Joint Probability Data Association Based on Loss Function

  • Jiao, Hao;Liu, Yunxue;Yu, Hui;Li, Ke;Long, Feiyuan;Cui, Yingjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2339-2355
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    • 2021
  • In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

Optimizing Movement of A Multi-Joint Robot Arm with Existence of Obstacles Using Multi-Purpose Genetic Algorithm

  • Toyoda, Yoshiaki;Yano, Fumihiko
    • Industrial Engineering and Management Systems
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    • v.3 no.1
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    • pp.78-84
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    • 2004
  • To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.

Kalman Randomized Joint UKF Algorithm for Dual Estimation of States and Parameters in a Nonlinear System

  • Safarinejadian, Behrouz;Vafamand, Navid
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1212-1220
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    • 2015
  • This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.

Impact control of redundant manipulators using null-space dynamucs

  • Chung, W.J.;Choi, S.L.;kim, I.H.;Chung, G.J.
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.89-94
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    • 1994
  • This paper presents an impact control algorithm for reducing the potentially damaging effects by interation of redundant manipulators with their environments. In the. proposed control algorithm, the redundancy is resolved at the torque level by locally minimizing joint torque, subject to tire operational space dynamic formulation which maps tire joint torque set into the operational forces. For a given pre-impact velocity of the manipulator, the proposed approach is on generating joint space trajectories throughout the motion near the contact which instantaneously minimize the impulsive force which is a scalar function of manipulator's configurations. This is done by using the null space dynamics which does not affect the motion of an end-effector. The comparative evaluation of the proposed algorithm with a local torque optimization algorithm without reducing impact is performed by computer simulation. The simulation results illustrate the effectiveness of the algorithm in reducing both the effects of impact and large torque requirements.

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Joint Position Control using ZMP-Based Gain Switching Algorithm for a Hydraulic Biped Humanoid Robot (유압식 이족 휴머노이드 로봇의 ZMP 기반 게인 스위칭 알고리즘을 이용한 관절 위치 제어)

  • Kim, Jung-Yup;Hodgins, Jessica K.
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.10
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    • pp.1029-1038
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    • 2009
  • This paper proposes a gain switching algorithm for joint position control of a hydraulic humanoid robot. Accurate position control of the lower body is one of the basic requirements for robust balance and walking control. Joint position control is more difficult for hydraulic robots than it is for electric robots because of an absence of reduction gear and better back-drivability of hydraulic joints. Backdrivability causes external forces and torques to have a large effect on the position of the joints. External ground reaction forces therefore prevent a simple proportional-derivative (PD) controller from realizing accurate and fast joint position control. We propose a state feedback controller for joint position control of the lower body, define three modes of state feedback gains, and switch the gains according to the Zero Moment Point (ZMP) and linear interpolation. Dynamic equations of hydraulic actuators were experimentally derived and applied to a robot simulator. Finally, the performance of the algorithm is evaluated with dynamic simulations.