Cooperative Control of Manipulator and Human Operator for Direct Teaching

2021 ◽  
pp. 2150007
Author(s):  
Jongwoo An ◽  
Youdong Zhao ◽  
Jangmyung Lee
Keyword(s):  
Control Strategy ◽  
Cooperative Control ◽  
Least Square Method ◽  
Interaction Force ◽  
Human Motion ◽  
Least Square ◽  
Human Operator ◽  
Recursive Least Square ◽  
Direct Teaching ◽  
Teaching Operation

A cooperative control of a manipulator and a human operator has been proposed for an efficient direct teaching operation in this research. The main goal is making the operator be convenient and relaxed when he is operating the manipulator for a direct teaching. The proposed control strategy has two layers: In the first layer, human motion estimator (HME) has been designed to estimate a human intention. The recursive least square method has been utilized for the HME to simultaneously estimate the interaction force and the human arm admittance model. In the second layer, human motion reactor has been designed to keep the human motion intention precisely by a proportional derivative and gravity compensation in real time. Real experiments with a 3-degree of freedom robotic manipulator guided by the human operator have been conducted to draw a diamond shape on a panel. The experimental results demonstrate the effectiveness of the proposed cooperative control strategy.

Recursive field estimation and tracking for autonomous manipulation

Robotica ◽  
2011 ◽  
Vol 30 (5) ◽  
pp. 743-753 ◽  
Author(s):  
Soo Jeon
Keyword(s):  
Radial Basis Function Network ◽  
Least Square Method ◽  
Least Square ◽  
Source Tracking ◽  
Control Law ◽  
Task Space ◽  
Recursive Least Square ◽  
Wide Range ◽  
Field Estimation ◽  
Task Space Control

SUMMARYAutonomous operation of mechanical systems often requires the ability to detect and locate a particular phenomenon occurring in the surrounding environment. Being implemented to articulated manipulation, such a capability may realize a wide range of applications in autonomous maintenance and repair. This paper presents the sensor-driven task space control of an end-effector that combines the field estimation and the target tracking in an unknown spatial field of interest. The radial basis function network is adopted to model spatial distribution of an environmental phenomenon as a scalar field. Their weight parameters are estimated by a recursive least square method using collective measurements from the on-board sensors mounted to the manipulator. Then the asymptotic source tracking has been achieved by the control law based on the gradient of the estimated field. A new singularity tolerant scheme has been suggested to command the task space control law despite singular configurations. Simulation results using the three-link planar robot and the 6-revolute elbow manipulator are presented to validate the main ideas.

scholarly journals MPPT Control Strategy of PV Based on Improved Shuffled Frog Leaping Algorithm under Complex Environments

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaohua Nie ◽  
Haoyao Nie
Keyword(s):  
Control Strategy ◽  
Control Strategies ◽  
Least Square ◽  
Measurement Noise ◽  
Complex Environments ◽  
Recursive Least Square ◽  
Shuffled Frog Leaping Algorithm ◽  
Noise Effects ◽  
Pv Array ◽  
Shuffled Frog Leaping

This work presents a maximum power point tracking (MPPT) based on the particle swarm optimization (PSO) improved shuffled frog leaping algorithm (PSFLA). The swarm intelligence algorithm (SIA) has vast computing ability. The MPPT control strategies of PV array based on SIA are attracting considerable interests. Firstly, the PSFLA was proposed by adding the inertia weight factor w of PSO in standard SFLA to overcome the defect of falling into the partial optimal solutions and slow convergence speed. The proposed PSFLA algorithm increased calculation speed and excellent global search capability of MPPT. Then, the PSFLA was applied to MPPT to solve the multiple extreme point problems of nonlinear optimization. Secondly, for the problems of MPPT under complex environments, a new MPPT strategy of the PSFLA combined with recursive least square filtering was proposed to overcome the measurement noise effects on MPPT accuracy. Finally, the simulation comparisons between PSFLA and SFLA algorithm were developed. The experiment and comparison between PSLFA and PSO algorithm under complex environment were executed. The simulation and experiment results indicate that the proposed MPPT control strategy based on PSFLA can suppress the measurement noise effects effectively and improve the PV array efficiency.

Design and Realization on the Optimal Quadratic Controller for the Positional Servo System of Numerical Control System

2011 ◽  
Vol 317-319 ◽  
pp. 1960-1963
Author(s):  
Li Bing Zhang ◽  
Ting Wu
Keyword(s):  
Control System ◽  
Control Method ◽  
Servo System ◽  
Least Square Method ◽  
Least Square ◽  
Servo Control ◽  
Numerical Control ◽  
Recursive Least Square ◽  
Servo Control System ◽  
Position Servo

This paper presents a technique for the position servo system of numerical control (NC) machine tool by utilizing the optimal quadratic controller. The mathematical model of the position servo control system is structured, which of the plant model is identified by making use of recursive least square method. The fundamental method of designing the optimal quadratic controller is proposed. Simulation of the optimal quadratic controller and PID controller are implemented by using MATLAB. The results of simulation show that the proposed control method of positional servo control system has better dynamic characteristics and better steady performance.

A Method for Modal Parameter Identification of Time Varying Vibration Systems

2012 ◽  
Vol 479-481 ◽  
pp. 688-693
Author(s):  
Zi Ying Wu ◽  
Kun Shi
Keyword(s):  
Linear Time ◽  
Least Square Method ◽  
Degree Of Freedom ◽  
Least Square ◽  
Modal Parameters ◽  
Time Varying ◽  
Recursive Least Square ◽  
Modal Parameter ◽  
Linear Time Invariant ◽  
Prony Method

In this paper a new time varying multivariate Prony (TVM-Prony) method is put forward to identify modal parameters of time varying (TV) multiple-degree-of-freedom systems from measured vibration responses. The proposed method is based on the classical Prony method that is often used to identify modal parameters of linear time invariant systems. The main advantage of the propose approach is that it can analyze multi-dimensional nonstationary signals simultaneously. A modified recursive least square method based on the traditional one is presented to determine the TV coefficient matrices of the multivariate parametric model established in the proposed method. The efficiency and accuracy of the identification approach is demonstrated by a numerical example, in which a TV mass-string system with three-degree-of-freedom is investigated. Satisfied results are obtained.

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