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.

Singularity Tolerant Robotic Manipulation for Autonomous Field Tracking in an Unknown Environment

2010 ◽  
Author(s):  
Soo Jeon
Keyword(s):  
Target Location ◽  
Null Space ◽  
A Priori ◽  
Recursive Estimation ◽  
Least Square ◽  
Control Law ◽  
Task Space ◽  
Recursive Least Square ◽  
Rbf Network ◽  
Autonomous Operation

This paper presents a comprehensive motion control strategy for the autonomous operation of robotic manipulators combined with the sensor-driven recursive estimation of an unknown field of interest. The spatial distribution of the environmental phenomenon is modeled by a radial basis function (RBF) network and their weight parameters are estimated by a recursive least square (RLS) method using the collective measurements from the on-board sensors mounted to the manipulator. The asymptotic tracking has been simultaneously achieved by the control law based on the gradient of the estimated field. Since the target location cannot be known a priori, the motion controller has to be designed in explicit consideration of tolerating the singular configuration of the manipulator kinematics. By using the null space decomposition of the task space for the Jacobian near the singularities, a systematic method is suggested to command the task space control law in spite of the singular configurations. Simulation results using the three link planar robot are presented to support the main ideas.

A New Method to Detect P-Wave Based on Quadratic Function

2011 ◽  
Vol 267 ◽  
pp. 462-467
Author(s):  
Nan Quan Zhou
Keyword(s):  
Quadratic Function ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
P Wave ◽  
Good Effect ◽  
Rate Variation ◽  
Optimal Interval ◽  
Wave Detection ◽  
Wide Range

The paper presents a P-wave detection algorithm based on fitting function in the optimal interval. In the algorithm we used quadratic function to fit the P wave by this means of least square method in every interval, which was shifted in local range. Then we found the optimal fitting interval of P wave by comparing the error of fitting. Finally, we obtained the characteristic points of P wave by using the fitting function to fit P wave in the optimal interval. The performance of the algorithm tested using the records of the MIT-BIH database was effective and accurate. The algorithm on the wide range of heart rate variation and small P wave of ECG P-wave detection has good effect. Also it has some capabilities of anti-interference, particularly the false dismissal probability is quite low.

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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