Baoyu Song

Passive Acoustic Source Localization at a Low Sampling Rate Based on a Five-Element Cross Microphone Array

Accurate acoustic source localization at a low sampling rate (less than 10 kHz) is still a challenging problem for small portable systems, especially for a multitasking micro-embedded system. A modification of the generalized cross-correlation (GCC) method with the up-sampling (US) theory is proposed and defined as the US-GCC method, which can improve the accuracy of the time delay of arrival (TDOA) and source location at a low sampling rate. In this work, through the US operation, an input signal with a certain sampling rate can be converted into another signal with a higher frequency. Furthermore, the optimal interpolation factor for the US operation is derived according to localization computation time and the standard deviation (SD) of target location estimations. On the one hand, simulation results show that absolute errors of the source locations based on the US-GCC method with an interpolation factor of 15 are approximately from 1/15- to 1/12-times those based on the GCC method, when the initial same sampling rates of both methods are 8 kHz. On the other hand, a simple and small portable passive acoustic source localization platform composed of a five-element cross microphone array has been designed and set up in this paper. The experiments on the established platform, which accurately locates a three-dimensional (3D) near-field target at a low sampling rate demonstrate that the proposed method is workable.

Research on the Thermal Error of the 3D-Coordinate Measuring Machine Based on the Finite Element Method

3D-coordinate Measuring Machine (CMM) is affected by various heat sources in high-speed measuring, which results in deformation of the machine and measurement errors. This paper makes a theoretical analysis on the thermal error produced during the CMMs work process. And the thermal deformation of CMM is analyzed with Finite Element Method (FEM). A thermal error compensation model is also established by multi-body theory. Meanwhile integral mean value theorem is used to establish a mathematical model of the thermal expansion of the drive screw, and the CMM measurement accuracy is improved.

A High-performance Speed Feed-forward Controller for Permanent Magnet Synchronous Motor Based on Control System Model

Abstract This study proposes a feed-forward controller based on a control system model that can precisely track a reference trajectory by canceling out the effects of parameter uncertainties on a surface-mounted (magnets glued to the shaft surface) permanent magnet synchronous motor. Furthermore, the speed tracking control algorithm demands rapid and accurate q-axis current command, so the feed-forward system based on the control model is used to estimate it. The stability of the proposed controller is mathematically studied. The proposed control scheme is executed on a permanent magnet synchronous motor drive using a Renesas micro-control unit (RX62TADFFM, Japan). Finally, simulation and experimental results are presented to verify that the proposed controller achieves less steady-state error, better robust performance, and faster dynamic response than the proportional–integral controllers in the presence of permanent magnet synchronous motor parameter uncertainties and external load torque disturbance.

Real-Time Filtering Method Based on Neuron Filtering Mechanism and Its Application on Robot Speed Signals

In order to implement the real-time filtering and tracking of robot signals with high efficiency, a novel real-time filtering method based on neuron filtering mechanism is developed in this paper. By considering the ubiquity of resonance in mammal and combining the mechanism of neural information processing, the derived details and the feasible parameter criterion under minimum error variance condition are given. For illustration, the application on quadruped robot is discussed. The quadruped robot feet speed signals are processed by developed real-time filtering method and Kalman filtering algorithm, respectively, and the computation time of both methods is tested. Experiment results show that the performance of developed real-time filtering method is better than that of Kalman filtering algorithm, not only in filtering and tracking performance but also in filtering speed. The novel real-time filtering method based on neuron filtering mechanism can effectively implement the real-time filtering and tracking with regard to robot signals.

Design of high precision magnetic grid displacement sensor

A new kind of magnetic grid displacement sensor is designed in this paper, which is composed of magnetic head and magnetic grid. The magnetic head contains arrays of linear hall element, and the magnetic grid is made of arrays of permanent magnet. In order to enhance the quality of original voltage signal, the signal generator adopts three-phase and six components. The errors caused by assemble and zero drift is eliminated through difference. Otherwise, the electromagnetic field of magnetic signal generator is analyzed with ANSYS. The assemblage gap of magnetic head can be chosen better according to the analysis result, which can improve the signal quality also. A look-up table technique is presented when dealing with magnetic grid signal, which can decreases the computational complexity of the processing chip. And the method is realized through the flush type SCM(dsPIC33FJ64MC706) with 16 bits. The peripheral circuit is simplified, which meets the requirement of miniaturization and increases the resolution and reliability of the magnetic grid displacement sensor.

Adaptive gain scheduling with feedforward control system based on system model for PMSM

ABSTRACT A feedforward controller for permanent magnet synchronous motor (PMSM) has been proposed in this study, and proportional and integral gain could be self-adaptive under different operating conditions. The control structure used in the feedforward system is the same as in the feedback control system. This control structure could guarantee independence of the speed command input to output with the disturbance input to output, which makes the system have better reference trajectory tracking and disturbances rejection. In order to obtain optimal control performance when the parameters are uncertain, a gain scheduling adaptive controller is used in the feedforward system. The proposed controller has been verified by the experimental and simulation results with less steady-state error and better dynamic response than the controllers without it under the condition of external load torque disturbance and PMSM parameter uncertainties.

A New Joint Localization Model Using Multiple Microphone Arrays for Passive Acoustic Source Localization System

The geometrical construction, the number of the microphone and spacing between microphones can affect the acoustic source localization accuracy based on the microphone array (namely acoustic sensor). Presently, the joint localization model using multiple microphone arrays has been widespread concerned because of its wider localization scope, higher robustness and localization accuracy compared with the single microphone array model. Yet, the increase of the number of the microphone in joint localization model with multiple microphone arrays can lead to increase the complexity of the localization system structure and computation, as well as the localization time. So, for this problem, this paper proposes a new joint localization model using multiple microphone arrays based on the generalized cross-correlation method. The simulated results show that the established joint localization model using multiple microphone arrays can accurately locate acoustic source position under the conditions of decreasing the number of the microphone.

Study on high precision magnetic encoder based on PMSM sensorless control

Purpose To eliminate the angle deviation of magnetic encoder, this paper aims to propose a compensation method based on permanent magnet synchronous motor (PMSM) sensorless control. The paper also describes the experiments performed to verify the validity of this proposed method. Design/methodology/approach The proposed method uses PMSM sensorless control method to get high precision virtual angle value, and then get the deviation value between virtual position and magnetic angle which is used as compensation table. Oversampling linear interpolation tabulation method has been proposed to eliminate the noise signals. Finally, a magnetic encoder with precision (repeatability) 0.09° and unidirectional motion precision 0.03 is realized. The control system with an encoder running at 14,000 and 0.01 r/min showing high motion resolution is also realized. Findings Higher value of current in PMSM leads to a magnetic encoder with higher precision. When using oversampling linear interpolation to tabulate the compensation table, it is understood that more oversampling does not lead to a better result. Finally, validated by experiments, using eight intervals to calculate the mean value of angle deviation leads to the best result. Practical implications The angle deviation compensation method proposed in this paper has a great practical implication and a good commercial application. The method proposed in this paper could be effectively used to self-correct the magnetic encoder using arctangent method and also correct any rotary encoder sensor. Originality/value This paper originally proposes an adaptive correction method for a rotary encoder based on PMSM sensorless control. To eliminate the noise signals in an angle compensation table, over-sampling linear interpolation tabulation method has been proposed which also guarantees the precision of the compensation table.

A hybrid PWM strategy combining modified space vector and sinusoidal pulse width modulation methods

In this paper, a method of combining modified space vector control (SVPWM) and sinusoidal pulse width modulation (SPWM) control has been proposed for the three-phase permanent magnet synchronous motor (PMSM). This method solves the problem of the torque ripple when the motor starts running and the hardness to control zero axis component when use SVPWM control method. The proposed method uses SPWM control method when the motor starts running or low speed to ensure the stability of the zero axis component of the control system, and utilize the SVPWM method when the motor at high speed to ensure the stability of the torque ripple of the system. So the method made full use of the advantages of SVPWM and SPWM method respectively. Dynamic response and power quality performance are comparatively analyzed for this method. This method uses PI- IP control structure to further improve the robustness of the control system and the response performance. The simulation and experimental results show the dynamic response of the control structure. In order to guarantee the validity of the data, utilize a high precision identification system to guarantee the precision of the parameter used in control system. This paper gives a detailed description of how to use the method mentioned to realize the PWM output and the control structure used. This method is more efficiently and generates less harmonic distortion when compared with traditional method.

A fast filtering algorithm using the transmission mechanism of human auditory information and its application on quadruped robot speed tracking

This paper develops a fast filtering algorithm based on the transmission mechanism of human auditory information. By integrating the function of cochlea tuning and short-term synaptic plasticity, the derived details and the feasible parameter criterion under minimum error variance condition are discussed. For illustration, the developed fast filtering algorithm is applied to the speed tracking of quadruped robot walks. The comparison with the Kalman filtering method is given from two aspects, the tracking performance and the tracking speed. Both the two illustrate the high-efficiency of developed fast filtering algorithm.