Bong-Su Cho

Implementation of the Ultrasonic Local Positioning System using Dual Frequencies and Codes

This paper presents real-time algorithm for an ultrasonic Local Positioning System(LPS). An ultrasonic LPS consists of 4 transmitters and n receivers. Each transmitter transmits an sequential ultrasonic signal to avoid interference of ultrasonic signal. This method is a noneffective application for a fast object. Because receiver detects four sequential transmissive ultrasonic signal and calculates a position. This paper proposes the method which 4 transmitters transmit simultaneous ultrasonic signal and each transmitter distinguished by frequencies and codes. And Auto-Correlation Function(ACF) method separates codes from an ultrasonic echo signal which is interference of each transmitter`s code. If the receiver uses only ACF method, it is difficult to implement real time application for increased computation. This paper implements LPS using dual frequencies and ACF method. Using dual frequencies reduces codes length. The reduced codes length save computation in ACF. To prove this algorithm by experiment, high performance DSP(digital signal processor) used. The result shows the performance of the designed system is good enough positioning.

Implementation of MOST/CAN network protocol

This paper describes the protocol of the in-vehicle network. Nowadays, many cars adopt in-vehicle network for lightweight and maintenance. CAN is popular in-vehicle network for control data, and MOST is network for multimedia data. But CAN and MOST does not integrate and work independently. This paper suggests integration of MOST and CAN. The two networks have different characteristics such as data frame structure, transfer speed, network/bus configuration, etc. So, we implement the MOST/CAN converter that integrates protocols of the two networks by transmitting the CAN data using the MOST asynchronous data channel. To verify the performance of the MOST/CAN converter, we adopt the queuing model and the SAE benchmark data.

Position estimation using hyperbolic model for time difference of flight of ultrasonic

Three ultrasonic transmitters are in line at one side and transmit ultrasonic signals that contain different 9bit pseudo-random codes at the same time. The receiver measures time difference of flights (TDOFs) of transmitted signals by optimum correlation detection. According to TDOF, the possible position of the receiver is represented by hyperbolic curves. An intersection of the hyperbolic curves is the position of the receiver. The intersection is calculated by bisection method. The proposed system can be installed easily and the cost of installation is low. In the experimental results, the position errors become large when the receiver is at the position far from central transmitter and are correlated about (u, v) position.

Position estimation using time difference of flight of the multi-coded ultrasonic

The environment where mobile robots move is modeled as 2-dimensional space. Three ultrasonic receivers are in a line. The transmitters attached to the mobile robots transmit ultrasonic signals which contain different 9bit PR (pseudo-random) codes. The receiver calculates TDOFs (Time Difference of Flight) of each transmitted signals by CCF (Cross Correlation Function). According to TDOFs, the possible position of the mobile robot is represented by hyperbolic curves. The position of the mobile robot is an intersection of hyperbolic curves. The intersection is calculated by bisection method. The external device becomes simple compared to traditional method. The proposed system is verified experimentally.

A study on localization of the mobile robot using inertial sensors and wheel revolutions

INS (Inertial Navigation System) is composed of inertial sensors such as accelerometers and gyroscopes and navigation computer. INS can estimate attitude and position by itself with no outside help and has acceptable stability in the short time, but poor stability in the long time. If a navigation system uses only INS, position and attitude errors are accumulated. The most basic and simple localization method is using encoders attached to robots wheels. However, measuring errors occur due to the slip between of wheel and ground. In this paper, we discuss about position estimation of the mobile robot in indoor environment. In order to achieve the optimal solution, the error model of encoder system and the Kalman filter will be designed. The system described in this paper shows better accurate position information.

A Distance Estimation Algorithm Based on Multi-Code Ultrasonic Sensor and Received Signal Strength

This paper reveals a distance estimation algorithm based on multi-code ultrasonic and wireless sensor network. For measuring the distances among the sensor nodes, each ultrasonic transmitter transmits multi-code ultrasonic signal simultaneously. Receivers use cross correlation method to separate the coded signals. The information of measured distances is broadcasted to each sensor node by wireless sensor network. The wireless sensor network measures the distance among the sensor nodes using the received signal strength of the broadcasting. The multi-code ultrasonic have a limitation of measurable distance. And the received signal strength is affected from an environment. This paper measures a distance using ultrasonic and a received signal strength in short range. These measured data are applied to the least square estimation algorithm. By the expansion of the fitting curve, a distance measurement in long range using the received signal strength is compensated. The coupled system reduce the error to an acceptable level.

A Study of the Circuit for CPS Signal Using Magnetic Pickup

The basic signals for electronic engine control are velocity and degree of the engine cam shaft. The CPS sensor used for this signal and magnetic pick-up type CPS sensor is more popular. It is very important thing analyze this signal correctly. If there are some mistakes at the analysis, like a noise, The engine do not working at the best status, it will generate some noise, emit exhaust fumes and waste more gases. In general way to analysis this signal, you use zero-level detector circuit and in order to reduce the error you must use another sensor like a TDC sensor. In this paper, We proposed the analysis method using electronics circuits for magnetic pick-up type CPS sensor. We designed Comparison level detector circuit, Differential circuit and Full-rectifier circuit for detected the Long tooth and Short tooth level correctly without another sensor. We expected it is useful for more reliable engine control.

Implementation of the Mass Flow Controller using Adaptive PID

The MFC(Mass Flow Controller) is an equipment that measures and controls mass flow rates of fluid. Most of the HFC system is still using the PID algorithm. The PID algorithm shows superior performance on the MFC system. But the PID algorithm in the MFC system has a few problems as followed. The characteristic of the MFC system is changed according to the operating environment. And, when the piezo valve that uses the control valve is assembled in the MFC system, a coupling error is generated. Therefore, it is very difficult to find out the exact parameters of MFC system. In this paper, we propose adaptive PID algorithm in order to compensate these problems of a traditional PID algorithm. The adaptive PID algorithm estimates the parameters of MFC system using LMS(Least Mean Square) algorithm and calculates the coefficients of PID controller. Besides, adaptive PID algorithm shows better transient response because adaptive PID algorithm includes a feedforward. And we implement MFC system using proposed adaptive PID algorithm with self-tuning and Ziegler and Nickels`s method. Finally, comparative analysis of the proposed adaptive PID and the traditional PID is shown.