Wook Bahn

Application of adaptive notch filter for resonance suppression in industrial servo systems

This paper presents an application of an adaptive notch filter (ANF) for resonance suppression in industrial servo systems. An on-line frequency estimator is utilized for estimating the resonant frequency. The current command of the servo system is an input to the frequency estimator. The ANF automatically changes its notch frequency according to the estimated resonant frequency values and suppress the resonance. Experiments are performed using an industrial servo system with a belt-drive type load for various load conditions. Results show that the controller with the developed ANF identifies the changes in the resonant frequency well and therefore successfully suppresses the resonance.

Mobile robot vision tracking system using Unscented Kalman Filter

This paper introduces a vision tracking system for mobile robot by using Unscented Kalman Filter (UKF). The proposed system accurately estimates the position and orientation of the mobile robot by integrating information received from encoders, inertial sensors, and active beacons. These position and orientation estimates are used to rotate the camera towards the target during robot motion. The UKF, used as an efficient sensor fusion algorithm, is an advanced filtering technique which reduces the position and orientation errors of the sensors. The designed system compensates for the slip error by switching between two different UKF models, which are designed for slip and no-slip cases, respectively. The slip detector is used to detect the slip condition by comparing the data from the accelerometer and encoder to select the either UKF model as the output of the system. The experimental results show that proposed system is able to locate robot position with significantly reduced position errors and successful tracking of the target for various environments and robot motion scenarios.

Tuningless servo controller using variable structure control and disturbance compensation

This paper presents a new tuningless control algorithm for a DC servo drive to minimize parameter tuning efforts by an operator. This tuningless algorithm is based on a nonlinear control method, utilizing variable structure control and disturbance compensator. Experiments are performed using a 400 W Tamagawa servo motor and a belt drive load, which is a common combination in automation applications. The performance of the developed method is compared with the conventional servo drive controller, which is manually tuned by an experienced engineer. The experimental results show that the developed tuningless control exhibits excellent performance and is applicable to various load conditions.

A 16-bit ultra-thin tri-axes capacitive microaccelerometer for mobile application

A 16-bit ultra-thin tri-axes capacitive microaccelerometer is presented, where tri-axes MEMS (microrlectromechanical systems) sensing elements, capacitive readout ASIC (application specific integrated circuit), and EEPROM (electrically erasable and programmable read only memory) are integrated to an ultra-thin LGA (land grid array) package. The input range and input-output non-linearity of x/y-axis channel is measured to be plusmn1.5 g and 0.35% FSO, respectively. The input range and input-output non-linearity of z-axis accelerometer channel are measured to be plusmn1.5 g and 0.19% FSO, respectively. The fabricated microaccelerometer system is suitable for many applications, including robots, game interfaces and mobile phone input interfaces.

Decoupled disturbance compensation under control saturation with discrete-time variable structure control method in industrial servo systems

This paper presents a new decoupled disturbance compensation scheme with discrete-time variable structure control, to provide asymptotic convergence property even when the control input is driven beyond saturation limits. Discrete-time variable structure control (DVSC) method with a decoupled disturbance compensator (DDC) has been widely used in many applications, attributed to the robust properties in the presence of external disturbances and parametric uncertainties. However, when the control input is driven beyond saturation limits, the DVSC method with DDC cannot provide robust performance. This paper develops a disturbance estimation scheme that can maintain the asymptotic convergence property of the disturbance estimation error dynamics in the presence of control saturation. Experiments are performed on a servo system, and experimental results show that the developed method performs well in the presence of control input saturation.

Discrete-derivative method for adaptive-notch-filter based frequency estimators

This paper presents a new discrete-derivative method for adaptive-notch-filter (ANF) based frequency estimators to reduce frequency estimation errors. Frequency estimators generally require the first derivative of the filter state. However, differentiating the filter state in the discrete-time domain can result in large estimation errors. If a finite difference method is used, the frequency estimation results in a large amount of errors when the input signal contains high frequency components. The bilinear transform method does not cause the high frequency problems, but causes an oscillation problem due to the finite poles and zeros used to approximate the continuous differentiation operation. In this paper, a modification of the bilinear transform method is proposed. The proposed method can differentiate the high frequency signal without the oscillation problem. Numerical simulations are performed, and the results show the effectiveness of the proposed method.

A kalman-filter-based tuning method for input shapers in servo systems

This paper presents a new tuning method for input shapers in industrial servo systems. The input shaper is an FIR filter for removing endpoint vibration effects of a control system. The input shaper has a sequence of impulses to produce a response for canceling out the endpoint vibration. To determine the values of impulses of the input shaper, prior knowledge about system characteristics or endpoint vibrations is required. In this paper, we proposed a new automatic tuning method for the input shaper using the decaying sinusoidal signal model and an extended Kalman filter. The proposed method does not require any iteration or repetitive motion to estimate the vibration parameters. Furthermore, the method uses the stable filter to estimate the vibration parameters. Experiment results for an industrial servo system show that the input shaper which is tuned by using the estimated parameters of the proposed method successfully removes the endpoint vibration of the system.

Control of 400 Watt Belt-Drive and 400 Watt Ball-Screw Servo Systems Using Discrete-Time Variable Structure Control

Abstract This paper develops a discrete-time variable structure control method for servo drives. The objective is to achieve tungless control in industrial servo systems. The developed control method is experimentally evaluated for load variations and parameter uncertainties. Experiments are performed on typical automation applications: a 400 W servo motor with a belt-drive connection and a 400 W servo motor with a ball-screw connection. The experimental results show that the developed discrete-time variable structure controller provides better performance characteristics than the conventional commercial servo controller.

Several methods of sensor fusion for vision tracking in mobile robots

This paper presents several different sensor-fusion methods for vision tracking, to keep a cameras line of sight on a target. The data-fusion methods in this paper use several combinations of vision and motion information. The vision information is acquired through a vision processing ASIC (Application-Specific Integrated Circuit), which has an ODR (Output Data Rate) of 27 Hz. The motion information is acquired through one or more sensors, comprising a 3-axis accelerometer, a 3-axis gyroscope, and robot wheel encoders, which have the ODR of 100Hz, 100Hz, and 50 Hz, respectively. Several data-fusion scenarios are tested with these different sensors. An extended kalman filter and an appropriate data-fusion method are applied to each method. Also tested for comparison is a vision-only scenario with a slower ODR of 6.75 Hz. The vision-only method with the fast ODR of 27 Hz performs reasonably well. However, the slower case with the ODR of 6.75 Hz does not provide an adequate performance. The sensor-fusion method that uses all three motion sensors and a vision sensor greatly improves the target tracking performance, regardless of the vision sensor ODR. The motion sensors used are very low cost mass production sensors, found commonly in mobile phones. The proposed method presents a viable solution for target tracking in mobile robots.

A robotic pan and tilt 3-d target tracking system by data fusion of vision, encoder, accelerometer, and gyroscope measurements

This paper presents a vision-tracking system for mobile robots, which travel in a 3-dimentional environment. The developed system controls pan and tilt actuators attached to a camera so that a target is always directly in the line of sight of the camera. This is achieved by using data from robot wheel encoders, a 3-axis accelerometer, a 3-axis gyroscope, pan and tilt motor encoders, and camera. The developed system is a multi-rate sampled data system, where the sampling rate of the camera is different with that of the other sensors. For the accurate estimation of the robot velocity, the developed system detects the slip of robot wheels, by comparing the data from the encoders and the accelerometer. The developed system estimates the target position by using an extended Kalman filter. The experiments are performed to show the tracking performance of the developed system in several motion scenarios, including climbing slopes and slip cases.