• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.7
• /
• pp.615-620
• /
• 2015

DOB (Disturbance Observer) is an useful control method for estimating the disturbance applied to dynamic systems. Disturbance observer can be used to implement a robust control system to generate a control input for rejecting the disturbance, and it can be also used to estimate the disturbance to obtain information. The system that uses disturbance estimation is investigated for high performance control such as automatic door systems, walking robot and electric power steering system in vehicles. In this paper, a novel disturbance observer which is called disturbance and current observer for estimating load torque in the motor system is proposed. The difference between the DOB for disturbance rejection and DCOB is mathematically verified. Current and angular velocity are required for estimating the load torque of the motor in DOB. However, the DCOB can estimate load torque and current without current sensor. DCOB is designed based on modeling of the motor system. Appropriate Q-filter is selected and the applicability of DCOB is verified by simulation. The estimated disturbance and current of the electric motor can be verified without current sensor, as experiments of the actual motor system.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.4
• /
• pp.180-189
• /
• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.23 no.11 s.170
• /
• pp.1960-1969
• /
• 1999

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double rod type ERSU(electro-rheological suspension unit). A 16 degree-of-freedom model for the tracked vehicle is established by Lagrangian method followed by the formulation of a new sky-ground hook controller. This controller takes account for both the ride quality and the steering stability. The weighting parameter between the two performance requirements is adopted to adjust required performance characteristics with respect to the operation conditions such as road excitation. The parameter is appropriately determined by employing a fuzzy algorithm associated with the vehicle motion. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control system. Acceleration values at the driver's seat are analyzed under bump road profile, while frequency responses of vertical acceleration are investigated under random road excitation.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.25 no.6
• /
• pp.467-474
• /
• 2005

The expanded multi-Gaussian beam model has recently been developed that can calculate the radiation beam field from a single, rectangular transducer with great computational efficiency. In this study, this model is adopted to calculate the radiation beam field for a phased array transducer with various time delays to achieve steering and/or focusing. The calculation beam fields are compared to those obtained by well known Rayleigh-Sommerfeld integral that provides the exact solution in order to explore the validity of the expanded multi-Gaussian beam model And then, this study proposes a complete ultrasonic measurement model including the expanded beam model, far-field scattering model and system efficiency, Using the proposed model, phased array ultrasonic testing signals for a flat-bottomed hole with/without focusing were performed.

• Journal of Ocean Engineering and Technology
• /
• v.24 no.2
• /
• pp.10-17
• /
• 2010

Conventionally, because it is difficult to control a ship in shallow water and because attempting to do so creates unwanted environmental effects, maneuvering ships in the harbor area for berthing is usually done with the assistance of tugboats. In this paper, we propose a new method for berthing ships automatically by using bow and stern thrusters. Specifically, a steering motion model of a ship is considered, and parameters in the equation are evaluated by the system identification technique. An optimal controller based on observations was designed from the linearization of the non-linear ship motion in the horizontal plane. It is used to reduce the uncertainty about the ship's dynamics and reduce measurement requirements. The performance of the controller was also analyzed for its robustness relative to avoiding disturbing the environment due to winds, currents, and wave-drift forces. Experiments were conducted to estimate the potential for identifying result and the design of the controller. Specifically, in this paper, the system modeling and tracking control approach are discussed based on a two-degree-of-freedom (2DOF) servo-system design.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.408-412
• /
• 2003

Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.

• Transactions on Control, Automation and Systems Engineering
• /
• v.3 no.4
• /
• pp.210-216
• /
• 2001

In this paper, design of a 3-degree-of-freedom mobile robot with three caster wheels is performed. Initially, kinematic modeling and singularity analysis of the mobile robot is performed. It is found that the singularity can be avoided when the robot has more than two wheels on which two active joints are located. Optimal kinematic parameters of mobile robots with three active joint variables and with four active joint variables are obtained and compared with respect to kinematic isotropic index of the Jacobian matrix of the mobile robot which is functions of the wheel radius and the length of steering link.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.4 no.1
• /
• pp.63-74
• /
• 1996

Automatic transmission for heavy duty vehicles is a part of the power pack which includes steering and braking systems. This transmission in different from the one for passenger car. Therefore, in order to understand the trend of the important design parameters, maneuverability, acceleration performance and maximum speed, we need to analyze the total performance characteristics of the power transmission systems. In this study, modeling of the automatic transmission in heavy duty vehicle is carried out and the performance analysis method is presented. Results can be used for performance estimation data in the analysis for several combination method which determines the optimal parameters on the basis of penalty functions and weightings. And the estimation method of the important performance parameters such as engine inertia or power loss of engine by experiments is presented.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.621-626
• /
• 2019

The driver's steering wheel maneuver is a typical disturbance that causes excessive body motion and traveling instability of a vehicle. Abrupt and extreme operation can cause rollover depending on the geometric and dynamic characteristics, e.g., SUV vehicles. In this study, to cope with the performance limitation of conventional cars, fundamental research on the structurization of a control system was performed as follows. Mathematical modeling of the lateral behavior induced by driver input was carried out. A controller was designed to reduce the body motion based on this model. An algorithm was applied to secure robust control performance against modeling errors due to parameter uncertainty, $H_{\infty}$. Using the decoupled 1/4 car, a dynamic load simulating model considering the body moment was suggested. The simulation result showed the validity of the load-simulating model. The framework for a lateral behavior control system is proposed, including an experimental 1/4 vehicle unit, load simulating module, suspension control module, and hardware-in-the-loop simulation technology.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.10
• /
• pp.65-77
• /
• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.