• International Journal of Control, Automation, and Systems
• /
• v.2 no.3
• /
• pp.374-383
• /
• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• International Journal of Precision Engineering and Manufacturing
• /
• v.4 no.3
• /
• pp.28-35
• /
• 2003

The objective of the Vehicle Dynamics Control (VDC) system is to maintain vehicle stability under critical lateral motions, It has a good potential of becoming one of the chassis control necessities since the system can be realized with little additional cost on top of the ABS/TCS system, Developed in this research is a hardware-in-the-loop simulator for VDC with a valve control system that modulates the brake pressures at four wheels: Two VDC control logics, a simple control logic and an LQR control logic, have been developed and incorporated in the HILS system. Their performance under various driving conditions was tested in the HILS system and the results are presented.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.5
• /
• pp.257-263
• /
• 2022

Active stabilizers use signals such as steering angle, yaw rate, and lateral acceleration to vary the roll stiffness of the front and rear suspension depending on the vehicle's driving conditions, and are attracting attention as RSC (Roll Stability Control) system that suppresses roll when turning and improves ride comfort when going straight. Various studies have been conducted in relation to active stabilizer bars and RSC systems. However, accurate modeling of passive stabilizer model and active stabilizer model and vehicle dynamics analysis result verification are insufficient, and performance result analysis related to vehicle roll angle estimation and electric motor control is insufficient. Therefore, in this study, an accurate vehicle dynamics model was constructed by measuring the passive/active stabilizer bar model and component parameters. Based on this, the analysis result with high reliability was derived by comparing the roll angle estimation algorithm based on the lateral acceleration and suspension of the vehicle with the actual vehicle driving test result. In addition, it was intended to accurately analyze the motor torque characteristics and roll reduction effects of the electric motor-driven RSC system.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.257-257
• /
• 2000

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car Like robot was utilized to quit unwanted safety problem. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.

• International Journal of Ocean System Engineering
• /
• v.1 no.3
• /
• pp.120-135
• /
• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.690-699
• /
• 2008

In this paper a conventional approach for design and analysis of subsonic air vehicle is used. First of all subsonic aerodynamic coefficients are calculated using Computational Fluid Dynamics(CFD) tools and then wind-tunnel model was developed that integrates vehicle components including control surfaces and initial data is validated as well as refined to enhance aerodynamic efficiency of control surfaces. Experimental data and limited computational fluid dynamics solutions were obtained over a Mach number range of 0.5 to 0.8. The experimental data show the component build-up effects and the aerodynamic characteristics of the fully integrated configurations, including control surface effectiveness. The aerodynamic performance of the fully integrated configurations is comparable to previously tested subsonic vehicle models. Mathematical model of the dynamic equations in 6-Degree of Freedom(DOF) is then simulated using MATLAB/SIMULINK to simulate trajectory of vehicle. Effect of altitude on range, Mach no and stability is also shown. The approach presented here is suitable enough for preliminary conceptual design. The trajectory evaluation method devised accurately predicted the performance for the air vehicle studied. Formulas for the aerodynamic coefficients for this model are constructed to include the effects of several different aspects contributing to the aerodynamic performance of the vehicle. Characteristic parameter values of the model are compared with those found in a different set of similar air vehicle simulations. We execute a set of example problems which solve the dynamic equations to find the aircraft trajectory given specified control inputs.

• International Journal of Automotive Technology
• /
• v.5 no.2
• /
• pp.135-144
• /
• 2004

In this paper, the model-matching control in the longitudinal autonomous driving system is investigated by vehicle dynamics simulation, which contains nonlinear subcomponents and simplified subcomponents. The design of the robust model-matching controller is performed by the characteristics of the 2 degrees of freedom controller, which is composed of the feedforward compensator and the feedback compensator. It makes the characteristics of tractive and brake force to be equivalent to the specific transfer function, which is suggested as the reference model. Mathematical models of vehicle dynamic analysis including the model-matching control are constructed for computer simulation. Then, simple examples on open-loop simulation without any controller and closed loop simulation with the model-matching controller are applied to check the validity of the robust controller. As the practical example, the autonomous driving system in the longitudinal direction is adopted. It is proved that the model-matching control is effective and adequate to the disturbances and the perturbations, which are shown in the responses of the change of a vehicle mass and a road gradient.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.341-344
• /
• 1997

This paper presents a dynamics failure detection algorithm developed for the two-motor-driven electric vehicle system. The algorithm is based on the application of the fault detection filter. The fault detection includes the identification of sudden pressure drops of the two rear tires in driving axis and dynamics faults of the two inverter-motor-paired actuators An E.V. dynamics simulator is developed, which includes the modeling of the E.V. dynamics as well as the driving dynamics. The simulator, which allows the generation of various fault situations, is utilized in the verification of the developed fault detection algorithm. The results of the simulations are also presented.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.4 s.181
• /
• pp.44-51
• /
• 2006

This paper addresses sliding mode control of the anti-lock braking system (ABS) with a disturbance observer for model uncertainties such as vehicle parameter variation, un-modeled dynamics, and external disturbances. By using a nominal vehicle model, a sliding mode controller is designed to achieve a desired wheel slip ratio for ABS control. To compensate the model uncertainties, a disturbance observer is introduced with the help of a transfer function of a hydraulic brake dynamics. A proposed sliding mode controller with a disturbance observer is evaluated through simulations for model uncertainties. The simulation results show that the disturbance observer can enhance performances of sliding mode control for ABS.

• International Journal of Automotive Technology
• /
• v.7 no.2
• /
• pp.167-172
• /
• 2006

A design of controller for vehicle dynamic control(VDC) and its implementation on the real vehicle were introduced. The controller has been designed using a three-degrees-of-freedom(3DOF) yaw plane vehicle, and the control algorithm was implemented on the vehicle by control prototyping system dSPACE. A hybrid control algorithm, which makes full use of the advantages of robust and fuzzy control, was adopted in the control system. Field test results show that the performance of the vehicle handling dynamics with hybrid controller is improved obviously compared to that without VDC and with simple robust controller on skiddy roads(friction coefficients lower than 0.3).