Browsing by Author "Hsu, Ling-Yuan"

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A Constrained Wheel Torque Controller for Lane Following System Using Control Distribution
(2010)
Hsu, Ling-Yuan
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Weng, Kent
;
Chen, Tsung-Lin
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機械工程學系
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Department of Mechanical Engineering
A lane following system is proposed that employs four constrained wheel torques to regulate a vehicle on a reference trajectory. The proposed control algorithm was developed by combining several techniques such as: DYC method, hierarchical control architecture, sliding mode controls, control distributions, and etc. Different from existing approaches, the proposed method has the following advantages: (1) it can be implemented on two-wheel drive vehicles; (2) the error resulting from the hierarchical architecture are minimized and compensated; (3) the controlled wheel torque calculated by the control distribution method is an analytical solution instead of from numerical search. The proposed controller is evaluated by simulations on two more complex vehicle models: a full-state vehicle model and a sedan model from commercial software Carsim. Simulation results indicate that, in both cases, the proposed method can regulate the vehicle to finish a single lane change when the vehicle is moving at an initial speed of 90 km/hr.
An Optimal Wheel Torque Distribution Controller for Automated Vehicle Trajectory Following
(2013-07-01)
Hsu, Ling-Yuan
;
Chen, Tsung-Lin
;
機械工程學系
;
Department of Mechanical Engineering
This paper proposes an automated vehicle trajectory following system that uses four constrained wheel torques to regulate a vehicle on a reference trajectory. The constrained wheel torques can be achieved using the two-wheel drive and differential brakes. The proposed control algorithm is developed using the following steps. First, the sliding-mode control is used to find stability constraints for trajectory following when the vehicle system is subjected to modeling errors. Second, these stability constraints, along with other actuator constraints, are particularly tuned for the proposed control distribution method. The proposed control distribution method determines four longitudinal tire forces and minimizes actuator control efforts. Finally, these tire forces are converted to traction/braking wheel torques. The proposed method has the following advantages: 1) It achieves both robust trajectory following and optimal control efforts, 2) the optimal control effort is obtained analytically instead of from a numerical search, and 3) the robust performance of this vehicle control system can be theoretically verified. The proposed method is evaluated using numerical simulations on two front-drive vehicle models: a full-state vehicle model and a sedan model from the Carsim commercial software. The simulation results indicate that, in both cases, the proposed method can regulate the vehicle to finish a "double-lane change" when the vehicle is moving at an initial speed of 90 km/h. The maximum lateral acceleration is 6.56 m/s(2), and the regulated position error is less than 6.9 cm.
Applying a Three-Antenna GPS and Suspension Displacement Sensors to a Road Vehicle
(2009)
Hsu, Ling-Yuan
;
Chen, Tsung-Lin
;
機械工程學系
;
Department of Mechanical Engineering
This paper presents a novel sensor fusion system for road vehicles, which mainly composed of a three-antenna global positioning system (GPS), and four suspension displacement sensors. This sensor system not only obtains accurate six degree-of-freedom (DOF) information for vehicle dynamics but also road angles in real time. The road angles and vehicle attitude are difficult to be detected using on-board sensors because they are often coupled in the sensor measurements. Most approaches ignore this coupling effect; only a few try to obtain them by state estimations using vehicle models. The proposed method solve this problem, without requiring any vehicle model, by incorporating a non-inertial sensor (suspension displacement sensors) with inertial sensors (three-antenna GPS). In a demonstrating case, an additional inertial measurement unit (IMU) is included in the senor system to improve the estimation accuracy. Simulation results indicate that the accuracy of the estimated vehicle attitude is less than 0.85 deg, and that of the estimated road angles is less than 0.3 deg. Additionally, the estimation accuracy of the vertical displacement is improved from 3 m to 0.248 m.
Estimating Road Angles With the Knowledge of the Vehicle Yaw Angle
(2010-05-01)
Hsu, Ling-Yuan
;
Chen, Tsung-Lin
;
機械工程學系
;
Department of Mechanical Engineering
This paper presents a method of estimating road angles using state observers and three types of sensors (lateral acceleration sensors, longitudinal velocity sensors, and suspension displacement sensors). The proposed method differs from those in most existing literature in three aspects. First, a "full-state" vehicle model is used to describe nonlinear vehicle dynamics on a sloped road. Second, "switching observer" techniques are used to suggest suitable sensors and to construct state observers. Lastly, the road angles are described by three Euler angles, and two of them are estimated simultaneously. The analysis indicates that (1) road angles affect vehicle dynamics through components of the gravitational force acting on the vehicle body. These gravitational forces can be correctly estimated with an estimation accuracy less than 7.5%, even when road angles vary with time. (2) Those road angles can be correctly estimated only when the vehicle yaw angle is known.
SYSTEM AND METHOD FOR ROAD ANGLE ESTIMATION
(2010-04-22)
Chen, Tsung-Lin
;
Hsu, Ling-Yuan
A system and method for estimating road angles of a road on which a moving body is traveling are disclosed. The road angle estimation system includes: a sensing module adapted to be mounted on the moving body to detect a plurality of pieces of measurement information associated with the moving body; and a calculating module coupled to the sensing module to receive the pieces of measurement information therefrom. The calculating module simultaneously calculates an estimated bank angle and an estimated grade angle on the basis of the pieces of measurement information, a plurality of support parameters, and a plurality of user control parameters.
Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions
(2012-11-01)
Hsu, Ling-Yuan
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Chen, Tsung-Lin
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機械工程學系
;
Department of Mechanical Engineering
This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehiclemodel. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.
Vehicle Full-State Estimation and Prediction System Using State Observers
(2009-07-01)
Hsu, Ling-Yuan
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Chen, Tsung-Lin
;
機械工程學系
;
Department of Mechanical Engineering
This paper presents a novel vehicle full-state estimation and prediction system that employs a "full-state vehicle model" together with lateral acceleration, longitudinal velocity, and suspension displacement sensors to obtain the current and future vehicle state information. The full-state vehicle model is a vehicle model with 6 degrees of freedom (DOFs) and is described by 20-state nonlinear differential equations. The proposed approach differs from those in most of the existing literatures in three aspects. First, the road angles and the nonlinear suspension systems are incorporated into the vehicle modeling. Second, the "switching observer scheme" is introduced to significantly reduce the heavy work load that is required for the mathematical derivations. Finally, the full-state vehicle model is employed to predict the vehicle dynamics at future times. The simulation results show that the proposed system can accurately estimate and predict the state values. The relative accuracy of the state estimation is 2.66% on average and 2.86% on average of the state prediction. Furthermore, the proposed system can predict whether the vehicle rollover will occur when a vehicle performs a quick turn on a slope road.