Vehicle dynamics

About: Vehicle dynamics is a research topic. Over the lifetime, 12909 publications have been published within this topic receiving 204091 citations.

Adaptive sliding mode control of autonomous underwater vehicles in the dive plane

Abstract: The problem of controlling an autonomous underwater vehicle (AUV) in a diving maneuver is addressed. Having a simple controller which performs satisfactorily in the presence of dynamical uncertainties calls for a design using the sliding mode approach, based on a dominant linear model and bounds on the nonlinear perturbations of the dynamics. Nonadaptive and adaptive techniques are considered, leading to the design of robust controllers that can adjust to changing dynamics and operating conditions. The problem of using the observed state in the control design is addressed, leading to a sliding mode control system based on input-output signals in terms of drive-phase command and depth measurement. Numerical simulations using a full set of nonlinear equations of motion show the effectiveness of the proposed techniques. >

Free-Locomotion of Underwater Vehicles Actuated by Ionic Polymer Metal Composites

Abstract: In this paper, we develop a modeling framework for studying free-locomotion of biomimetic underwater vehicles propelled by vibrating ionic polymer metal composites (IPMCs). The motion of the vehicle body is described using rigid body dynamics in fluid environments. Hydrodynamic effects, such as added mass and damping, are included in the model to enable a thorough description of the vehicle's surge, sway, and yaw motions. The time-varying actions exerted by the vibrating IPMC on the vehicle body, including thrust, lift, and moment, are estimated by combining force and vibration measurements with reduced order modeling based on modal analysis. The model predictions are validated through experimental results on a miniature remotely controlled fish-like robotic swimmer.

Development and Experimental Evaluation of a Slip Angle Estimator for Vehicle Stability Control

Abstract: Real-time knowledge of the slip angle in a vehicle is useful in many active vehicle safety applications, including yaw stability control, rollover prevention, and lane departure avoidance. Sensors to measure slip angle, including two-antenna GPS systems and optical sensors, are too expensive for ordinary automotive applications. This paper develops a real-time algorithm for estimation of slip angle using inexpensive sensors normally available for yaw stability control applications. The algorithm utilizes a combination of model-based estimation and kinematics-based estimation. Compared with previously published results on slip angle estimation, this present paper compensates for the presence of road bank angle and variations in tire-road characteristics. The developed algorithm is evaluated through experimental tests on a Volvo XC90 sport utility vehicle. Detailed experimental results show that the developed system can reliably estimate slip angle for a variety of test maneuvers.

Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle

Abstract: This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.

Dynamic motion planning of autonomous vehicles

Abstract: A method for planning the motions of autonomous vehicles moving on general terrains is presented that obtains the geometric path and vehicle speeds that minimize motion time considering vehicle dynamics, terrain topography, obstacles, and surface mobility. The terrain is represented by a smooth cubic B patch, and the geometric path consists of a B spline curve mapped to the surface. The time-optimal motions are computed by first obtaining the best obstacle-free path from all paths represented by a uniform grid. This path is further optimized using a local optimization procedure, using the optimal motion time along the path as the cost function and the control points of a B spline as the optimizing parameters. Examples are presented that demonstrate the method for a simple dynamic model of a vehicle moving on mountainous terrain. >