Optimal Path Tracking Control of Autonomous Vehicle: Adaptive Full-State Linear Quadratic Gaussian (LQG) Control

Linear Quadratic Gaussian (LQG) control is developed for a prestressed square membrane with bimorph actuators attached to it. The membrane is modeled using the finite element method and the membrane is assumed to be clamped on all edges. After obtaining the mass, damping, stiffness and input matrices in second order form using the weak form Finite Element Method (FEM), the problem is represented in first order form to develop the LQG controller. To study the robustness of the system, the control and observer gain matrices developed for the nominal system are applied to systems obtained from the nominal system by modifying material properties and prestress.

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Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Mathematical Problems in Engineering ◽

10.1155/2020/3108589 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18

Author(s):

Runqiao Liu ◽

Minxiang Wei ◽

Nan Sang ◽

Jianwei Wei

Keyword(s):

Autonomous Vehicles ◽

Tracking Control ◽

Spline Interpolation ◽

Lateral Displacement ◽

Autonomous Vehicle ◽

State Parameter ◽

Front Wheel ◽

Path Tracking ◽

Adhesion Coefficient ◽

Polar Coordinate

Curved path tracking control is one of the most important functions of autonomous vehicles. First, small turning radius circular bends considering bend quadrant and travel direction restrictions are planned by polar coordinate equations. Second, an estimator of a vehicle state parameter and road adhesion coefficient based on an extended Kalman filter is designed. To improve the convenience and accuracy of the estimator, the combined slip theory, trigonometric function group fitting, and cubic spline interpolation are used to estimate the longitudinal and lateral forces of the tire model (215/55 R17). Third, to minimize the lateral displacement and yaw angle tracking errors of a four-wheel steering (4WS) vehicle, the front-wheel steering angle of the 4WS vehicle is corrected by a model predictive control (MPC) feed-back controller. Finally, CarSim® simulation results show that the 4WS autonomous vehicle based on the MPC feed-back controller can not only significantly improve the curved path tracking performance but also effectively reduce the probability of drifting or rushing out of the runway at high speeds and on low-adhesion roads.

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MPC based path tracking control for autonomous vehicle with multi-constraints

2017 International Conference on Advanced Mechatronic Systems (ICAMechS) ◽

10.1109/icamechs.2017.8316521 ◽

2017 ◽

Cited By ~ 2

Author(s):

Mengyuan Chen ◽

Yue Ren

Keyword(s):

Tracking Control ◽

Autonomous Vehicle ◽

Path Tracking

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Adaptive linear quadratic gaussian (LQG) control of a bioreactor

Journal of Chemical Technology & Biotechnology ◽

10.1002/jctb.280530205 ◽

2007 ◽

Vol 53 (2) ◽

pp. 133-141 ◽

Cited By ~ 3

Author(s):

G. Roux ◽

B. Dahhou ◽

K. Najim ◽

I. Queinnec

Keyword(s):

Linear Quadratic ◽

Linear Quadratic Gaussian ◽

Lqg Control

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Motion control of a cruise ship by using active stabilizing fins

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment ◽

10.1177/1475090211421268 ◽

2011 ◽

Vol 225 (4) ◽

pp. 311-324 ◽

Cited By ~ 1

Author(s):

J-H Kim ◽

Y-H Kim

Keyword(s):

Motion Control ◽

Control Algorithm ◽

Roll Motion ◽

Cruise Ship ◽

Linear Quadratic ◽

Linear Quadratic Gaussian ◽

Lqg Control ◽

Induced Motion ◽

The Time Domain ◽

Wave Induced

The present study considers the motion control of a cruise ship by using active stabilizing fins. One or two pairs of stabilizing fins are equipped to reduce the roll and/or pitch motions of the cruise ship. Each fin is controlled by algorithms based on proportional–integral–derivative (PID) and linear quadratic Gaussian (LQG) control. Numerical analysis of the wave-induced motion of a cruise ship with stabilizing fins is carried out by using the time-domain ship motion program which has been developed through this study. The resultant motion response as the performance of each controller is compared between different control algorithms. Based on the present simulation results, the stabilizing fin can be considered a good instrument to reduce pitch motion as well as roll motion of the present cruise ship model. The present results show that the PID control algorithm, a simple but practical algorithm, can be an appropriate method to reduce the roll motion in a moderate sea state, while the LQG control algorithm shows good performance in reducing not only the roll motion but also the coupled roll and pitch motions simultaneously in all of environmental conditions considered.

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