Constrained Model Predictive Control for dynamic path tracking of a bi-steerable rover on slippery grounds
The research works carried out in this paper deal with the control of a fast double-steering off-road mobile robot. Such kind of robots requires very high stable and accurate controllers because their mobility is particularly influenced by wheel–ground interactions. Hence, the vehicle dynamics shoul...
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| Published in: | Control engineering practice Vol. 107; p. 104693 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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01.02.2021
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| ISSN: | 0967-0661, 1873-6939 |
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| Abstract | The research works carried out in this paper deal with the control of a fast double-steering off-road mobile robot. Such kind of robots requires very high stable and accurate controllers because their mobility is particularly influenced by wheel–ground interactions. Hence, the vehicle dynamics should be incorporated in the control circuit to take into account these issues, which is developed based on the road geometry parameters and the slippage-friction conditions at the wheel–ground contacts. Relying on this dynamic model, we present in this paper the design and application of a constrained Model Predictive Control (MPC). It is based on the minimization of a cost function (optimizing the deviation from the reference trajectory, and the variation of the control input) along a finite prediction horizon, however, the prediction horizon is variable according to the forward speed of the robot. On the other hand, this approach incorporates several constraints, essentially important for the stability and safety of an off-road mobile robot moving at the high velocity, namely : saturation and maximum variations of the vehicle’s actuators (i.e. steering joints and their speeds limits) as well as the tire adhesion zone bounds (allowing to validate the assumption of a linear tire model). The full optimization problem is formulated as a Linearly Constrained Quadratic Programming (QP) to compute at each time-step the optimal and dynamically-consistent front and rear steering angles that are required to reach the desired path, with respect to all these constraints. The capabilities of our proposed controller are compared with another control law which does not apply any physical or intrinsic constraints. The latter is simply a feedback controller based on the same dynamic model and LQR theory (Linear Quadratic Regulator). Both of them have been investigated through several tests on simulations via ROS/GAZEBO and experiments on a real off-road vehicle for different kinds of trajectories and velocity levels.
•We propose a constrained MPC for dynamic path tracking dedicated to fast rovers.•The controller is formulated as a QP problem (tracking task and constraints).•Steering and sliding constraints are handled by the global QP problem.•The constrained MPC is compared to the LQR controller to emphasize its effectiveness.•To show their capabilities, experiments on a real off-road vehicle are conducted. |
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| AbstractList | The research works carried out in this paper deal with the control of a fast double-steering off-road mobile robot. Such kind of robots requires very high stable and accurate controllers because their mobility is particularly influenced by wheel–ground interactions. Hence, the vehicle dynamics should be incorporated in the control circuit to take into account these issues, which is developed based on the road geometry parameters and the slippage-friction conditions at the wheel–ground contacts. Relying on this dynamic model, we present in this paper the design and application of a constrained Model Predictive Control (MPC). It is based on the minimization of a cost function (optimizing the deviation from the reference trajectory, and the variation of the control input) along a finite prediction horizon, however, the prediction horizon is variable according to the forward speed of the robot. On the other hand, this approach incorporates several constraints, essentially important for the stability and safety of an off-road mobile robot moving at the high velocity, namely : saturation and maximum variations of the vehicle’s actuators (i.e. steering joints and their speeds limits) as well as the tire adhesion zone bounds (allowing to validate the assumption of a linear tire model). The full optimization problem is formulated as a Linearly Constrained Quadratic Programming (QP) to compute at each time-step the optimal and dynamically-consistent front and rear steering angles that are required to reach the desired path, with respect to all these constraints. The capabilities of our proposed controller are compared with another control law which does not apply any physical or intrinsic constraints. The latter is simply a feedback controller based on the same dynamic model and LQR theory (Linear Quadratic Regulator). Both of them have been investigated through several tests on simulations via ROS/GAZEBO and experiments on a real off-road vehicle for different kinds of trajectories and velocity levels. The research works carried out in this paper deal with the control of a fast double-steering off-road mobile robot. Such kind of robots requires very high stable and accurate controllers because their mobility is particularly influenced by wheel–ground interactions. Hence, the vehicle dynamics should be incorporated in the control circuit to take into account these issues, which is developed based on the road geometry parameters and the slippage-friction conditions at the wheel–ground contacts. Relying on this dynamic model, we present in this paper the design and application of a constrained Model Predictive Control (MPC). It is based on the minimization of a cost function (optimizing the deviation from the reference trajectory, and the variation of the control input) along a finite prediction horizon, however, the prediction horizon is variable according to the forward speed of the robot. On the other hand, this approach incorporates several constraints, essentially important for the stability and safety of an off-road mobile robot moving at the high velocity, namely : saturation and maximum variations of the vehicle’s actuators (i.e. steering joints and their speeds limits) as well as the tire adhesion zone bounds (allowing to validate the assumption of a linear tire model). The full optimization problem is formulated as a Linearly Constrained Quadratic Programming (QP) to compute at each time-step the optimal and dynamically-consistent front and rear steering angles that are required to reach the desired path, with respect to all these constraints. The capabilities of our proposed controller are compared with another control law which does not apply any physical or intrinsic constraints. The latter is simply a feedback controller based on the same dynamic model and LQR theory (Linear Quadratic Regulator). Both of them have been investigated through several tests on simulations via ROS/GAZEBO and experiments on a real off-road vehicle for different kinds of trajectories and velocity levels. •We propose a constrained MPC for dynamic path tracking dedicated to fast rovers.•The controller is formulated as a QP problem (tracking task and constraints).•Steering and sliding constraints are handled by the global QP problem.•The constrained MPC is compared to the LQR controller to emphasize its effectiveness.•To show their capabilities, experiments on a real off-road vehicle are conducted. |
| ArticleNumber | 104693 |
| Author | Plumet, Frédéric Benamar, Faïz Du, Wenqian Fnadi, Mohamed |
| Author_xml | – sequence: 1 givenname: Mohamed surname: Fnadi fullname: Fnadi, Mohamed email: mohamed.fnadi@sorbonne-universite.fr – sequence: 2 givenname: Wenqian orcidid: 0000-0002-3352-0809 surname: Du fullname: Du, Wenqian – sequence: 3 givenname: Frédéric surname: Plumet fullname: Plumet, Frédéric – sequence: 4 givenname: Faïz surname: Benamar fullname: Benamar, Faïz |
| BackLink | https://hal.sorbonne-universite.fr/hal-03151883$$DView record in HAL |
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| Cites_doi | 10.1109/25.385930 10.1002/rob.20118 10.1002/rnc.4590050403 10.1002/rob.20319 10.1504/IJVAS.2005.008237 10.1016/j.conengprac.2012.09.009 10.1017/S0962492900002518 10.1016/j.trc.2015.09.011 10.1109/TCST.2007.894653 10.1017/S0263574715000260 10.3182/20140824-6-ZA-1003.01287 10.1007/s10846-016-0442-0 10.1109/TCST.2009.2017934 10.1016/j.mechmachtheory.2020.103984 10.1177/0278364916645661 10.1080/00423119608969210 |
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| Keywords | Off-road robot Slippage Quadratic programming Dynamics Model Predictive Control off-road robot slippage Quadratic Programming |
| Language | English |
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| SubjectTerms | Computer Science Dynamics Model Predictive Control Off-road robot Quadratic programming Slippage |
| Title | Constrained Model Predictive Control for dynamic path tracking of a bi-steerable rover on slippery grounds |
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