| 1. |
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| 2. |
- Borrelli, Francesco, et al.
(författare)
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MPC-based approach to active steering for autonomous vehicle systems
- 2005
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Ingår i: International Journal on Vehicle Autonomous Systems. ; 3:2/3/4, s. 265--291-
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Tidskriftsartikel (refereegranskat)abstract
- In this paper a novel approach to autonomous steering systems is presented. A model predictive control (MPC) scheme is designed in order to stabilize a vehicle along a desired path while fulfilling its physical constraints. Simulation results show the benefits of the systematic control methodology used. In particular we show how very effective steering manoeuvres are obtained as a result of the MPC feedback policy. Moreover, we highlight the trade off between the vehicle speed and the required preview on the desired path in order to stabilize the vehicle. The paper concludes with highlights on future research and on the necessary steps for experimental validation of the approach.
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| 3. |
- Falcone, Paolo, 1977, et al.
(författare)
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A Hierarchical Model Predictive Control Framework for Autonomous Ground Vehicles
- 2008
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Ingår i: American Control Conference. - 0743-1619. - 9781424420797 ; , s. 3719 - 3724
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Konferensbidrag (refereegranskat)abstract
- A hierarchical framework based on Model Predictive Control (MPC) for autonomous vehicles is presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle while fulfilling various physical and design constraints.We start from the low-level active steering-controller presented in [3], [9] and integrate it with a high level trajectory planner. At both levels MPC design is used. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model. At the low-level a MPC controller computes the vehicle inputs in order to best follow the desired trajectory based on detailed nonlinear vehicle model.This article presents the approach, the method for implementing it, and successful preliminary simulative results on slippery roads at high entry speed.
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| 4. |
- Falcone, Paolo, 1977, et al.
(författare)
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A Model Predictive Control Approach for Combined Braking and Steering in Autonomous Vehicles
- 2007
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Ingår i: 15th Mediterranean Conference on Control and Automation, Athens, Greece, June 2007.
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a Model Predictive Control (MPC) approach for combined braking and steering systems in autonomous vehicles. We start from the result presented in [1] and [2], where a Model Predictive Controller (MPC) for autonomous steering systems has been presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle and the brakes at the four wheels independently, while fulfilling various physical and design constraints.
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| 5. |
- Falcone, Paolo, 1977, et al.
(författare)
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A Real-Time Model Predictive Control Approach for Autonomous Active Steering
- 2006
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Ingår i: First IFAC International workshop on NMPC for Fast Systems, Grenoble, France, October 2006.
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Konferensbidrag (refereegranskat)abstract
- The problem of controlling the front steering to stabilize a vehicle along a desired path is tackled in this paper. Although a Non-LinearModel Predictive Control (NLMPC) approach can achieve good performance and constraints fulfillment, its computational burden does not allow a real-time implementation. In order to decrease the complexity of the controller, in this paper we propose a suboptimal MPC scheme based on successive on-line linearizations of the non-linear vehicle model. The method stems from an accurate analysis of the vehicle nonlinearities, the constraints and the performance index in the optimal control problem. The simulation results show a significant reduction of the controller complexity, with a small loss of performances respect to a NLMPC controller. The suboptimal MPC control policy is compared to the control policy of a robot driver from Ford Motor Company.We show that better performance can be achieved with a smaller control effort, without violating vehicle physical constraints, by using a systematic control design procedure.
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| 6. |
- Falcone, Paolo, 1977, et al.
(författare)
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Experimental Validation of Integrated Steering and Braking Model Predictive Control
- 2009
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Ingår i: International Journal of Vehicle Autonomous Systems. - 1471-0226 .- 1741-5306. ; 7:3/4, s. 292-309
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we present and discuss an in-vehicle experimental validation of an integrated steering and braking Model Predictive Control (MPC) algorithm. The experimental results are obtained in autonomous path following tests, where the vehicle has to autonomously perform a double lane change maneuver by simultaneously coordinating the front steering and the braking torques at the four wheels.The maneuvers are performed at high speed on slippery surfaces in order tooperate close to the vehicle stability limits.The proposed controller is an MPC based on successive on-line linearizations of the nonlinear vehicle model. Experimental tests of a double lane change maneuvers at 70 Kph are shown and complex countersteering maneuvers are presented and discussed.
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| 7. |
- Falcone, Paolo, 1977, et al.
(författare)
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Integrated Braking and Steering Model Predictive Control Approach in Autonomous Vehicles
- 2007
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Ingår i: 5-th IFAC Symposium on Advances in Automotive Control, Berkeley, CA, USA, August 2007.
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a Model Predictive Control (MPC) approach for combined braking and steering systems in autonomous vehicles. We start from the result presented in (Borrelli et al. (2005)) and (Falcone et al. (2007a)), wherea Model Predictive Controller (MPC) for autonomous steering systems has been presented. As in (Borrelli et al. (2005)) and (Falcone et al. (2007a)) we formulate an MPC control problem in order to stabilize a vehicle along a desired path. In the present paper, the control objective is to best follow a given path by controlling the front steering angle and the brakes at the four wheels independently, while fulfilling various physical and design constraints.
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| 8. |
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| 9. |
- Falcone, Paolo, 1977, et al.
(författare)
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Linear Time Varying Model Predictive Control and its Application to Active Steering Systems: Stability Analysis and Experimental Validation
- 2008
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Ingår i: International Journal of Robust and Nonlinear Control. - : Wiley. - 1099-1239 .- 1049-8923. ; 18:8, s. 862-875
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Tidskriftsartikel (refereegranskat)abstract
- A Model Predictive Control (MPC) approach for controlling an Active Front Steering (AFS) system in an autonomous vehicle is presented. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed. We start from the results presented in [2], [6] and formulate the MPC problem based on successive on-line linearization of the nonlinear vehicle model (LTV MPC). We present a sufficient stability conditions for such LTV MPC scheme. The condition is derived for a general class of nonlinear discrete time systems and results into an additional convex constraint to be included in the LTV MPC design. For the AFS control problem, we compare the proposed LTV MPC scheme against the LTV MPC scheme in [6] where stability has been enforced with an ad-hoc constraint. Simulation and experimental tests up to 21 m/s on icy roads show the effectiveness of the LTV MPC formulation.
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| 10. |
- Falcone, Paolo, 1977, et al.
(författare)
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Linear Time Varying Model Predictive Control Approach to the Integrated Vehicle Dynamics Control Problem in Autonomous Systems
- 2007
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Ingår i: 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, December 2007.
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Konferensbidrag (refereegranskat)abstract
- A Model Predictive Control (MPC) approach for controlling active front steering, active braking and active differentials in an autonomous vehicle is presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle, brakes and traction at the four wheels independently, while fulfilling various physical and design constraints. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the system inputs in order to best follow the desired trajectory on slippery roads at a given entry speed. We start from the results presented in [1], [2] and formulate the MPC problem based on successive on-line linearization of the nonlinear vehicle model (LTV MPC). Simulative results are presented, interpreted and compared against LTV MPC schemes which make use only of steering and/or braking.
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| 11. |
- Falcone, Paolo, 1977, et al.
(författare)
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Low Complexity MPC Schemes for Integrated Vehicle Dynamics Control Problems
- 2008
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Ingår i: 9th International Symposium on Advanced Vehicle Control (AVEC ’08).
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Konferensbidrag (refereegranskat)abstract
- A low complexity Model Predictive Control (MPC) approach to the problem of autonomous path following via combined steering and independent braking is presented in this paper. We start from the simpler approach in [5] and significantly improve the performance by better modeling the longitudinal dynamics and slightly increasing the number of optimization variables, i.e., the computational complexity. In order to assess the performance improvement, simulations are presented and compared against the results of the simpler approach in [5]. Moreover, experimental results are shown and discussed.
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| 12. |
- Falcone, Paolo, 1977, et al.
(författare)
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MPC-Based Yaw and Lateral Stabilization Via Active Front Steering and Braking
- 2008
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Ingår i: Vehicle System Dynamics. - : Informa UK Limited. - 1744-5159 .- 0042-3114. ; 46, Supplement:SUPPL.1, s. 611-628
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we propose a path following Model Predictive Control-based (MPC) scheme utilizing steering and braking. The control objective is to track a desired path for obstacle avoidance maneuver, by a combined use of braking and steering. The proposed control scheme relies on the Nonlinear MPC (NMPC) formulation we used in [1] and [2]. In this work, the NMPC formulation will be used in order to derive two different approaches. The first relies on a full tenth order vehicle model and has high computational burden. The second approach is based on a simplified bicycle model and has a lower computational complexity compared to the first. The effectiveness of the proposed approaches is demonstrated through simulations and experiments.
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| 13. |
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| 14. |
- Falcone, Paolo, 1977, et al.
(författare)
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Predictive Active Steering Control for Autonomous Vehicle Systems
- 2007
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Ingår i: IEEE Transactions on Control Systems Technology. ; 15:3, s. 566-580
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Tidskriftsartikel (refereegranskat)abstract
- In this paper a Model Predictive Control (MPC) approach for controlling an Active Front Steering system in an autonomous vehicle is presented. At each time step a trajectory in assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We present two approaches with different computational complexities. In the first approach we formulate the MPC problem by using a non-linear vehicle model. The second approach is based on successive on-line linearization of the vehicle model. Discussions on computational complexity and performance of the two schemes are presented. The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads.
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| 15. |
- Falcone, Paolo, 1977, et al.
(författare)
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Towards Real-Time Model Predictive Control Approach for Autonomous Active Steering
- 2006
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Ingår i: 8th International Symposium on Advanced Vehicle Control, Taipei, Taiwan, August 2006.
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Konferensbidrag (refereegranskat)abstract
- In this paper we follow the novel approach presented in [1] to autonomous active steering control design. A nonlinear Model Predictive Control (MPC) scheme is designed to control front wheel steering in order to stabilize a vehicle along a desired path while fulfilling its physical constraints.The proposed nonlinear MPC controller has been implemented in in real time by using advanced sensors, actuators and non-linear optimization solvers. This papers presents the experimental setup and the experimental results obtained at low vehicle speeds on icy roads with a passenger car.
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| 16. |
- Keviczky, Tamas, et al.
(författare)
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Predictive Control Approach to Autonomous Vehicle Steering
- 2006
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Ingår i: American Control Conference, Minneapolis, Minnesota, June 2006.
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Konferensbidrag (refereegranskat)abstract
- A model predictive control (MPC) approach to active steering is presented for autonomous vehicle systems. The controller is designed to stabilize a vehicle along a desired path while rejecting wind gusts and fulfilling its physical constraints. Simulation results of a side wind rejection scenario and a double lane change maneuver on slippery surfaces show the benefits of the systematic control methodology used. A trade-off between the vehicle speed and the required preview on the desired path for vehicle stabilization is highlighted. The paper concludes with future research directions and the necessary steps for experimental validation of the approach.
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