A new explicit dynamic path tracking controller using generalized predictive control

Krid, Mohamed; Benamar, Faiz; Lenain, Roland

doi:10.1007/s12555-015-0160-6

Cited by 22 publications

(12 citation statements)

References 20 publications

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“…Besides improving the motion planner, a further step was to include a control law to minimize the deviation between planned and executed trajectories. We modified an MPC introduced in [12] so it could take advantage of our particular motion planner.…”

Section: Improvements For Dealing With Dynamicsmentioning

confidence: 99%

“…The authors of [12] propose a Non-linear Continuoustime Generalized Predictive Control (NCGPC) meant for outdoor mobile robots. Following their approach, we derive a different control law that takes advantage of our receding horizon planner.…”

Section: Planner (Drhmp)mentioning

confidence: 99%

“…To apply the same approach as in [12] we need an extended model for the unicycle mobile robot that integrates the kinematic and dynamic models. Furthermore, we need to be able to write the model in a non-linear control-affine form as shown bellow in eq.…”

Section: ) Extended Unicycle Modelmentioning

confidence: 99%

See 2 more Smart Citations

Real-time distributed receding horizon motion planning and control for mobile multi-robot dynamic systems

Filho

Lucet

Filliat³

2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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This paper proposes an improvement of a motion planning approach and a modified model predictive control (MPC) for solving the navigation problem of a team of dynamical wheeled mobile robots in the presence of obstacles in a realistic environment. Planning is performed by a distributed receding horizon algorithm where constrained optimization problems are numerically solved for each prediction timehorizon. This approach allows distributed motion planning for a multi-robot system with asynchronous communication while avoiding collisions and minimizing the travel time of each robot. However, the robots dynamics prevents the planned motion to be applied directly to the robots. Using unicycle-like vehicles in a dynamic simulation, we show that deviations from the planned motion caused by the robots dynamics can be overcome by modifying the optimization problem underlying the planning algorithm and by adding an MPC for trajectory tracking. Results also indicate that this approach can be used in systems subjected to real-time constraint.

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Section: Improvements For Dealing With Dynamicsmentioning

confidence: 99%

Section: Planner (Drhmp)mentioning

confidence: 99%

See 1 more Smart Citation

Real-time distributed receding horizon motion planning and control for mobile multi-robot dynamic systems

Filho

Lucet

Filliat³

2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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“…Where e q (t + t h ) is a predicted error, q(t + t h ) is a t h -step ahead prediction of the output and t h > 0 is a prediction horizon. The Taylor series expansion is derived by Lie derivatives [11] for extracting a prediction model for robotic underwater manipulator as follows:…”

Section: (18)mentioning

confidence: 99%

Robust Model Predictive Control for Autonomous Underwater Vehicle – Manipulator System with Fuzzy Compensator

Esfahani

2019

Polish Maritime Research

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This paper proposes an improved Model Predictive Control (MPC) approach including a fuzzy compensator in order to track desired trajectories of autonomous Underwater Vehicle Manipulator Systems (UVMS). The tracking performance can be affected by robot dynamical model uncertainties and applied external disturbances. Nevertheless, the MPC as a known proficient nonlinear control approach should be improved by the uncertainty estimator and disturbance compensator particularly in high nonlinear circumstances such as underwater environment in which operation of the UVMS is extremely impressed by added nonlinear terms to its model. In this research, a new methodology is proposed to promote robustness virtue of MPC that is done by designing a fuzzy compensator based on the uncertainty and disturbance estimation in order to reduce or even omit undesired effects of these perturbations. The proposed control design is compared with conventional MPC control approach to confirm the superiority of the proposed approach in terms of robustness against uncertainties, guaranteed stability and precision.

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“…Krid et al [8] presented a path tracking controller for a fast rover with independent front and rear steering. The controller was based on the dynamic model of a bicycle like vehicle which considered the lateral slippage of the wheels.…”

Section: Introductionmentioning

confidence: 99%

Path tracking with minimum time of vehicle handling inverse dynamics based on adaptive gauss pseudospectral method

Liu¹,

Liu²

2019

J. meas. eng.

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Vehicle driving safety is the urgent key problem to be solved by an independent automobile development project. And it is also the premise and one of the necessary conditions for active vehicle safety. A new technique for path tracking with minimum time of vehicle handling inverse dynamics is proposed in this paper. Based on a new optimal control method-Adaptive Gauss Pseudospectral Method (AGPM), the optimal control for path tracking with minimum time problem was converted into a nonlinear programming problem which met the boundary condition and a series of path constraints including path constraint, state constraint, control constraint. And then the problem was solved using the sequential quadratic programming (SQP). The simulation results showed that the proposed method was not sensitive to the initial value and the optimization efficiency was higher compared with indirect methods and traditional direct methods. When solving the problem of path tracking with minimum time as per this method, boundary constraints and path constraints were well satisfied. The algorithm was not only precise but it could also shorten the evaluation period of vehicle handling stability and could reduce the tremendous cost for real vehicle testing. So the maneuverability of two different vehicles that complete the pylon course slalom test road with minimum time can be evaluated objectively by utilizing the method. The model correctness is verified through a real vehicle test.

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A new explicit dynamic path tracking controller using generalized predictive control

Cited by 22 publications

References 20 publications

Real-time distributed receding horizon motion planning and control for mobile multi-robot dynamic systems

Real-time distributed receding horizon motion planning and control for mobile multi-robot dynamic systems

Robust Model Predictive Control for Autonomous Underwater Vehicle – Manipulator System with Fuzzy Compensator

Path tracking with minimum time of vehicle handling inverse dynamics based on adaptive gauss pseudospectral method

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