IFAC-PapersOnLine · 2019 · 81 citations · 13 references
EngineeringAutomotive EngineeringAutonomous SystemsAutonomous VehiclesOptimizationVehicle DynamicsCascade ControlControl SystemsControl TheoryDynamic ControlModel Predictive ControlVehicle ControlDynamic ModelsLinear Model Predictive ControlLinear Quadratic RegulationLinear Quadratic RegulatorLinear-quadratic ControlPosition ControlReal-time OperationTrajectory Tracking Control
In this work, a novel approach is presented to solve the trajectory tracking problem for autonomous vehicles. This method is based on the use of a cascade control where the external loop solves the position control using a novel Linear Parameter Varying - Model Predictive Control (LPV-MPC) approach and the internal loop is in charge of the dynamic control of the vehicle using a LPV - Linear Quadratic Regulator technique designed via Linear Matrix Inequalities (LPV-LMI-LQR). Both techniques use an LPV representation of the kinematic and dynamic models of the vehicle. The main contribution of the LPV-MPC technique is its ability to calculate solutions very close to those obtained by the non-linear version but reducing significantly the computational cost and allowing the real-time operation. To demonstrate the potential of the LPV-MPC, we propose a comparison between the non-linear MPC formulation (NL-MPC) and the LPV-MPC approach.
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YALMIP : a toolbox for modeling and optimization in MATLAB
Johan Löfberg · 2005 · 9.2K citations
Model predictive control: Recent developments and future promise
D.Q. Mayne · Automatica · 2014 · 1.9K citations
Engineering, Manufacturing Engineering, Dynamical Systems +15