The problem of trajectory tracking for quadrotor unmanned aerial vehicles(UAVs)is investigated in this paper.An iterative linear quadratic regulator(iLQR)based model predictive control(MPC)strategy is proposed.The pro...The problem of trajectory tracking for quadrotor unmanned aerial vehicles(UAVs)is investigated in this paper.An iterative linear quadratic regulator(iLQR)based model predictive control(MPC)strategy is proposed.The proposed iLQRMPC strategy solves the nonlinear optimal control problem using the iLQR algorithm and implements the control in a receding horizon manner.A constrained iLQR algorithm is designed in the framework of the augmented Lagrangian method to solve the optimization problem induced by the trajectory tracking.Finally,a comparative simulation experiment is conducted to demonstrate the effectiveness and advantage of the proposed control strategy.展开更多
We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajecto...We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajectory generation algorithm,and trajectory tracking controller design.A lattice planner,which searches over a 3D(x,y,θ) configuration space,is adopted to generate the global trajectory.The ILQR method is used to design a local trajectory tracking controller.The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot.The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator(LQR) method.According to the experiments,the new controller improves the control sequences(v,ω) iteratively and produces slightly better results.Specifically,two trajectories,'S' and '8' courses,are followed with sufficient accuracy using the proposed controller.展开更多
文摘The problem of trajectory tracking for quadrotor unmanned aerial vehicles(UAVs)is investigated in this paper.An iterative linear quadratic regulator(iLQR)based model predictive control(MPC)strategy is proposed.The proposed iLQRMPC strategy solves the nonlinear optimal control problem using the iLQR algorithm and implements the control in a receding horizon manner.A constrained iLQR algorithm is designed in the framework of the augmented Lagrangian method to solve the optimization problem induced by the trajectory tracking.Finally,a comparative simulation experiment is conducted to demonstrate the effectiveness and advantage of the proposed control strategy.
基金Project (Nos. 90920304 and 91120015) supported by the National Natural Science Foundation of China
文摘We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajectory generation algorithm,and trajectory tracking controller design.A lattice planner,which searches over a 3D(x,y,θ) configuration space,is adopted to generate the global trajectory.The ILQR method is used to design a local trajectory tracking controller.The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot.The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator(LQR) method.According to the experiments,the new controller improves the control sequences(v,ω) iteratively and produces slightly better results.Specifically,two trajectories,'S' and '8' courses,are followed with sufficient accuracy using the proposed controller.
