Khái niệm cốt lõi
A robust control technique that combines Control Lyapunov Function and Hamilton-Jacobi Reachability to compute a controller and its Region of Attraction for nonlinear systems with bounded model uncertainty.
Tóm tắt
The paper presents a robust control approach that combines Control Lyapunov Function (CLF) and Hamilton-Jacobi (HJ) Reachability Analysis to handle model uncertainty in nonlinear systems.
Key highlights:
- The CLF method uses a linear system model with assumed additive uncertainty to calculate a control gain and the level sets of the Region of Attraction (ROA) as a function of the uncertainty.
- The HJ Reachability Analysis uses the nonlinear model with the modeled uncertainty, which need not be additive, to compute the Backward Reachable Set (BRS).
- By juxtaposing the level sets of the ROA with the BRS, the approach can calculate the worst-case additive disturbance and the ROA of the nonlinear model.
- The technique is demonstrated on a 2D quadcopter tracking a trajectory and a 2D quadruped with height and velocity regulation in the presence of model uncertainty.
The proposed robust control approach provides safety guarantees by leveraging the strengths of both CLF and HJ methods. It can handle nonlinear dynamics and non-additive uncertainties, outperforming a nominal Model Predictive Control (MPC) in the presence of disturbances.
Thống kê
The mass of the 2D quadcopter is 1 kg, the length is 0.2 m, and the moment of inertia is 0.1 kg·m^2.
The mass of the 2D quadruped is 12.454 kg, and the moment of inertia is 0.0565 kg·m^2.
The maximum additive disturbance for the quadcopter is bounded by 3.5.
The unknown mass disturbance for the quadruped is 5 kg.
Trích dẫn
"The technique is demonstrated on a 2D quadcopter tracking a trajectory and a 2D quadruped with height and velocity regulation in the presence of model uncertainty."
"By juxtaposing the level sets of the ROA with the BRS, the approach can calculate the worst-case additive disturbance and the ROA of the nonlinear model."