A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Automatica (Journal of IFAC)
Brief paper: Singular perturbation analysis of a receding horizon controller
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief Feasibility and stability of constrained finite receding horizon control
Automatica (Journal of IFAC)
A stabilizing model-based predictive control algorithm for nonlinear systems
Automatica (Journal of IFAC)
Terrain Avoidance Nonlinear Model Predictive Control for Autonomous Rotorcraft
Journal of Intelligent and Robotic Systems
| Hi-index | 22.15 |
Receding horizon feedback control (RHFC) was originally introduced as an easy method for designing stable state-feedback controllers for linear systems. Here those results are generalized to the control of nonlinear autonomous systems, and we develop a performance index which is minimized by the RHFC (inverse optimal control problem). Previous results for linear systems have shown that desirable nonlinear controllers can be developed by making the RHFC horizon distance a function of the state. That functional dependence was implicit and difficult to implement on-line. Here we develop similar controllers for which the horizon distance is an easily computed explicit function of the state.