TR2021-145

On the Stability Properties of Perception-aware Chance-constrained MPC in Uncertain Environments


    •  Bonzanini, A.D., Mesbah, A., Di Cairano, S., "On the Stability Properties of Perception-aware Chance-constrained MPC in Uncertain Environments", IEEE Conference on Decision and Control (CDC), December 2021.
      BibTeX TR2021-145 PDF
      • @inproceedings{Bonzanini2021dec,
      • author = {Bonzanini, Angelo Domenico and Mesbah, Ali and Di Cairano, Stefano},
      • title = {On the Stability Properties of Perception-aware Chance-constrained MPC in Uncertain Environments},
      • booktitle = {IEEE Conference on Decision and Control (CDC)},
      • year = 2021,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2021-145}
      • }
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  • Research Areas:

    Control, Dynamical Systems

Abstract:

Perception systems for acquiring environment information and control systems for commanding a system operating in the environment are usually separately designed, but their performance is often interdependent: control decisions affect perception, e.g., the distance from an object affects its sensing, and perception affects control decisions, e.g., ar- eas may be traversed or avoided based on the amount of available information. Perception-aware control accounts for such an interdependence to optimize the overall performance. We recently proposed a perception-aware chance constrained MPC (PAC-MPC) that considers the impact of control on the evolution of the environment uncertainty, then used within chance constraints. In this paper we obtain a stabilizing design the PAC-MPC, by first determining stability conditions in a general nonlinear setting, and then deriving specify design rules for the linear-Gaussian case, which results in a specific choice of the cost function parameters and in design conditions for the estimation algorithms that determine uncertainty propagation. The results are illustrated by means of a numerical example.