Control of Constrained Dynamical Systems with Performance Guarantees: With Application to Vehicle motion Control
Doctoral thesis, 2021
A fundamental tool in constrained control application is the robust control invariant sets (RCI). For a controlled dynamical system, if initial states belong to RCI set, control inputs always exist that keep the future state trajectories restricted within the set. Hence, RCI sets can characterize a system that never violates constraints. These sets are the primary ingredient in the synthesis of the well-known constraint control strategies like model predictive control (MPC) and interpolation-based controller (IBC). Consequently, a large body of research has been devoted to the computation of these sets. In the thesis, we will focus on the computation of RCI sets and the method to generate control inputs that keep the system trajectories within RCI set. We specifically focus on the systems which have time-varying dynamics and polytopic constraints. Depending upon the nature of the time-varying element in the system description (i.e., if they are observable or not), we propose different sets of algorithms.
The first group of algorithms apply to the system with time-varying, bounded uncertainties. To systematically handle the uncertainties and reduce conservatism, we exploit various tools from the robust control literature to derive novel conditions for invariance. The obtained conditions are then combined with a newly developed method for volume maximization and minimization in a convex optimization problem to compute desirably large and small RCI sets. In addition to ensuring invariance, it is also possible to guarantee desired closed-loop performance within the RCI set. Furthermore, developed algorithms can generate RCI sets with a predefined number of hyper-planes. This feature allows us to adjust the computational complexity of MPC and IBC controller when the sets are utilized in controller synthesis. Using numerical examples, we show that the proposed algorithms can outperform (volume-wise) many state-of-the-art methods when computing RCI sets.
In the other case, we assume the time-varying parameters in system description to be observable. The developed algorithm has many similar characteristics as the earlier case, but now to utilize the parameter information, the control law and the RCI set are allowed to be parameter-dependent. We have numerically shown that the presented algorithm can generate invariant sets which are larger than the maximal RCI sets computed without exploiting parameter information.
Lastly, we demonstrate how we can utilize some of these algorithms to construct a computationally efficient IBC controller for the vehicle motion control. The devised IBC controller guarantees to meet safety requirements mentioned in ISO 26262 and the ride comfort requirement by design.
Linear fractional transformation
Linear parameter varying system
Linear matrix inequalities
Chalmers, Electrical Engineering, Systems and control, Mechatronics
Computation of Robust Control Invariant Sets with Predefined Complexity for Uncertain Systems
International Journal of Robust and Nonlinear Control,; Vol. 31(2021)p. 1674-1688
Full-complexity characterization of control-invariant domains for systems with uncertain parameter dependence
IEEE Control Systems Letters,; Vol. 3(2019)p. 19-24
Computation of low-complexity control-invariant sets for systems with uncertain parameter dependence
Automatica,; Vol. 101(2019)p. 330-337
Restricted-Complexity Characterization of Control-Invariant Domains with Application to Lateral Vehicle Dynamics Control
IEEE Conference on Decision and Control,; (2018)p. 4946-4951
Paper in proceedings
A. Gupta, M. Mejari, P. Falcone, D. Piga, Computation of Parameter Dependent Invariant Sets for LPV Systems with Guaranteed Performance
The main objective of the thesis is to propose control methods, with performance guarantees, for constrained uncertain system. To meet the objectives, we present algorithms that compute a stabilizing controller, along with a set of states where the system is guaranteed to satisfy constraints. In the control theory, these sets are well-known as invariant sets and widely used in safety-critical applications to enforce the controllers' safety.
Further, we demonstrate how we can utilize these algorithms to construct a controller for vehicle motion control application. This is a relevant application to show the thesis contribution. Because for high-level autonomous vehicles, the controller has to guarantee the satisfaction of recently introduced Automotive Safety Integrity Level (ASIL) requirements mentioned in ISO 26262. For such an application, we propose a constrained control strategy which ensures safety by design.
Areas of Advance
Electrical Engineering, Electronic Engineering, Information Engineering
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4904
Chalmers University of Technology
Opponent: Prof. Mircea Lazar, Eindhoven University of Technology, The Netherlands