State-Constrained Control of Discrete-Time Nonlinear Systems via Constraint Lifting

TL;DR

This paper introduces a control framework for discrete nonlinear systems that enforces state constraints by transforming the problem into an unconstrained one using smooth constraint-lifting, ensuring stability and safety.

Contribution

It proposes a novel constraint-lifting approach with recursive backstepping for nonlinear systems, guaranteeing stability and forward invariance of safe sets.

Findings

Successfully enforces state constraints in simulations

Guarantees asymptotic stability of the controlled system

Ensures forward invariance of the safe set during operation

Abstract

This paper presents a constraint-enforcing control framework for a class of discrete-time strict-feedback nonlinear systems. The objective is to guarantee closed-loop stability while ensuring forward invariance of a prescribed safe set defined by state constraints. The proposed approach transforms the constrained control problem into an equivalent unconstrained one through smooth constraint-lifting mappings constructed using strictly increasing sigmoid functions. Controller synthesis is then performed in the lifted coordinates, enabling recursive backstepping design while preserving the admissibility of the constrained states. Conditions on the controller gains are derived to guarantee both asymptotic stability of the closed-loop system and forward invariance of the admissible domain of the lifting functions. The analysis also establishes a conditional deadbeat property for the second backstepping step once the system trajectory enters a region in which the lifting-domain admissibility conditions are satisfied. Numerical simulations of a constrained double-integrator system demonstrate the effectiveness of the proposed method in enforcing state constraints while tracking a reference command.