State Constrained Model Reference Adaptive Control with Input Amplitude and Rate Limits

TL;DR

This paper introduces a novel, optimization-free MRAC method that enforces user-defined constraints on plant states, input amplitude, and rate in uncertain MIMO LTI systems using barrier Lyapunov functions, ensuring safety despite disturbances.

Contribution

The paper presents the first optimization-free adaptive control approach with verifiable feasibility conditions for constrained MIMO LTI systems under uncertainties.

Findings

Effective constraint enforcement demonstrated in simulations

Ensures safety despite bounded disturbances

Provides verifiable conditions for control feasibility

Abstract

This paper proposes a robust model reference adaptive controller (MRAC) for uncertain multi-input multi-output (MIMO) linear time-invariant (LTI) plants with user-defined constraints on the plant states, input amplitude, and input rate. The proposed two-layer barrier Lyapunov function (BLF)-based control design considers the input and the input rate as states that are constrained using two BLFs in the first layer, while another BLF in the second layer constrains the plant states. The adaptive control law ensures that the plant states, input amplitude, and input rate remain within the user-defined safe sets despite unmatched bounded disturbances. Sufficient conditions for the existence of a feasible control policy are also provided. To the best of the authors' knowledge, this is the first optimization-free method that imposes user-defined constraints on the state, input, and input rate and also provides verifiable feasibility conditions in the presence of parametric uncertainties and disturbances. Simulation results demonstrate the effectiveness of the proposed algorithm.