As it is well-known, system uncertainties and unmodeled dynamics can deteriorate stability properties of model reference adaptive control systems. Motivated by this standpoint, we first analyse stability conditions of model reference adaptive control architectures in the presence of unstructured system uncertainties and unmodeled dynamics. We then synthesise adaptive robustifying terms to relax the aforementioned stability condition, which presents our main contribution. Specifically, these terms in the feedback loop guarantee overall system stability even in the presence of significant system uncertainties when unmodeled dynamics satisfy a condition. We further demonstrate our theoretical findings in an experiment involving an inverted pendulum on a cart (modeled dynamics) coupled with another cart through a spring (unmodeled dynamics).

众所周知，系统不确定性和未建模动力学会降低模型参考自适应控制系统的稳定性。受此观点的启发，我们首先分析了模型参考自适应控制架构在存在非结构化系统不确定性和未建模动力学的情况下的稳定性条件。然后，我们综合自适应鲁棒化项来放松上述稳定性条件，这是我们的主要贡献。具体来说，反馈回路中的这些项保证了整个系统的稳定性，即使在存在显着系统不确定性的情况下，当未建模的动力学满足某个条件时也是如此。我们在一项实验中进一步证明了我们的理论发现，该实验涉及推车上的倒立摆（建模动力学）与另一个推车通过弹簧（未建模动力学）耦合。