Sentence examples for learning controller from inspiring English sources

The control scheme is composed of a robust control term and an iterative learning controller The robust controller is designed based on the Lyapunov theorem to overcome the degrading effect of the disturbances and uncertainties exist in the system model.

The major advantage of the proposed design method is realizing an integrated optimization for the parameters of existing feedback controller and design of a simple iterative learning controller, and then ensuring the optimal control performance of the whole system in sense of 2D-GPC.

Iterative Learning Controller (ILC) built on top of conventional controls helps the plant to effectively track its reference signals under repetitive conditions.

The chapter presents a learning controller that has been designed for the control of mobile microrobots, which belong to the class of nonlinear, time-variant systems with ambiguous inverse behavior.

In this paper, a model reference adaptive control strategy is used to design an iterative learning controller for a class of repeatable nonlinear systems with uncertain parameters, high relative degree, initial output resetting error, input disturbance and output noise.

This paper presents a design of robust iterative learning controller.

This is prompted by the fact that many organic pollutants in industrial wastewaters are resistant to conventional biological treatments, and the fact that advanced oxidation processes, controlled with learning controllers measuring the oxidation reduction potential (ORP), give a cost-effective solution.

The event-triggered scheme is firstly considered in the iterative learning controllers to reduce the number of iteration steps to be updated.

The new algorithm generalizes existing learning controllers since, in the case of periodic references and/or disturbances, the knowledge of the period is not required.

Sufficient and necessary condition to ensure robust BlBO (bounded-input boundedoutput) stability is derived for the optimal iterative learning controllers when tracking arbitrary bounded output.

It is shown that among these possibilities, only a non-standard case of pole placement and noise filtering will naturally result in iterative learning controllers with orders higher than one.