In this paper, we present an overview of adaptive control by contrasting model‐based
approaches with data‐driven approaches. Indeed, we propose to classify adaptive …

The nonuniform trial length problem, which causes information dropout in learning, is very
common in various control systems such as robotics and motion control systems. This paper …

In most implementations of iterative learning control (ILC) for trajectory tracking, it is usually
required that the trial lengths of different iterations are uniform. However, this requirement …

The magnetic shape memory alloy based actuator (MSMA-BA) is an indispensable
component mechanism for high-precision positioning systems as it possesses the …

This paper conducts a survey on iterative learning control (ILC) with incomplete information
and associated control system design, which is a frontier of the ILC field. The incomplete …

The typical characteristic of a magnetic shape memory alloy (MSMA)-based actuator is rate-
dependent and stress-dependent hysteresis. In addition, the hysteresis in an MSMA-based …

Iterative learning control (ILC) has been well recognized for its output tracking ability in
systems that perform repetitive tasks, such as robot manipulators. In practice, however, the …

This paper proposes adaptive iterative learning control (ILC) schemes for continuous-time
parametric nonlinear systems with iteration lengths that randomly vary. As opposed to the …

This work reports on a novel approach to effective design of iterative learning control of
repetitive nonlinear processes based on artificial neural networks. The essential idea …

In this article, a noisy-output-based direct learning tracking control is proposed for stochastic
linear systems with nonuniform trial lengths. The iteration-varying trial length is modeled …