In this paper, an extended state observer-based data-driven iterative learning control
[extended state observer (ESO)-based DDILC] is developed for a permanent magnet linear …

This article reconsiders the data quantization problem in iterative learning control (ILC) for
nonlinear nonaffine systems from four aspects: 1) use of available additional control …

This paper studies the output tracking control problems for multiple-input, multiple-output
(MIMO) locally Lipschitz nonlinear (LLNL) systems subject to iterative operation and …

This paper proposes a neural network (NN)-based control scheme in an Adaptive Actor-
Critic (AAC) learning framework designed for output reference model tracking, as a …

In this article, a radial basis function neural network-based adaptive iterative learning fault-
tolerant control (RBFNN-AILFTC) algorithm is developed for subway trains subject to the …

Batch processes repeatedly execute a given set of tasks over a finite duration, whose
versatility and ability to adapt to rapidly changing markets make it prevalent in a multitude of …

This paper explores the formation control problem of repetitive nonlinear homogeneous and
asynchronous multiagent networks, where the early starting agent is designated as the …

In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and
Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for …

In this article, the optimal consensus problem at specified data points is considered for
heterogeneous networked agents with iteration-switching topologies. A point-to-point linear …

For a class of unknown MIMO non-affine nonlinear repetitive discrete-time systems, a novel
data-driven high-order point-to-point iterative learning control scheme is proposed. The …