Fractional calculus is an efficient tool, which has the potential to improve the performance of
gradient methods. However, when the first order gradient direction is generalized by …

A reinforcement learning-based boundary optimal control algorithm for parabolic distributed
parameter systems is developed in this article. First, a spatial Riccati-like equation and an …

This paper presents a novel iterative learning feedback control method for linear parabolic
distributed parameter systems with multiple collocated piecewise observation. Multiple …

In this paper, a new online adaptive optimal controller design scheme is studied for a class
of nonlinear systems with input time-delays. First, we linearize the original nonlinear systems …

This paper focuses on the convergence problem of the emerging fractional order gradient
descent method, and proposes three solutions to overcome the problem. In fact, the general …

This study accentuates the intricacies of designing a quantized observer-oriented model
reference tracking controller for parabolic non-linear uncertain partial differential equation …

Computer-aided diagnosis tools have experienced rapid growth and development in recent
years. Among all, deep learning is the most sophisticated and popular tool. In this paper …

Motivated by the increase in practical applications of fractional calculus, we study the
classical gradient method under the perspective of the ψ-Hilfer derivative. This allows us to …

In this paper, we consider a magnetic control problem arising in a one-dimensional (1-D)
MHD flow system governed by a set of coupled partial differential equations (PDEs) with …

There are physical phenomena, involving diffusion and structural vibrations, modeled by
partial differential equations (PDEs) whose solution reflects their spatial distribution …