In practical applications of iterative learning control (ILC), the repetitive process may end up
early by accident during the performance improvement along the trial axis, which yields the …

Metaheuristic optimization algorithms (MHA) play a significant role in obtaining the best
(optimal) values of the system's parameters to improve its performance. This role is …

In many engineering problems, the systems dynamics are uncertain, and then, the accurate
dynamic modeling is required. Type-2 fuzzy neural networks (T2F-NNs) are extensively …

This paper presents a novel application of the metaheuristic Slime Mould Algorithm (SMA) to
the optimal tuning of interval type-2 fuzzy controllers. Inserting the information feedback …

Abstract The Combined Heat and Power Economic Dispatch (CHPED) is a real-world
optimization problem with several complex constraints that has been a topic of studies …

Abstract Whale Optimization Algorithm (WOA) is a key tool for solving complex engineering
optimization problems, aiming at adjusting important parameters to satisfy constraints and …

This book categorizes the wide area of data-driven model-free controllers, reveals the exact
benefits of such controllers, gives the in-depth theory and mathematical proofs behind them …

In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients.
Unlike most studies, the glucose–insulin metabolism is considered to be uncertain. A new …

Accurate prediction of blood glucose (BG) is conducive to avoiding abnormal blood glucose
events and improving blood glucose management for Type 1 diabetes (T1D) patients …

The main objective of this study is to present a novel dynamic fractional-order deep learned
type-2 fuzzy logic system (FDT2-FLS) with improved estimation capability. The proposed …