Abstract Machine learning (ML) has recently gained in popularity, spurred by well-publicized
advances like deep learning and widespread commercial interest in big data analytics …

Model predictive control (MPC) has become one of the well-established modern control
methods for three-phase inverters with an output LC filter, where a high-quality voltage with …

Active control of sound and vibration is a relatively new and fast growing field of research
and application. The numbers of papers published on the subject have been more than …

This book explores how developing solutions with heuristic tools offers two major
advantages: shortened development time and more robust systems. It begins with an …

In the past decade, the control of nonlinear systems has received considerable attention in
both academia and industry. The recent interest in the design and analysis of nonlinear …

Artificial intelligence (AI) is an emerging technology that has great potential in reducing
energy consumption, environmental burdens, and operational risks of chemical production …

As a result of good modeling capabilities, neural networks have been used extensively for a
number of chemical engineering applications such as sensor data analysis, fault detection …

A nonlinear internal model control (NIMC) strategy based on neural network models is
proposed for SISO processes. The neural network model is identified from input—output …

A type of recurrent neuro-fuzzy network is proposed in this paper to build long-term
prediction models for nonlinear processes. The process operation is partitioned into several …

A presentation of techniques in advanced process modelling, identification, prediction, and
parameter estimation for the implementation and analysis of industrial systems. The authors …