The scientific community has recently seen a fast-growing number of publications tackling the topic of fractional-order controllers in general, with a focus on the fractional order PID. Several versions of this controller have been proposed, including different tuning methods and implementation possibilities. Quite a few recent papers discuss the practical use of such controllers. However, the industrial acceptance of these controllers is still far from being reached. Autotuning methods for such fractional order PIDs could possibly make them more appealing to industrial applications, as well. In this paper, the current autotuning methods for fractional order PIDs are reviewed. The focus is on the most recent findings. A comparison between several autotuning approaches is considered for various types of processes. Numerical examples are given to highlight the practicality of the methods that could be extended to simple industrial processes.
Induction motors are widely used in industry and are essential to industrial processes. The faults in motors lead to high repair costs and cause financial losses resulting from unexpected downtime. Early detection of faults in induction motors has become necessary and critical in reducing costs. Most motor faults are caused by bearing failure. Machine learning-based diagnostic methods are proposed in this study. These methods use effective features. First, load currents of healthy and faulty motors are measured while the rotating speed is changing continuously. Second, experiments revealed the relationship between the magnitude of the amplitude of specific signals and the rotating speed, and the rotating speed is treated as a new feature. Third, machine learning-based diagnoses are conducted. Finally, the effectiveness of machine learning-based diagnostic methods is verified using experimental data.
Sustainability and circularity are currently two relevant drivers in the development and optimisation of industrial processes. This study assessed the use of electrodialysis (ED) to purify synthetic erythritol culture broth and for the recovery of the salts in solution, for minimising the generation of waste by representing an efficient alternative to remove ions, ensuring their recovery process contributing to reaching cleaner standards in erythritol production. Removal and recovery of ions was evaluated for synthetic erythritol culture broth at three different levels of complexity using a stepwise voltage in the experimental settings. ED was demonstrated to be a potential technology removing between 91.7–99.0% of ions from the synthetic culture broth, with 49–54% current efficiency. Besides this, further recovery of ions into the concentrated fraction was accomplished. The anions and cations were recovered in a second fraction reaching concentration factors between 1.5 to 2.5 times while observing low level of erythritol losses (<2%), with an energy consumption of 4.10 kWh/m3.
Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes. The solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict. The number of applications of multi- objective optimization in industrial processes is ample and each application has its own challenges. In the present literature review, a broad panorama of the applications in multi-objective optimization is presented, including future perspectives and open questions that still need to be addressed.
The important developments in membrane techniques used in the dairy industrial processes to whey manufacturing are discussed. Particular emphasis is placed on the description of membrane processes, characterization of protein products, biological issues related to bacteriophages contamination, and modeling of the processes. This choice was dictated by the observed research works and consumer trends, who increasingly appreciate healthy food and its taste qualities.
The periderm acts as armor protecting the plant's inner tissues from biotic and abiotic stress. It forms during the radial thickening of plant organs such as stems and roots and replaces the function of primary protective tissues such as the epidermis and the endodermis. A wound periderm also forms to heal and protect injured tissues. The periderm comprises a meristematic tissue called the phellogen, or cork cambium, and its derivatives: the lignosuberized phellem and the phelloderm. Research on the periderm has mainly focused on the chemical composition of the phellem due to its relevance as a raw material for industrial processes. Today, there is increasing interest in the regulatory network underlying periderm development as a novel breeding trait to improve plant resilience and to sequester CO2. Here, we discuss our current understanding of periderm formation, focusing on aspects of periderm evolution, mechanisms of periderm ontogenesis, regulatory networks underlying phellogen initiation and cork differentiation, and future challenges of periderm research. Expected final online publication date for the Annual Review of Plant Biology, Volume 73 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.