The 1st International Conference on Computational Engineering and Intelligent Systems

Computational engineering, artificial intelligence and smart systems constitute a hot multidisciplinary topic contrasting computer science, engineering and applied mathematics that created a variety of fascinating intelligent systems. Computational engineering encloses fundamental engineering and science blended with the advanced knowledge of mathematics, algorithms and computer languages. It is concerned with the modeling and simulation of complex systems and data processing methods. Computing and artificial intelligence lead to smart systems that are advanced machines designed to fulfill certain specifications. This proceedings book is a collection of papers presented at the first International Conference on Computational Engineering and Intelligent Systems (ICCEIS2021), held online in the period December 10-12, 2021. The collection offers a wide scope of engineering topics, including smart grids, intelligent control, artificial intelligence, optimization, microelectronics and telecommunication systems. The contributions included in this book are of high quality, present details concerning the topics in a succinct way, and can be used as excellent reference and support for readers regarding the field of computational engineering, artificial intelligence and smart system

A Hybrid Controller for Stability Robustness, Performance Robustness, and Disturbance Attenuation of a Maglev System

Devices using magnetic levitation (maglev) offer the potential for friction-free, high-speed, and high-precision operation. Applications include frictionless bearings, high-speed ground transportation systems, wafer distribution systems, high-precision positioning stages, and vibration isolation tables. Maglev systems rely on feedback controllers to maintain stable levitation. Designing such feedback controllers is challenging since mathematically the electromagnetic force is nonlinear and there is no local minimum point on the levitating force function. As a result, maglev systems are open-loop unstable. Additionally, maglev systems experience disturbances and system parameter variations (uncertainties) during operation. A successful controller design for maglev system guarantees stability during levitating despite system nonlinearity, and desirable system performance despite disturbances and system uncertainties. This research investigates five controllers that can achieve stable levitation: PD, PID, lead, model reference control, and LQR/LQG. It proposes an acceleration feedback controller (AFC) design that attenuates disturbance on a maglev system with a PD controller. This research proposes three robust controllers, QFT, Hinf , and QFT/Hinf , followed by a novel AFC-enhanced QFT/Hinf (AQH) controller. The AQH controller allows system robustness and disturbance attenuation to be achieved in one controller design. The controller designs are validated through simulations and experiments. In this research, the disturbances are represented by force disturbances on the levitated object, and the system uncertainties are represented by parameter variations. The experiments are conducted on a 1 DOF maglev testbed, with system performance including stability, disturbance rejection, and robustness being evaluated. Experiments show that the tested controllers can maintain stable levitation. Disturbance attenuation is achieved with the AFC. The robust controllers, QFT, Hinf , QFT/ Hinf, and AQH successfully guarantee system robustness. In addition, AQH controller provides the maglev system with a disturbance attenuation feature. The contributions of this research are the design and implementation of the acceleration feedback controller, the QFT/ Hinf , and the AQH controller. Disturbance attenuation and system robustness are achieved with these controllers. The controllers developed in this research are applicable to similar maglev systems

Computational modeling of the brain limbic system and its application in control engineering

This study mainly deals with the various aspects of modeling the learning processes within the brain limbic system and studying the various aspects of using it for different applications in control engineering. The current study is a multi-aspect research effort which not only requires a background of control engineering, but also a basic knowledge of some biomorphic systems. The main focus of this study is on biological systems which are involved in emotional processes. In mammalians, a part of the brain called the limbic system is mainly responsible for emotional processes. Therefore, general brain emotional processes and specific aspects of the limbic system are reviewed in the early parts of this study. Next, we describe developing a computational model of the limbic system based on these concepts. Since the focus of this study is on the application of the model in engineering systems and not on the biological concepts, the model established is not a very complicated model and does not include all the components of the limbic system. In fact, we are trying to develop a model which captures the minimal and basic properties of the limbic system which are mainly known as the Amygdala-Orbitofrontal Cortex system. The main chapter of this thesis, Chapter IV, shows the utilization of the Brain Emotional Learning (BEL) model in different applications of control and signal fusion systems. The main effort is focused on applying the model to control systems where the model acts as the controller block. Furthermore, the application of the model in signal fusion is also considered where simulation results support the applicability of the model. Finally, we studied different analytical aspects of the model including the behavior of the system during the adaptation phase and the stability of the system. For the first issue, we simplify the model, e.g. remove the nonlinearities, to develop mathematical formulations for behavior of the system. To study the stability of the system, we use the cell-to-cell mapping algorithm which reveals the stability conditions of the system in different representations. This thesis finishes with some concluding remarks and some topics for future research on this field

Frequency deviations stabilizations in restructured power systems using coordinative controllers

Modern restructured power system faces excessive frequency aberrations due to the intermittent renewable generations and persistently changing load demands. An efficient and robust control strategy is obligatory to minimise deviations in the system frequency and tie-line to avoid any possible blackout. Hence, in this research, to achieve this target, automatic generation control (AGC) is utilized as a secondary controller to alleviate the changes in interconnected restructured systems at uncertainties. The objective of AGC is to quickly stabilize the deviations in frequency and tie-line power following load fluctuations. This thesis addresses the performance of AGC in two-area restructured power systems with many sophisticated control strategies in the presence of renewable and traditional power plants. As per literature of research work, there are quite a few research studies on AGC of a restructured system using optimized coordinative controllers. Besides, investigations on advanced optimized-based coordinative controller approaches are also rare to find in the literature. So, various combinations of two degrees of freedom (2DOF) controllers are utilized as supplementary controllers to diminish the frequency deviations. Nevertheless, the interconnected tie-lines are typically congested in areas with huge penetration of renewable sources, which may reduce the tie -line capability. Therefore, distinct FACTS controllers and ultra-capacitor (UC) are integrated into two-area restructured systems for strengthening the tie-line power and frequency. Further, new optimization techniques such as cuckoo search (CS), bat algorithm (BA), moth-flame optimization (MFO) are utilized in this work for investigating the suggested 2DOF controllers and compared their performance in all contracts of restructured systems. As per the simulation outcomes, the amalgamation of DPFC and UC with MFObased 2DOF PID-FOPDN shows low fluctuation rate in frequency and tie-line power. Besides, the settling times (ST) of two areas are 9.5 S for ΔF1, 8.2 S for ΔF2, and 10.15 S for ΔPtie. The robustness of the suggested controller has been verified by ±25% variations in system parameters and loading conditions

Quarter and Full Car Models Optimisation of Passive and Active Suspension System Using Genetic Algorithm

© The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/This study evaluates a suspension design of a passenger car to obtain maximum rider's comfort when the vehicle is subjected to different road profile or road surface condition. The challenge will be on finding a balance between the rider's comfort and vehicle handling to optimize design parameters. The study uses a simple passive suspension system and an active suspension model integrated with a pneumatic actuator controlled by proportional integral derivative (PID) controller in both quarter car and full car models having a different degree of freedoms (DOF) and increasing degrees of complexities. The quarter car considered as a 2-DOF model, while the full car model is a 7-DOF model. The design process set to optimise the spring stiffnesses, damping coefficients and actuator PID controller gains. For optimisation, the research featured genetic algorithm optimisation technique to obtain a balanced response of the vehicle as evaluated from the displacement, velocity and acceleration of sprung and unsprung masses along with different human comfort and vehicle performance criteria. The results revealed that the active suspension system with optimised spring stiffness, damping coefficients and PID gains demonstrated the superior riding comfort and road holding compared to a passive suspension system.Peer reviewe

Bending moment and efficient fatigue assessment in a Subsea Shuttle Tanker under the effect of waves

The subsea shuttle tanker (SST) is the next-generation autonomous submarine designed to transport liquid CO2 from land/offshore facilities to the smaller fields for injection. Unlike normal shuttle tankers, which are highly weather dependent, the SST can carry out freight operations in all weather conditions because it travels underwater between 40 m and 70 m water depth. The first part of the thesis proposes a fast, efficient and reliable multi-body approach to determine the bending moment response of the SST hull at 40 m and 70 m water depth. The chosen approach is based on the discrete-module-beam bending-based hydroelasticity principle. The flexible hull of the vessel is divided into several multi-body rigid modules. All the hydrodynamic and hydrostatic forces are applied to the center of gravity of each rigid module. The parametric models, like the state-space model system, are used to compute the free-surface memory effect more effectively. The multi-body equation of motion is solved to determines the bending moment response of an interconnected multi-body rigid module. The numerical model is prepared using Matlab Simulink to study the dynamics of the vessel. A convergence study is conducted to select the optimal number of bodies needed to perform this study. The result shows that the lower number of bodies (i.e., three and five bodies) does not have enough points to capture all the wave encounter frequencies, thus underestimating the bending moment. Therefore, seven-body SST is used to carry out a further assessment. The bending moment standard deviation is reduced by approximately 50 % when SST travels at 70 m water depth instead of 40 m. The second part of the thesis presents the fatigue assessment of the SST hull, considering the stiffeners' local details. Two FE models (2D axisymmetric and 3D shell element models) representing the local detail of the flooded-mid body of the SST are prepared to determine the stress concentration factor (SCF). The resultant SCF can be given using the superposition concept by taking the product of the SCF for the individual models. The Rainflow counting method and Palmgren-Miner rule are used to calculate the accumulated fatigue damage and fatigue life. The numerical results show that the impact of long waves has contributed to the most damage to the vessel. The minimum fatigue life at the flooded-mid section is 13 and 19 years for the 40 m and 70 m water depths, respectively. The results also shows that fatigue life due to the change in hydrostatic pressure during dive-in and dive-out is five years

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency