Dynamic Modeling and Torque Feedforward based Optimal Fuzzy PD control of a High-Speed Parallel Manipulator

Dynamic modeling and control of high-speed parallel manipulators are of importance due to their industrial applications deployed in production lines. However, there are still a number of open problems, such as the development of a precise dynamic model to be used in the model-based control design. This paper presents a four-limb parallel manipulator with Schönflies motion and its simplified dynamic modeling process. Then, in order to fix the issue that computed torque method control (CTC) will spend a lot of time to calculate dynamic parameters in real-time, offline torque feedforward-based PD (TFPD) control law is adopted in the control system. At the same time, fuzzy logic is also used to tune the gains of PD controller to adapt to the variation of external disturbance and compensate the un-modeled uncertainty. Additionally, bottom widths of membership functions of fuzzy controller are optimized by bat algorithm. Finally, three controllers of CTC, TFPD and bat algorithm-based torque feedforwad fuzzy PD controller (BA-TFFPD) are compared in trajectory tracking simulation. Fro the result, compared with TFPD and CTC, BA-TFFPD can lead faster transient response and lower tracking error, which prove the validity of BA-TFFPD

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

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

Towards Closed-loop, Robot Assisted Percutaneous Interventions under MRI Guidance

Image guided therapy procedures under MRI guidance has been a focused research area over past decade. Also, over the last decade, various MRI guided robotic devices have been developed and used clinically for percutaneous interventions, such as prostate biopsy, brachytherapy, and tissue ablation. Though MRI provides better soft tissue contrast compared to Computed Tomography and Ultrasound, it poses various challenges like constrained space, less ergonomic patient access and limited material choices due to its high magnetic field. Even after, advancements in MRI compatible actuation methods and robotic devices using them, most MRI guided interventions are still open-loop in nature and relies on preoperative or intraoperative images. In this thesis, an intraoperative MRI guided robotic system for prostate biopsy comprising of an MRI compatible 4-DOF robotic manipulator, robot controller and control application with Clinical User Interface (CUI) and surgical planning applications (3DSlicer and RadVision) is presented. This system utilizes intraoperative images acquired after each full or partial needle insertion for needle tip localization. Presented system was approved by Institutional Review Board at Brigham and Women\u27s Hospital(BWH) and has been used in 30 patient trials. Successful translation of such a system utilizing intraoperative MR images motivated towards the development of a system architecture for close-loop, real-time MRI guided percutaneous interventions. Robot assisted, close-loop intervention could help in accurate positioning and localization of the therapy delivery instrument, improve physician and patient comfort and allow real-time therapy monitoring. Also, utilizing real-time MR images could allow correction of surgical instrument trajectory and controlled therapy delivery. Two of the applications validating the presented architecture; closed-loop needle steering and MRI guided brain tumor ablation are demonstrated under real-time MRI guidance

MATLAB

This excellent book represents the final part of three-volumes regarding MATLAB-based applications in almost every branch of science. The book consists of 19 excellent, insightful articles and the readers will find the results very useful to their work. In particular, the book consists of three parts, the first one is devoted to mathematical methods in the applied sciences by using MATLAB, the second is devoted to MATLAB applications of general interest and the third one discusses MATLAB for educational purposes. This collection of high quality articles, refers to a large range of professional fields and can be used for science as well as for various educational purposes

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

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Design and Hardware-in-the-Loop Testing of Optimal Controllers for Hybrid Electric Powertrains

The main objective of this research is the development of a flexible test-bench for evaluation of hybrid electric powertrain controllers. As a case study, a real-time near-optimal powertrain controller for a series hybrid electric vehicle (HEV) has been designed and tests. The designed controller, like many other optimal controllers, is based on a simple model. This control-oriented model aims to be as simple as possible in order to minimize the controller computational effort. However, a simple model may not be able to capture the vehicle's dynamics accurately, and the designed controller may fail to deliver the anticipated behavior. Therefore, it is crucial that the controller be tested in a realistic environment. To evaluate the performance of the designed model-based controller, it is first applied to a high-fidelity series HEV model that includes physics-based component models and low-level controllers. After successfully passing this model-in-the-loop test, the controller is programmed into a rapid-prototyping controller unit for hardware-in-the-loop simulations. This type of simulation is mostly intended to consider controller computational resources, as well as the communication issues between the controller and the plant (model solver). As the battery pack is one of the most critical components in a hybrid electric powertrain, the component-in-the-loop simulation setup is used to include a physical battery in the simulations in order to further enhance simulation accuracy. Finally, the driver-in-the-loop setup enables us to receive the inputs from a human driver instead of a fixed drive cycle, which allows us to study the effects of the unpredictable driver behavior. The developed powertrain controller itself is a real-time, drive cycle-independent controller for a series HEV, and is designed using a control-oriented model and Pontryagin's Minimum Principle. Like other proposed controllers in the literature, this controller still requires some information about future driving conditions; however, the amount of information is reduced. Although the controller design procedure is based on a series HEV with NiMH battery as the electric energy storage, the same procedure can be used to obtain the supervisory controller for a series HEV with an ultra-capacitor. By testing the designed optimal controller with the prescribed simulation setups, it is shown that the controller can ensure optimal behavior of the powertrain, as the dominant system behavior is very close to what is being predicted by the control-oriented model. It is also shown that the controller is able to handle small uncertainties in the driver behavior