 Название: Computational Intelligent Techniques in Mechatronics
Автор: Kolla Bhanu Prakash, Satish Kumar Peddapelli, Ivan C. K. Tam, Wai Lok Woo, Vishal Jain
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 532
Язык: английский
Формат: pdf (true)
Размер: 58.4 MB
Computational Intelligent Techniques welcomes a diverse audience to learn about technological innovation in the mechatronics system. This comprehensive resource is designed to empower readers with the knowledge and skills in the rapidly evolving world of mechatronics. Equipped with knowledge about mechatronic systems, and discussions on cutting-edge technologies in the latest innovations, this book is a learning gateway with tools to design, analyze, and implement mechatronic systems across various industries.
Dive into 15 chapters covering the basics of mechatronics, computational intelligence approaches, simulation, and modeling concepts. This book will help research and development departments understand various branches of the engineering design process. Learn about challenges and opportunities in employing these techniques and how mechatronics proposes future research direction to optimize the system. Explore the components, challenges, and benefits of integrating AI in self-driving transportation systems. Lastly, read up on the latest mechatronics in altering current agriculture practices including productivity and sustainability.
The chapter “AI in Mechatronics” provides a comprehensive overview of how Artificial Intelligence (AI) techniques can enhance mechatronic systems; it covers core AI approaches, including Machine Learning, computer vision, soft computing methods, natural language processing, AI planning, and intelligent system design tools. Key real-world applications across areas like manufacturing automation, robotics, vehicles, and human–machine interaction are analyzed. The integration of data-driven and knowledge-based AI methods can endow mechatronics with advanced capabilities around autonomy, environmental perception, reasoning, control, and human collaboration. This creates intelligent self-optimizing systems that continue learning and adapting. Current challenges around model accuracy, data availability, security, and algorithmic transparency are discussed along with emerging opportunities in embedded intelligence and bio-inspired robotics. Overall, the synergistic fusion of AI and mechatronics promises to transform technological systems across industrial and societal domains by enhancing automation, augmenting human capabilities, and enabling next-generation smart mechanized assistants.
Industrial automation and control systems have been revolutionized by the mechatronics sector’s widespread use of programmable logic controllers (PLCs). Many industries are adopting mechatronics, merging mechanical, electrical, and computer engineering to improve efficiency, accuracy, and production. This study delves into the widespread use of PLCs in mechatronics applications, covering their underlying concepts, programming methods, and seamless integration with mechatronics gadgets. The first section of the article serves as an introduction to PLCs, discussing their history, architecture, and programming languages. It highlights the benefits of using PLCs in mechatronics systems and how well they interface with other devices and parts. The fundamentals of PLC programming, including ladder logic, sequential function charts, and function block diagrams, are also covered in depth. The importance of sensors and actuators for monitoring physical variables and regulating mechanical motion is discussed in this study, which focuses on PLC-based mechatronics systems. It highlights the effective deployment of PLCs in various industrial contexts by showcasing real-world case studies, including illustrations of PLC-controlled automated assembly lines, robotic arms, and computer numerical control (CNC) machine tools. The importance of motion control in mechatronics and the role that PLC-based motion control approaches play in obtaining precise motion are discussed. In addition, the study explores human–machine interaction/PLC integration, guiding how to create intuitive user interfaces for mechatronics.
Computational Intelligence (CI) has emerged as a powerful paradigm in the field of autonomous robotics and drones, enabling the development of intelligent, adaptive, and self-learning systems. This chapter explores the application of CI techniques in autonomous robotics and drones, focusing on the utilization of Artificial Intelligence, machine learning, and swarm intelligence algorithms to enhance navigation, perception, decision-making, and collaboration capabilities. The journey starts with an introduction to autonomous robotics and drones, outlining the challenges and opportunities in developing self-sufficient systems. It then delves into the fundamentals of CI, explaining the concepts of Artificial Intelligence, Machine Learning, and swarm intelligence, and their significance in autonomous systems.
This chapter is based on a novel Arduino-based multi-featured robot. The components required are Arduino UNO, ultrasonic sensor, Bluetooth module, servomotor, and a few more hardware devices. With the ever-increasing technological advancement, it has become easier to communicate from the different places; it could be nearby, few kilometers away, or very far, thousands of kilometers away. Thus, it has come to notice that there are a few places where it is hard and dangerous to explore for the human beings. Using Arduino controller, ESP32 CAM, and few sensors, we can explore such locations. Nowadays, with the increase of population, it is hard to invigilate all the students during an examination. So, this proposed model of multi-featured robot is very useful in keeping an eye, as it can send live surveillance and also any notification if human motion is detected.
Contents:
Preface xxi
1 AI in Mechatronics 1
2 Thermodynamics for Mechatronics 41
3 Role of Data Acquisition, Sensors, and Actuators in Mechatronics Industry 83
4 Optimization Techniques for Mechatronics: A Comprehensive Review and Future Directions 109
5 Reinforcement Learning for Adaptive Mechatronics Systems 135
6 Application of PLC in the Mechatronics Industry 185
7 Fuzzy Logic and Its Applications in Mechatronic Control Systems 211
8 Drones and Autonomous Robotics Incorporating Computational Intelligence 243
9 Exploring the Convergence of Artificial Intelligence and Mechatronics in Autonomous Driving 297
10 Improving Power Quality for Industry Control Using Mechatronics Devices 317
11 Study on Integrated Neural Networks and Fuzzy Logic Control for Autonomous Electric Vehicles 347
12 Advancing Mechatronics Through Artificial Intelligence 381
13 Computational Intelligent Techniques in Mechatronics: Emerging Trends and Case Studies 401
14 Advanced Sensing Systems in Automobiles: Computational Intelligence Approach 445
15 Design of Arduino UNO-Based Novel Multi-Featured Robot 471
16 Integrating Mechatronics in Autonomous Agricultural Machinery: A Case Study
References 505
Index 509
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