Currently, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia. The book encompasses the kinematic and dynamic modelling, analysis, design, and control of mechatronic and robotic systems, with the scope of improving their performance, as well as simulating and testing novel devices and control architectures. A broad range of disciplines and topics are included, such as robotic manipulation, mobile systems, cable-driven robots, wearable and rehabilitation devices, variable stiffness safety-oriented mechanisms, optimization of robot performance, and energy-saving systems.

Currently, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia. The book encompasses the kinematic and dynamic modelling, analysis, design, and control of mechatronic and robotic systems, with the scope of improving their performance, as well as simulating and testing novel devices and control architectures. A broad range of disciplines and topics are included, such as robotic manipulation, mobile systems, cable-driven robots, wearable and rehabilitation devices, variable stiffness safety-oriented mechanisms, optimization of robot performance, and energy-saving systems.

In modern times, mechatronic and robotic systems are developing at a faster pace than in the past, and research on novel solutions and applications of such devices are studied in both industrial and academic environments. The second volume of this Special Issue of Applied Sciences aims to disseminate the latest research achievements, ideas, and applications of the modeling and control of mechatronic and robotic systems, with particular emphasis on novel trends and challenges. We invited contributions to this Special Issue on topics including (but not limited to): modeling and control, path and trajectory planning, optimization problems, collaborative robotics, mechatronics, flexible multi-body systems, mobile robotics, and manufacturing applications.

In this textbook, fundamental methods for model-based design of mechatronic systems are presented in a systematic, comprehensive form. The method framework presented here comprises domain-neutral methods for modeling and performance analysis: multi-domain modeling (energy/port/signal-based), simulation (ODE/DAE/hybrid systems), robust control methods, stochastic dynamic analysis, and quantitative evaluation of designs using system budgets. The model framework is composed of analytical dynamic models for important physical and technical domains of realization of mechatronic functions, such as multibody dynamics, digital information processing and electromechanical transducers. Building on the modeling concept of a technology-independent generic mechatronic transducer, concrete formulations for electrostatic, piezoelectric, electromagnetic, and electrodynamic transducers are presented. More than 50 fully worked out design examples clearly illustrate these methods and concepts and enable independent study of the material.

Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes: An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control Dedicated chapters for advanced topics such as multibody dynamics and micro-electromechanical systems, vehicle mechatronic systems, robot kinematics and dynamics, space robotics and intelligent transportation systems Detailed discussion of cooperative environments and reconfigurable systems Intelligent Mechatronic Systems provides control, electrical and mechanical engineers and researchers in industrial automation with a means to design practical, functional and safe intelligent systems.

Modern robotic systems are tied to operate autonomously in real-world environments performing a variety of complex tasks. Autonomous robots must rely on fundamental capabilities such as locomotion, trajectory tracking control, multi-sensor fusion, task/path planning, navigation, and real-time perception. Combining this knowledge is essential to design rolling, walking, aquatic, and hovering robots that sense and self-control. This book contains a mathematical modelling framework to support the learning of modern robotics and mechatronics, aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. The volume exposes a solid understanding of mathematical methods as a common modelling framework to properly interpret advanced robotic systems. Including numerical approximations, solution of linear and non-linear systems of equations, curves fitting, differentiation and integration of functions. The book is suitable for courses on robotics, mechatronics, sensing models, vehicles design and control, modelling, simulation, and mechanisms analysis. It is organised with 17 chapters divided in five parts that conceptualise classical mechanics to model a wide variety of applied robotics. It comprehends a hover-craft, an amphibious hexapod, self-reconfiguration and under-actuation of rolling and passive walking robots with Hoekens, Klann, and Jansen limbs for bipedal, quadruped, and octapod robots.

As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems.