Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

A PLC-based Hybrid Fuzzy PID Controller for PWM-driven Variable Speed Drive

In adjustable-speed drive applications, the range of speed and torque achievable is very important. A power electronic converter is needed as an interface between the input AC power and the drive. A controller is needed to make the motor (drive), through the power electronics converter meets the drive requirements. The widely used conventional control that is based on mathematical model of the controlled system is very complex and not easy to be determined since it requires explicit knowledge of the motor and load dynamics. This thesis proposed a design and implementation of a PLC-based hybrid controller from a basic PLC to a PWM-driven variable-voltage variable-frequency (VVVF) speed control of an induction motor and the analysis, evaluation and improvement of the control strategies. A simulation model in MA TLAB/Simulink is developed using system identification technique to perform verification of the PLCbased intelligent controller of the PWM-driven VVVF algorithm. To provide stability in response to sudden changes in reference speed and/or load torque, a switching type controller consisting of two control modes are devised: a PID-type fuzzy controller consisting of a PI-type and a PD-type fuzzy controller, and a conventional PID. The proposed scenario is implementing a strategy when the actual value is closed to setpoint. At the early phase of the control action, the control task is handled by the PIDtype fuzzy controller. At a later phase when the absolute of error is less than a threshold value, the input of integrator at the output side is no longer given by fuzzy action but fed by the incremental PID action. In term of control action, this is an enhanced proportional and derivative action when the actual value is closed to reference. Detailed evaluations of the controller's performance based-on a predefined performance indices under several conditions are presented. The findings demonstrate the ability of the control approach to provide a viable control solution in response to the different operating conditions and requirements

Navigational Path Analysis of Mobile Robot in Various Environments

This dissertation describes work in the area of an autonomous mobile robot. The objective is navigation of mobile robot in a real world dynamic environment avoiding structured and unstructured obstacles either they are static or dynamic. The shapes and position of obstacles are not known to robot prior to navigation. The mobile robot has sensory recognition of specific objects in the environments. This sensory-information provides local information of robots immediate surroundings to its controllers. The information is dealt intelligently by the robot to reach the global objective (the target). Navigational paths as well as time taken during navigation by the mobile robot can be expressed as an optimisation problem and thus can be analyzed and solved using AI techniques. The optimisation of path as well as time taken is based on the kinematic stability and the intelligence of the robot controller. A successful way of structuring the navigation task deals with the issues of individual behaviour design and action coordination of the behaviours. The navigation objective is addressed using fuzzy logic, neural network, adaptive neuro-fuzzy inference system and different other AI technique.The research also addresses distributed autonomous systems using multiple robot

Sensor based real-time mechatronic control of computer integrated manufacturing

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2008Industrial competition is characterised by increasing globalisation of markets, coupled wit