Introduction

MERITORIOUS AUTONOMOUS UNIVERSITY OF PUEBLASchool of Electronics Sciences

Advanced MechatronicsMechatronics in Biomedical Applications and Biomechatronics

IntroductionMechatronic systems have many benefits and big application areas. In consumer electronic, like CD player until packing machines such as food and improvements of modern automotive ABS, stabilization systems. A clear example of mechatronic system is the CD player.The CD-player

BiomechatronicsRecently the BMTI of the University of Twente has started a new research program in biomechatronics.Recently it was decided to start a program of developing mechatronic systems to support elderly and disabled persons.An example of work in this area is the development of new wheelchairs. Originally, wheelchairs were pure mechanical, human powered devices. Modern wheelchairs are not only electrically driven, but can be controlled by means of joystick.Because there are many different handicaps the flexibility that could be obtained by a mechatronic design of these wheelchairs would be of great help to adjust the wheelchair to the personal needs of the user, even if these user needs would change over time.The aging population demands for more care for elderly people in the coming decades. If tools could be developed that enable these people to stay in their homes on their own, rather than moving to nursing homes, their quality of life can be improved and the cost of professional care reduced.

It can be an area of application of home robots, as well as of robotic systems that, for instance, can give a patient a glass of water or feed someone. Such robots will have properties that completely differ from those of conventional, industrial robots.

Neural NetworksAdvanced MechatronicsArtificial neural networks (commonly referred to as RNA or English as "ANN" 1) are a paradigm of learning and automatic processing inspired by the way the nervous system of animals works. It is an interconnection of neurons that work together to produce an output stimulus. In artificial intelligence is often referred to as neural networks or neural networks.

Neural NetworksThe principle of a learning feedforward mechanism can be explained with.

A neural network can be applied to obtain such aperfect model automatically. Because in the ideal case the controller output shouldbe zero, this signal is an indication how well the neural network performs and it canbe used to train the neural network.

The learning is typically finished after a certain reference trajectory hasbeen followed 5-10 times. If the network is too big, stability problems may occur because the networkwill learn stochastic variations, rather than the inherent properties of the process.