Dynamic Simulation and Control Design (IA5617) Elective course in control technology for the IA bachelor program Carlos F. Pfeiffer and Roshan Sharma University College of Southeast Norway, Porsgrunn, Norway

Overview and purpose 10 credits elective course for the 5th semester of the IA bachelor program in control technology (A and Y). The course offers the students an option to: increase their expertise in the design of advanced control systems by using state of the art dynamic simulation tools. to demonstrate and apply the theory and methods covered with real processes

The purpose of the course is: To help meet the industry's need for automation engineers with deep expertise. To provide necessary theoretical knowledge for IA bachelor students who want to continue their education with a master in automation. To provide an offer of an advanced course in control engineering to students who are motivated to extend and deepen the topics learned in IA3112 (Automation technology).

Learning outcomes Knowledge: The students will learn the theoretical basis for model-based simulation and control design of industrial processes. Skills: The students will be able to design, simulate and implement control systems on selected software platforms. The students will be able to test different control methods and control strategies using dynamic simulators. Given the importance of the Smart House project it is essential to study the legal aspects on how the project will affect the user and the population in general.

General competences The students will be able to assess the usefulness of dynamic simulation and control design with regard to technology, environment and economy. The students will be able to understand literature and communicate with professionals about model-based control design of industrial processes. The students will be able to document and disseminate the results of projects on model based control design. *Study and research on different algorithms to effectively describe and store activities and behaviours so that the system can be automatically adapted to the person at the home. *Fuzzy Logic, artificial neural network, Markov Chain, Bayesian networks, and others, in order to select the best modelling algorithm for the project. Algorithms to be evaluated and applied in the project will include: Fuzzy Logic, artificial neural network, Markov Chain, Bayesian networks, and others.

Teaching and learning methods The teaching methodology will use lectures in two sessions per week: During the first session theory and methods will be presented and demonstrated with simple systems. During the second session extensive simulation exercises and application of the topics developed during the first session will be applied to more complex systems (an helicopter system and a four tanks level system) . There will be both individual and group-based learning activities. Several companies now offer packages of welfare technological sensors and solutions. They make it easier to stay at home for people with special needs

Use of state of the art simulation tools SIMULINK Graphic programing. Block oriented. Able to handle contiunos and discrete systems. Able to handle mixed continuos and discrete systems. Extensivly used for research, analysis and design, both on academy and industry. - Aims to automatically monitor the older adult on their activities of daily life (ADL) such as eating, bathing, and sleeping habits [12] - Smart House system should ideally control the functions of the house and interact with the person through voice, movement sensors, hand gestures, touch panels, and other devices

Realistic and challenging advanced multivariable processes Four tanks level system Prototype helicopter system

Platform: Simulation and implementation

Platform: Simulation and implementation Graphical approach to system and control design Drag-drop-connect Sits on top of MATLAB so it can inherit all the features and functions of MATLAB Simulink library contains ready-to-use blocks for various operations such as: Model development and simulation System analysis Design and implementation of control systems Simulink desktop real-time kernel: for implementation

Platform: Simulation and implementation Demonstration