AIC3: Automation, Industrial Computing, Communication and Control Laboratory

Factory of the Future model
One of the four main components of the lab is factory of the future. We have two large systems demonstrating the same. The Festo MPS model and Festo Prolog factory model.
Production, manufacturing and storage

Production system Festo MPS 500 will demonstrate the following
- Customised product
- Smart product
- On the fly layout change
- Smart autonomous stations providing services
- Demonstration of the factory floor warehouse and on-demand order delivery with sorting
Smart autonomous stations providing services

Industrial Robotics
We have various robots in our lab, 4 Autonomous logistics robot, human friendly Baxter robot and a industrial ABB robot that can multitask many operations with its changeable grippers

The ABB Robot is mounted on a rail and performs three operations with its three changable grippers
- Aseembly of workpieces on the Festo MPS production system
- Packaging of upto 4 workpieces onto a pallet on the Festo Proglog factory logistics systems
- Reload 3D printed work pieces from 3D printer to the MPS source station with the help of the Robotino automnomous robots.
Building automation
Building automation is the automated control of the heating, ventilation, air conditioning, lighting and other systems using centralized controllers within a building. We are taking Building Automation Systems (BAS) systems to the next level with the introduction of decentralized BAS systems providing flexibility and robustness to BAS systems.

A commercial building can be classified as a complex Cyber-Physical Systems system where many physical processes (sensors and actuators such as lights, light switches HVACs etc are individually monitored and controlled by computation processes interacting via communication links to provides a flexibile and efficient Building Automation Control System (BACS) system.
There are many challenges in modern BACS systems where centralized control system are not longer thought to be adequate. These challenges includes:
- Demand for reusable control artefacts since BACS usually involves significant amount of recurrent tasks with repetitive rooms with identical functions. There is a need to reduce these laborious tasks with an effective well-define design paradigm and reusable control software.
- Need of a comprehensive metering infrastructure for handling of metering in decentralized BACS systems.
- Demand for simulation-in-the-loop testing for quick prototyping and evaluation of various control strategies.
Simulation-in-the-loop
It is not always possible to test or evaluate your BACS on a real-system nor is it desirable. Simulation-in-the-loop is often used to evaluate the designed system be it software-in-the-loop (SIL) or hardware-in-the-loop (HIL) with OPAL-RT

Experimental Testbed for Electrical Distribution Networks
The Smart Grid concept is being widely researched and prototyped in the last decade. With the introduction of widespread distributed energy generation, which motivates bi-directional flow of energy, current electrical grid needs to evolve from energy delivery network into an Energy Exchange network ie the Energy Internet. We have developed a prototype of a distribution network, where we can model and test our Smart Grid solutions.

Smart Grid promises efficient, sustainable and reliable electricity infrastructure, where every member of the grid (consumer, energy retailer, operator and generation) is an active participant in fast-paced real-time energy market.
To control such a complex and highly distributed infrastructure, the Smart Grid has to employ new generation of distributed automation and control systems, ie Distributed Grid Intelligence (DGI). DGI is a network of distributed nodes performing intelligent control to achieve goals and local participating in overall Smart Grid operation and control system to achieve objectives. These nodes are essentially agents operating autonomously, reacting on the environment and proactively negotiating among themeselves to realize systems objectives, exhibiting social behavior. DGI of the Smart Grid is best realized as a distributed multi-agent systems (MAS).
To test our agent based systems we developed a test bed. The test bed allows us to model various configuraitons of the distribution networks. We now able to test and demonstrate our Smart Grid projects: design, development and implementation.
Multi-agent control system is Implemented using IEC 61499 IDE and deployed to several Beckhoff industrial controllers and PLCs nxtMini.
The multi-agent system is developed in the IEC 61499 FBs. Each agent is modelled as composite FB and represents a particular power system protection function, such as overcurrent or autoreclosing.
Usually we test our systems by interfacing PLCs to PC which running the Matlab simulation. Current and voltage measurements are passed from Matlab to PLC via Ethernet.
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