Abstract

The key role of cybernetics may be described as the study and design of dynamical system behaviours, namely restrictions on the universum of outcomes arising from the input-output product space, or if convenient, the input-state-output product space. Such restrictions establish what is possible and conversely what is not as systems interact with their environments. In this talk, I will use the behavioural approach to mathematical system theory to set the scene and discuss three problems in which in am currently doing research, and on which I would welcome collaborations. 

The first problem is related to Agricultural Cybernetics, which takes a system view of agriculture for the analysis and design of management strategies to control and optimise agricultural production systems while exploiting the intrinsic feedback information-exchanging mechanisms. This problem is rapidly gaining importance as digital technologies disrupt agriculture and data becomes available - big-data cybernetics. Feedback is great tool, but it is also the subject to fundamental limitations, which when not understood properly can lead to underwhelming results as well as wasting time and resources. This is where Agricultural Cybernetics enters the scene by seeking to answer fundamental questions related to systems and system behaviours.

The second problem relates to the use of inverse optimal control and inverse differential games to gain insight into the behaviours of birds avoiding impending collisions and how can these be translated into potential behaviours for UAS. Here, we exploit the discrete-time Minimum Principle plus structure in the in the cost functional of optimal control problems and differential games to infer elements of the cost functional from incomplete state information. 

The last problem relates to enabling aspects of autonomous system technology. We advocate that the assessment of hypotheses about system behaviours related to performance and safety can lead to decision theoretic frameworks for assessment of autonomy that can assist with regulation, insurance, and procurement decisions. Here we exploit the use of probability as an extension of logic leading to a Bayesian approach to quantify the uncertainty associated with decision problems related to the adoption of autonomy. We also discuss extensions to the assessment of learning agents.

Bio

Tristan Perez is Professor of Robotics and Autonomous Systems at The Queensland University of Technology (QUT).  He leads the IntelliSensing Enabling Platform at QUT's Institute for Future Environments. This is a transdisciplinary program that focuses on assisting industry to transition into the digital age - transforming data collection, modelling, analytics, decisions and control.  Tristan is an Assoc. Investigator at the ARC CoE for Mathematical and Statistical Frontiers (ACEMS) and at ARC CoE for Robotic Vision (ACRV). He is also the Co-Chair – IFAC Technical Committee in Marine Systems.

Tristan conducts and leads research in the areas of:

• Dynamics and control of cyber-physical systems
• Robotics with applications to agriculture
• Data-enabled Agriculture  
• Bayesian inference and decisions under uncertainty
• Biologically inspired behaviours for unmanned aircraft
• Motion control of underwater vehicles close to the surface

From 2010 to 2014, he was the leader of the mechatronics program at the University of Newcastle in Australia, where he also lead a Laboratory for Autonomous Systems and Robotics. In this position, he  was working on assessment of robust autonomous systems, energy-based control of mechanical systems, and bio-inspired robust navigation systems for unmanned aircraft.  

From 2007 to 2010, he was with the Australian Research Council Centre of Excellence for Complex Dynamic Systems and Control (CDSC), at the University of Newcastle. From 2008 to 2012, he was also an Adjunct Associate Professor of ship dynamics at the Norwegian University of Science and Technology (NTNU), Norway. From 2004 to 2007 he was a senior researcher at the Centre for Ships and Ocean Structures of the Norwegian University of Science and Technology, Trondheim, Norway. 

Tristan completed his Electronic Engineering degree at the National University of Rosario, Argentina, in 1999 and a PhD in Control Engineering at the University of Newcastle, Australia, in 2003. He moved to QUT in 2014.

Tristan Perez
Professor - Robotics and Autonomous Systems
Electrical Engineering & Computer Science,
Queensland University of Technology (QUT)  

Gardens Point, S Block Level 11,
2 George Street, Brisbane, QLD 4000 | CRICOS No. 00213J
phone: + 61 7 3138 9076 | m: +61 4475 9 0011
e-mail: tristan.perez@qut.edu.au |
website: http://staff.qut.edu.au/staff/perez5/ 

Leader - IntelliSensing Enabling Platform, Institute for Future Environments, QUT
Honorary Professor - Dynamical Systems and Control, QBI, University of Queensland
Assoc. Investigator - ARC CoE for Mathematical and Statistical Frontiers (ACEMS)
Assoc. Investigator - ARC CoE for Robotic Vision (ACRV)
Co-Chair – IFAC Technical Committee in Marine Systems
Publications: http://eprints.qut.edu.au/view/person/Perez,_Tristan.html