Model predictive controller and monitoring systems for Marine Autonomous Surface Ships (MASS)

For marine autonomous surface ships (MASS), a more acceptable operation is ‘constrained autonomous operation’ where the ship operates fully autonomously. Most of the existing systems have strictly defined operational constraints or limited available decision spaces; therefore, autonomous decisions are only allowed for some predefined scenarios. However, marine environment is dynamic; the environmental disturbances (wind, wave, current, ice), surrounding obstacles (ship, ice) can change quickly. In this project, we plan to develop an on-board navigation system using non-linear model predictive controllers (NMPCs) which will incorporate the path planning, collision avoidance, and tracking of the defined path and can deal with rapidly changing dynamic conditions in the sea. This cutting-edge research will help place Canada at the forefront of Marine Autonomous Surface Ship research. Our plan is to collaborate with various Canadian Marine Automation Vendors (e.g. Fleetway, Rockwell Automation, Siemens), Coast Guard etc. to fully harness the benefit of the proposed solution and improve the Canadian shipping industry in general.

Faculty Supervisor:

Syed Imtiaz

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Technology; Transportation (excluding aerospace)

University:

Memorial University of Newfoundland

Program: