Igor Astrov’s research while affiliated with Tallinn University of Technology and other places

The aim of this paper is to highlight the vulnerability of Maritime Autonomous Surface Ships (MASS) to cyber-attack and to illustrate, through a simulation experiment on a testbed, how to mitigate a cyber-attack on the MASS thruster controllers during low-speed motion. The first part of the paper is based on a scoping review of relevant articles in the field, including some MASS projects, related cyber threats and modelling techniques to improve cyber resilience. In the second part of the paper, a cyber-attack on the MASS thruster controllers at low speed motion is illustrated along with the impact of the attack on the trajectory motion. The Kalman filter, as an additional device to the thruster controllers, is used as a cyber-attack mitigation aid. Under the conditions of a simulated intrusion on the input and output signals of the thruster, the experiments conducted in the MATLAB Simulink environment provide an insight into the behaviour of the MASS propulsion subsystem from the perspective of the low-speed trajectory, with and without the Kalman filter.

A sharp increase in the importance of autonomous vehicles can be foreseen in future maritime transport. One important area of application of autonomous waterborne vehicles is the monitoring of the safety of sea routes and sea areas. In this case, an important subtask is following the desired coordinates and movement trajectories as accurately as possible, despite natural disturbances and malicious cyberattacks. In this work, we discuss the model-based ship navigation with increased disturbance resistance to assure the desired control of a catamaran robot ship in different conditions of natural disturbances and missing global positioning data due to possible cyber-attacks. The considered example autonomous surface vessel (ASV) is a catamaran ship of 2.5 m length, developed at Tallinn University of Technology. Different from the previous studies, in this work we have completed the hydromechanical ship model with wind force model in order to simulate the influence of nonlinear environment conditions to the accuracy of ship navigation. The main result, illustrated by detailed numerical calculations, is that the availability of an accurate mathematical model of ASV together with accurate data from local sensors (in particular ship direction and wind speed sensors) can compensate for the lack of a GPS signal under cyber-attack conditions. In addition, we demonstrate with a numerical simulation how data fusion methodology, supplementing the wind effect measurements with local ship sensor data, can achieve even better navigation accuracy.

The effective computer control of airborne, waterborne, and ground autonomous vehicles has become one of the highest priorities in the area of cyber-physical systems, Industry 4.0 in particular, and the world economy in general. Despite extensive research on Unmanned Aerial Vehicles (UAVs), the study of Autonomous Surface Vessels (ASVs) has been more than ten times less intense. As an attempt to fill a gap in that field, this article discusses the control mathematics of a realistic ASV nonlinear model of a real autonomous electric catamaran “Nymo”, which was designed at Tallinn University of Technology (TalTech). More technically, the article offers a novel adaptive control system that is based on knowledge of the main parameters of ASV and is specially designed for a Simulink/MATLAB environment. The article also enables adjusting variables like transition time and heading angle overshoot value. The control of the desired tracking is represented in such a maneuver as turning the catamaran at different angles. The designed control system has shown good quality in terms of accuracy in tracking the desired heading angles.

High-quality computer control of autonomous vehicles in various environments is a priority for cyber-physical systems (CPS), Industry 4.0, and the global economy as a whole. The paper discusses the linearized control model of a Self-Driving Car (SDC) with a weight of 1160 kg. For safe maneuvering with obstacle avoidance, we employ an optimal control by Linear Quadratic Regulator (LQR) using a Simulink/MATLAB environment that is capable to demonstrate the satisfiability of LQR control for this maneuver using a 3D simulation environment under changing urban conditions in a smart city. This controller is easy for engineering implementation.