Actuator injection attacks pose real threats to all industrial plants controlled through communication networks. In this manuscript, we study the possibility of constraining the controller output (i.e. the input to the actuators) by means of a dynamic filter designed to prevent reachability of dangerous plant states - preventing thus attacks from inducing dangerous states by tampering with the control signals. The filter synthesis is posed as the solution of a convex program (convex cost with Linear Matrix Inequalities constraints) where we aim at shifting the reachable set of control signals to avoid dangerous states while changing the controller dynamics as little as possible. We model the difference between original control signals and filtered ones in terms of the H-infinity norm of their difference, and add this norm as a constraint to the synthesis problem via the bounded-real lemma. Results are illustrated through simulation experiments.
Data-driven Force Observer for Human-Robot Interaction with Series Elastic Actuators using Gaussian Processes
Technical University of Munich（慕尼黑工业大学）；TUM School of Computation, Information and Technology（慕尼黑工业大学计算、信息与技术学院）；BioRobotics Institute, Scuola Superiore Sant’Anna（圣安娜高等学校生物机器人研究所）；ETH Zurich（苏黎世联邦理工学院）
Direct Electromechanical Actuation of the Shift Drum in Non-Synchronized Motorcycle Transmissions: From Actuator Sizing and Electronics Design to Closed-Loop Position Control
LP-MPPI: Low-Pass Filtering for Efficient Model Predictive Path Integral Control
Institute of Robotics and Machine Intelligence, Poznan University of Technology, Poznan, Poland（机器人与机器智能研究所，波兹南技术大学，波兰波兹南）；IDEAS Research Institute, Warsaw, Poland（IDEAS研究所，波兰华沙）
Introducing Coherent-Control Koopman Modeling to Reservoir Scale Porous Media Flow Studies
Harold Vance Department of Petroleum Engineering, Texas A&M University（德克萨斯农工大学哈罗德·万斯石油工程系）；Texas A&M Energy Institute, Texas A&M University（德克萨斯农工大学能源研究所）
