Controls and Control Theory Commons^™

Deep Learning-Based, Passive Fault Tolerant Control Facilitated By A Taxonomy Of Cyber-Attack Effects, Dean C. Wardell

Theses and Dissertations

In the interest of improving the resilience of cyber-physical control systems to better operate in the presence of various cyber-attacks and/or faults, this dissertation presents a novel controller design based on deep-learning networks. This research lays out a controller design that does not rely on fault or cyber-attack detection. Being passive, the controller’s routine operating process is to take in data from the various components of the physical system, holistically assess the state of the physical system using deep-learning networks and decide the subsequent round of commands from the controller. This use of deep-learning methods in passive fault tolerant control …

Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal

Theses and Dissertations--Electrical and Computer Engineering

Advances in computing power in recent years have facilitated developments in autonomous robotic systems. These robotic systems can be used in prosthetic limbs, wearhouse packaging and sorting, assembly line production, as well as many other applications. Designing these autonomous systems typically requires robotic system and world models (for classical control based strategies) or time consuming and computationally expensive training (for learning based strategies). Often these requirements are difficult to fulfill. There are ways to combine classical control and learning based strategies that can mitigate both requirements. One of these ways is to use a gravity compensated torque control with reinforcement …

Developing A Uas-Deployable Methane Sensor Using Low-Cost Modular Open-Source Components, Gavin Demali

Williams Honors College, Honors Research Projects

This project aimed to develop a methane sensor for deployment on an unmanned aerial system (UAS), or drone, platform. This design is centered around low cost, commercially available modular hardware components and open source software libraries. Once successfully developed, this system was deployed at the Bath Nature Preserve in Bath Township, Summit County Ohio in order to detect any potential on site fugitive methane emissions in the vicinity of the oil and gas infrastructure present. The deliverables of this project (i.e. the data collected at BNP) will be given to the land managers there to better inform future management and …

The Picture Fuzzy Distance Measure In Controlling Network Power Consumption, Florentin Smarandache, Ngan Thi Roan, Salvador Coll Arnau, Marina Alonso Diaz, Juan Miguel Martinez Rubio, Pedro Lopez, Fran Andujar, Son Hoang Lee, Manh Van Vu

Branch Mathematics and Statistics Faculty and Staff Publications

In order to solve the complex decision making problems, there are many approaches and systems based on fuzzy theory were proposed.

Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi

Honors Theses and Capstones

In this paper, I develop a hierarchical Markov Decision Process (MDP) structure for completing the task of vertical rocket landing. I start by covering the background of this problem, and formally defining its constraints. In order to reduce mistakes while formulating different MDPs, I define and develop the criteria for a standardized MDP definition format. I then decompose the problem into several sub-problems of vertical landing, namely velocity control and vertical stability control. By exploiting MDP coupling and symmetrical properties, I am able to significantly reduce the size of the state space compared to a unified MDP formulation. This paper …