Formal synthesis of partially-observable cyber-physical systems

This dissertation is motivated by the challenges arising in the synthesis of controllers for partially-observable cyber-physical systems (PO-CPSs). In the past decade, CPSs have become ubiquitous and an integral part of our daily lives. Examples of such systems range from autonomous vehicles, drones, and aircraft to robots and advanced manufacturing. In many applications, these systems are expected to do complex logic tasks. Such tasks can usually be expressed using temporal logic formulae or as (in)finite strings over finite automata. In the past few years, abstraction-based techniques have been very promising for the formal synthesis of controllers. Since these techniques are based on the discretization of state and input sets, when dealing with large-scale systems, unfortunately, they suffer severely from the curse of dimensionality (i.e., the computational complexity grows exponentially with the dimension of the state set). In order to overcome the large computa- tional burden, a discretization-free approach based on control barrier functions has shown great potential to solve formal synthesis problems. In this thesis, we provide a systematic approach to synthesize a hybrid control policy for partially-observable (stochastic) control systems without discretizing the state sets. In many real-life applications, full-state information is not always available (due to the cost of sensing or the unavailability of the measurements). Therefore, in this thesis, we consider partially-observable (stochastic) control systems. Given proper state estimators, our goal is to utilize a notion of control barrier functions to synthesize control policies that provide (and potentially maximize) a lower bound on the probability that the trajectories of the partially-observable (stochastic) control system satisfy complex logic specifications such as safety and those that can be expressed as deterministic finite automata (DFA). Two main approaches are presented in this thesis to construct control barrier functions. In the first approach, no prior knowledge of estimation accuracy is needed. The second approach utilizes a (probability) bound on the estimation accuracy. Though the synthesis procedure for lower-dimensional systems is challenging itself, the task is much more computationally expensive (if not impossible) for large-scale interconnected systems. To overcome the challenges encountered with large-scale systems, we develop approaches to reduce the computational complexity. In particular, by considering a large-scale partially-observable control system as an interconnection of lower-dimensional subsystems, we compute so-called local control barrier functions for subsystems along with the corresponding local controllers. By assuming some small-gain type conditions, we then utilize local control barrier functions of subsystems to compositionally construct an overall control barrier function for the interconnected system. Finally, since closed-form mathematical models of many physical systems are either unavailable or too complicated to be of any use, we also extend our work to the synthesis of safety controllers for partially-observable systems with unknown dynamics. To tackle this problem, we utilize a data-driven approach and construct control barrier functions and their corresponding controllers via sets of data collected from the output trajectories of the systems and the trajectories of the estimators. To demonstrate the effectiveness of the proposed results in the thesis, we consider various case studies, such as a DC motor, an adaptive cruise control (ACC) system consisting of vehicles in a platoon, and a Moore-Greitzer jet engine model

Synthesis of Controllers for Partially-Observable Systems: A Data-Driven Approach

This paper is concerned with the formal synthesis of safety controllers for partially-observable continuous-time polynomial-type systems with unknown dynamics. Given a continuous-time polynomial-type estimator with a partially-unknown dynamic and a known upper bound on the estimation accuracy, we propose a data-driven approach to compute a polynomial-type controller ensuring safety of the system. The proposed framework is based on a notion of so-called control barrier functions and only requires a single output trajectory collected from the system and a single state trajectory collected from its estimator. We show the application of our technique by synthesizing a safety controller for a partially-observable jet engine with unknown dynamics.</p

Synthesis of Partially Observed Jump-Diffusion Systems via Control Barrier Functions

In this letter, we study formal synthesis of control policies for partially observed jump-diffusion systems against complex logic specifications. Given a state estimator, we utilize a discretization-free approach for formal synthesis of control policies by using a notation of control barrier functions without requiring any knowledge of the estimation accuracy. Our goal is to synthesize an offline control policy providing (potentially maximizing) a lower bound on the probability that the trajectories of the partially observed jump-diffusion system satisfy some complex specifications expressed by deterministic finite automata. Finally, we illustrate the effectiveness of the proposed results by synthesizing a policy for a jet engine example.</p

Pharmacotherapy and Associated Factors in Women with Gestational Diabetes

Introduction Pharmacotherapy is an indicator of severity of hyperglycemia in pregnancy that may reflect β-cell dysfunction in women with gestational diabetes mellitus. Methods and Results &nbsp;Life after gestational diabetes Ahvaz Study (LAGAs) is a population-based prospective cohort study to investigate potential short and long-term metabolic outcomes of gestational diabetes in mothers and their offsprings. Pregnant women attending 25 urban public and private centers seeking prenatal care were recruited from March 2015. 19.3% (34/176) of women with gestational diabetes required pharmacotherapy in pregnancy (12.5% insulin and 6.8% metformin). The mean age of women who needed pharmacotherapy was 31.0 (SD, 4.6) years vs 29.3 (SD, 5.3) years in diet-treated women. Cesarean delivery, higher FPG at first visit of pregnancy and premature delivery were significantly associatiated &nbsp;with need to pharmacotherapy in pregnancy (p&lt;0.05).&nbsp; Conclusions Although the use of oral anti-diabetic drugs in pregnancy is not recommended by the American diabetes Association (ADA), consumption of them in women exposed to gestational diabetes is considerable. Use of insulin or metformin for management of hyperglycemia in pregnancy strongly prognoses metabolic disturbance later in life.&nbsp; Therefore postpartum prevention and screening program for cardiovascular risk factors is important for women with GDM who required pharmacotherapy for management of hyperglycemia in pregnancy

An adaptive sliding mode observer for linear systems under malicious attack

Recent years have witnessed extensive research activities in the development of control law architectures for cyber-physical systems consisting of sensing, computing and communication modules working together to control physical systems. One of the main challenges in cyber-physical systems is the vulnerability to adversarial attacks. As the important module in cyber physical systems, sensor measurements are prone to malicious attacks due to the use of open computation and communication architectures. This paper proposes an adaptive sliding mode observer for state estimation of systems subjected to adversarial attacks. The novelty of the method considered here lies in the use of the equivalent control concept to explicitly reconstruct attack signals and consequently the system state. A design procedure is described and simulation results are presented to demonstrate the effectiveness of the proposed approach.This publication was made possible by NPRP grant No. NPRP 5- 045-2-017 and NPRP 6-463-2-189 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu