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Vehicular platoons provide an appealing option for future transportation systems. Most of the existing work on platoons separated the design of the controller and its communication topologies. However, it is beneficial to design both the platooning controller and the communication topology simultaneously, i.e., controller and topology co-design, especially in the cases of platoon splitting and merging. We are, therefore, motivated to propose a co-design framework for vehicular platoons that maintains both the compositionality of the controller and the string stability of the platoon, which enables the merging and splitting of the vehicles in a platoon. To this end, we first formulate the co-design problem as a centralized linear matrix inequality (LMI) problem and then decompose it using Sylvester's criterion to obtain a set of smaller decentralized LMI problems that can be solved sequentially at individual vehicles in the platoon. Moreover, in the formulated decentralized LMI problems, we encode a specifically derived local LMI to enforce the $L_2$ stability of the closed-loop platooning system, further implying the $L_2$ weak string stability of the vehicular platoon. Finally, to validate the proposed co-design method and its features in terms of merging/splitting, we provide an extensive collection of simulation results generated from a specifically developed simulation framework. Available in GitHub: HTTP://github.com/NDzsong2/Longitudinal-Vehicular-Platoon-Simulator.git that we have made publicly available., Comment: 16 pages, 14 figures, one manuscript has been submitted to Automatica

Symbolic control problems aim to synthesize control policies for dynamical systems under complex temporal specifications. For such problems, Signal Temporal Logic (STL) is increasingly used as the formal specification language due to its rich expressiveness. Moreover, the degree of satisfaction of STL specifications can be evaluated using ``STL robust semantics'' as a scalar robustness measure. This capability of STL enables transforming a symbolic control problem into an optimization problem that optimizes the corresponding robustness measure. However, since these robustness measures are non-smooth and non-convex, exact solutions can only be computed using computationally inefficient mixed-integer programming techniques that do not scale well. Therefore, recent literature has focused on using smooth approximations of these robustness measures to apply scalable and computationally efficient gradient-based methods to find local optima solutions. In this paper, we first generalize two recently established smooth robustness measures (SRMs) and two new ones and discuss their strengths and weaknesses. Next, we propose ``STL error semantics'' to characterize the approximation errors associated with different SRMs under different parameter configurations. This allows one to sensibly select an SRM (to optimize) along with its parameter values. We then propose ``STL gradient semantics'' to derive explicit gradients of SRMs leading to improve computational efficiency as well as accuracy compared to when using numerically estimated gradients. Finally, these contributions are highlighted using extensive simulation results., Comment: To be submitted to ACC 2024 and TAC

In this paper, we consider networked systems comprised of interconnected sets of linear subsystems and propose a decentralized and compositional approach to stabilize or dissipativate such linear networked systems via optimally modifying some existing interconnections and/or creating entirely new interconnections. We also extend this interconnection topology synthesis approach to ensure the ability to stabilize or dissipativate such linear networked systems under distributed (local) feedback control. To the best of the authors' knowledge, this is the first work that attempts to address the optimal interconnection topology synthesis problem for linear networked systems. The proposed approach in this paper only involves solving a sequence of linear matrix inequality problems (one at each subsystem). Thus, using standard convex optimization toolboxes, it can be implemented efficiently and scalably in a decentralized and compositional manner. Apart from many generic linear networked systems applications (e.g., power grid control), a unique application for the proposed interconnection topology synthesis approach is in generating random stable (or dissipative, stabilizable, dissipativate-able) linear networked systems for simulation purposes. We also include an interesting case study where the proposed interconnection topology synthesis approach is compared with an alternative approach that only uses dissipativity information of the involved subsystems., Comment: A preliminary version of this paper is to be presented at the 31st Mediterranean Conference on Control and Automation 2023 (Limassol, Cyprus)

In this paper, we develop centralized and decentralized techniques for analyzing and synthesizing networked systems comprised of interconnected sets of non-linear subsystems - only using the subsystem dissipativity properties. In particular, this paper extends a recent work that proposed dissipativity based centralized analysis techniques for non-linear networked systems as linear matrix inequality (LMI) problems. First, we consider four networked system configurations (NSCs) of interest and provide centralized stability/dissipativity \emph{analysis} techniques for them as LMI problems. Second, we show that the centralized interconnection topology \emph{synthesis} techniques for these NSCs can also be developed as LMI problems. This enables synthesizing the interconnection topology among the subsystems so that specific stability/dissipativity measures of the networked system are optimized. Next, we show that the proposed analysis and synthesis techniques can be implemented in a decentralized and compositional manner (i.e., subsystems can be added/removed conveniently). Finally, we include several numerical results to demonstrate our contributions., Comment: To be submitted to ACC 2023

In this paper, we consider the problem of platooning control with mismatched disturbances using the distributed adaptive backstepping method. The main challenges are: (1) maintaining the compositionality and the distributed nature of the controller, and (2) ensuring the robustness of the controller with respect to general types of disturbances. To address these challenges, we first propose a novel notion that we named "Vector String Lyapunov Function", whose existence implies l2 weak string stability. This notion is based on the vector Lyapunov function-based stability analysis, which depends on the input-to-state-stability of a comparison system. Using this notion, we propose an adaptive backstepping controller for the platoon such that the compositionality and the distributed nature of the controller can be ensured while the internal stability and string stability of the closed-loop system are formally guaranteed. Finally, simulation examples are provided to illustrate the effectiveness of the proposed control algorithm. In particular, we provide simulation results comparing our proposed control algorithm with a recently proposed control algorithm from the literature, under two types of information flow topologies and disturbances., Comment: 11 pages, 18 figures, 1 table to be submitted to CSL/ACC 2023

We consider the problem of on-line evaluation of critical characteristic parameters such as the L_2-gain (L2G), input feedforward passivity index (IFP) and output feedback passivity index (OFP) of non-linear systems using their input-output data. Typically, having an accurate measure of such "system indices" enables the application of systematic control design techniques. Moreover, if such system indices can efficiently be evaluated on-line, they can be exploited to device intelligent controller reconfiguration and fault-tolerant control techniques. However, the existing estimation methods of such system indices (i.e., L2G, IFP and OFP) are predominantly off-line, computationally inefficient, and require a large amount of actual or synthetically generated input-output trajectory data under some specific initial/terminal conditions. On the other hand, the existing on-line estimation methods take an averaging-based approach, which may be sub-optimal, computationally inefficient and susceptible to estimate saturation. In this paper, to overcome these challenges (in the on-line estimation of system indices), we establish and exploit several interesting theoretical results on a particular class of fractional function optimization problems. For comparison purposes, the details of an existing averaging-based approach are provided for the same on-line estimation problem. Finally, several numerical examples are discussed to demonstrate the proposed on-line estimation approach and to highlight our contributions., Comment: Submitted to the CDC 2022

Piecewise affine (PWA) systems are widely applied in many practical cases such as the control of nonlinear systems and hybrid dynamics. However, most of the existing PWA control methods have poor scalability with respect to the number of modes and system dimensions and may not be robust to the disturbances in performance. In this paper, we present a robust approximate simulation based control method for PWA systems under bounded external disturbances. First, a lower-dimensional linear system (abstraction) and an associated interface are designed to enable the output of the PWA system (concrete system) to track the output of the abstraction. Then, a Lyapunov-like simulation function is designed to show the boundedness of the output errors between the two systems. Furthermore, the results obtained for linear abstraction are extended to the case that a simpler PWA system is the abstraction. To illustrate the effectiveness of the proposed approach, simulation results are provided for two design examples., Comment: 8 pages, 7 figures, 2022 American Control Conference extension

The event-triggered control problem over lossy communication networks is addressed in this paper. Although packet dropouts have been considered in the implementation of event-triggered controllers, the assumption of protocols that employ acknowledgement messages persists. This paper provides an approach that relaxes such assumption. An event-based controller is implemented at the sensor node of the networked and uncertain system and it transmits feedback measurements to the controller node at asynchronous time instants. The transmitted packets of information are subject to dropouts by the lossy network. We show that the uncertain system can be asymptotically stabilized, that a positive minimum inter-event time exists, and that the proposed approach does not require acknowledgement messages., Comment: 10 pages, 3 figures

Analysis and resilient design of Cyber-physical Systems have greatly benefited from energy based concepts of passivity and dissipativity. Recently, there has been much research devoted to the use of passivity indices in different components of Cyber-physical systems. Passivity indices are measures of passivity, indicating how passive a system is or how far is it from being passive and generalize passivity based methods to systems that might not be passive. In this paper, we will review recent advances in the use of passivity indices in Cyber-physical systems. We will overview how the indices have been defined and applied to different components of Cyber-physical systems and how they are used in the resilient design of compositional Cyber-physical systems., Comment: 9 pages

This paper presents a new data-driven fault identification and controller reconfiguration algorithm. The presented algorithm relies only on the system's input and output data, and it does not require a detailed system description. The proposed algorithm detects changes in the input-output behavior of the system, whether due to faults or malicious attacks and then reacts by reconfiguring the existing controller. This method does not identify the internal structure of the system nor the extent and nature of the attack; hence it can quickly react to faults and attacks. The proposed method can be readily applied to various applications without significant modifications or tuning, as demonstrated by the examples in the paper., Comment: 8 pages, 7 figures

In this paper, we will discuss how operational limitations affect input-output behaviours of the system. In particular, we will provide formulations for passivity and passivity indices of a nonlinear system given operational limitations on the input and state variables. This formulation is presented in the form of local passivity and indices. We will provide optimisation based formulation to derive passivity properties of the system through polynomial approximations. Two different approaches are taken to approximate the nonlinear dynamics of a system through polynomial functions; namely, Taylor's theorem and a multivariate generalisation of Bernstein polynomials. For each approach, conditions for stability, dissipativity, and passivity of a system, as well as methods to find its passivity indices, are given. Two different methods are also presented to reduce the size of the optimisation problem in Taylor's theorem approach. Examples are provided to show the applicability of the results.

Experimental determination of protein function is resource-consuming. As an alternative, computational prediction of protein function has received attention. In this context, protein structural classification (PSC) can help, by allowing for determining structural classes of currently unclassified proteins based on their features, and then relying on the fact that proteins with similar structures have similar functions. Existing PSC approaches rely on sequence-based or direct 3-dimensional (3D) structure-based protein features. In contrast, we first model 3D structures of proteins as protein structure networks (PSNs). Then, we use network-based features for PSC. We propose the use of graphlets, state-of-the-art features in many research areas of network science, in the task of PSC. Moreover, because graphlets can deal only with unweighted PSNs, and because accounting for edge weights when constructing PSNs could improve PSC accuracy, we also propose a deep learning framework that automatically learns network features from weighted PSNs. When evaluated on a large set of ~9,400 CATH and ~12,800 SCOP protein domains (spanning 36 PSN sets), our proposed approaches are superior to existing PSC approaches in terms of accuracy, with comparable running time.

This work focuses on the invariance of important properties between continuous and discrete models of systems which can be useful in the control design of large-scale systems and their software implementations. In particular, this paper discusses the relationships between the QSR dissipativity of a continuous state dynamical system and of its abstractions obtained through approximate input-output simulation relations. First, conditions to guarantee the dissipativity of the continuous system from its abstractions are provided. The reverse problem of determining the Q, S and R dissipativity matrices of the abstract system from that of the continuous system is also considered. Results characterizing the change in the dissipativity matrices are provided when the system abstraction is obtained. Since, under certain conditions, QSR dissipative systems are known to be stable, the results of this paper can be used to construct stable system abstractions as well. In the second part of this paper, we analyze the dissipativity of the approximate feedback composition of a continuous dynamical system and a discrete controller. We present illustrative examples to demonstrate the results of this paper., Comment: Submitted to SIAM Journal on Control and Optimization

In this paper, we show synchronization for a group of output passive agents that communicate with each other according to an underlying communication graph to achieve a common goal. We propose a distributed event-triggered control framework that will guarantee synchronization and considerably decrease the required communication load on the band-limited network. We define a general Byzantine attack on the event-triggered multi-agent network system and characterize its negative effects on synchronization. The Byzantine agents are capable of intelligently falsifying their data and manipulating the underlying communication graph by altering their respective control feedback weights. We introduce a decentralized detection framework and analyze its steady-state and transient performances. We propose a way of identifying individual Byzantine neighbors and a learning-based method of estimating the attack parameters. Lastly, we propose learning-based control approaches to mitigate the negative effects of the adversarial attack.

This paper summarizes important results useful for controller design of multi-input multi-output systems. The main goal is to characterize the stabilizing controllers that provide a desired response., Comment: 5 pages, 5 figures

We propose a formal design framework for synthesizing coordination and control policies for cooperative multi-agent systems to accomplish a global mission. The global performance requirements are specified as regular languages while dynamics of each agent as well as the shared environment are characterized by finite automata, upon on which a formal design approach is carried out via divide-and-conquer. Specifically, the global mission is decomposed into local tasks; and local mission supervisors are designed to accomplish these local tasks while maintaining the multi-agent performance by integrating supervisor synthesis with compositional verification techniques; finally, motion plans are automatically synthesized based on the obtained mission plans. We present three modifications of the L* learning algorithm such that they are adapted for the synthesis of the local mission supervisors, the compositional verification and the synthesis of local motion plans, to guarantee that the collective behavior of the agents will ensure the satisfaction of the global specification. Furthermore, the effectiveness of the proposed framework is demonstrated by a detailed experimental study based on the implementation of a multi-robot coordination scenario. The proposed hardware-software architecture, with each robot's communication and localization capabilities, is exploited to examine the automatic supervisor synthesis with inter-robot communication., Comment: 16 pages, 23 figures, 1 table

In this report, we introduce a comprehensive design framework for Event-Triggered Networked Control Systems based on the passivity-based concept of Input Feed-Forward Output Feedback Passive (IF-OFP) systems. Our approach is comprehensive in the sense that we show finite-gain $L_2$-stability and robustness for the networked control system by considering the effects of time-varying or constant network induced delays, signal quantizations, and data losses in communication links from the plant to controller and the controller to plant. Our design is based on the need for a more efficient utilization of band-limited shared communication networks which is a necessity for the design of Large-Scale Cyber-Physical systems. To achieve this, we introduce simple triggering conditions that do not require the exact knowledge of the sub-systems and are located on both sides of the communication network: the plant's output and the controller's output. This specifically leads to a great decrease in the communication rate between the controller and plant. Additionally, we show lower-bounds on inter-event time intervals for the triggering conditions and show the design's robustness against external noise and disturbance. We illustrate the relationship amongst stability, robustness and passivity levels for the plant and controller. We analyze our design's robustness against packet dropouts and loss of communication. Our results are design-oriented in the sense that based on our proposed framework, the designer can easily observe the trade-offs amongst different components of the networked control system, time-varying delays, effects of signal quantizations and triggering conditions, stability, robustness and performance of networked control system and make design decisions accordingly.

In this report, we apply an input-output transformation passivation method, described in our previous works, to an Adaptive Cruise Control system. We analyze the system's performance under a co-simulation framework that makes use of an online optimization method called extremum-seeking to achieve the optimized behavior. The matrix for passivation method encompasses commonly used methods of series, feedback and feed-forward interconnections for passivating the system. We have previously shown that passivity levels can be guaranteed for a system using our passivation method. In this work, an extremum-seeking algorithm was used to determine the passivation parameters. It is known that systems with input-output time-delays are not passive. On the other hand, time-delays are unavoidable in automotive systems and commonly emerge in software implementations and communication units as well as driver's behavior. We show that by using our passivation method, we can passivate the system and improve its overall performance. Our simulation examples in CarSim and Simulink will show that the passive system has a considerably better performance., Comment: 39 pages, 18 figures, Technical Report at the University of Notre Dame, American Control Conference (ACC), 2016

Input feed-forward output feedback passive (IF-OFP) systems define a great number of dynamical systems. In this report, we show that dissipativity and passivity-based control combined with event-triggered networked control systems (NCS) provide a powerful platform for the design of cyber-physical systems (CPS). We propose QSR-dissipativity, passivity and L2 stability conditions for an event-triggered networked control system in three cases where: (i) an input-output event-triggering sampler condition is located on the plant's output side, (ii) an input-output event-triggering sampler condition is located on controller's output side, (iii) input-output event-triggering sampler conditions are located on the outputs of both the plant and controller. We will show that this leads to a large decrease in communicational load amongst sub-units in networked control structures. We show that passivity and stability conditions depend on passivity levels for the plant and controller. Our results also illustrate the trade-off among passivity levels, stability, and system's dependence on the rate of communication between the plant and controller., Comment: 46 pages, 27 figures

In this paper, we consider the problem of quantifying systemic redundancy in reliable systems having multiple controllers with overlapping functionality. In particular, we consider a multi-channel system with multi-controller configurations -- where controllers are required to respond optimally, in the sense of best-response correspondence, a {\it reliable-by-design} requirement, to non-faulty controllers so as to ensure or maintain some system properties. Here we introduce a mathematical framework, based on the notion of relative entropy of probability measures associated with steady-state solutions of Fokker-Planck equations for a family of stochastically perturbed multi-channel systems, that provides useful information towards a systemic assessment of redundancy in the system., Comment: 9 Pages

In this paper, we consider an expanding construction of a distributed control system, which is obtained by adding a new subsystem one after the other, until all $n$ subsystems, where $n \ge 2$, are included in the distributed control system. It is assumed that a small random perturbation enters only into the first subsystem and is then subsequently transmitted to the other subsystems. Moreover, for any $\ell \in \{2, ..., n\}$, the distributed control system, compatible with the expanding construction, which is obtained from the first $\ell$ subsystems, satisfies an appropriate H\"{o}rmander condition. As a result of this, the diffusion process is degenerate, i.e., the backward operator associated with it is a degenerate parabolic equation. Our main interest here is to prevent the diffusion process (that corresponds to a particular subsystem) from leaving a given bounded open domain. In particular, we consider a risk-sensitive version of the mean escape time criterion with respect to each of the subsystems. Using a variational representation, we characterize the risk-sensitive escape control for the diffusion process as the lower and upper values of an associated stochastic differential game. Finally, we comment on the implication of our results, where one is also interested in evaluating the performance of the risk-sensitive escape control, when there is some modeling error in the distributed control system., Comment: 11 Pages (Additional Note: This work is, in some sense, a continuation of our previous paper arXiv:1409.2751 [math.DS])

In this paper, we consider the problem of minimizing the exit rate with which a diffusion process pertaining to a chain of distributed control systems, with random perturbations, exits from a given bounded open domain. In particular, we consider a chain of distributed control systems that are formed by $n$ subsystems (with $n \ge 2$), where the random perturbation enters only in the first subsystem and is then subsequently transmitted to the other subsystems. Furthermore, we assume that, for any $\ell \in \{2, \ldots, n\}$, the distributed control systems, which is formed by the first $\ell$ subsystems, satisfies an appropriate H\"ormander condition. As a result of this, the diffusion process is degenerate, in the sense that the infinitesimal generator associated with it is a degenerate parabolic equation. Our interest is to establish a connection between the minimum exit rate with which the diffusion process exits from the given domain and the principal eigenvalue for the infinitesimal generator with zero boundary conditions. Such a connection allows us to derive a family of Hamilton-Jacobi-Bellman equations for which we provide a verification theorem that shows the validity of the corresponding optimal control problems. Finally, we provide an estimate on the attainable exit probability of the diffusion process with respect to a set of admissible (optimal) Markov controls for the optimal control problems., Comment: 12 Pages. (Additional Note: This work is, in some sense, a continuation of our previous paper arXiv:1408.6260.)