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L2 Gain And Passivity Techniques In Nonlinear Control

Cyberphysical systems (CPSs) are new class of engineered systems that offer close interaction between cyber and physical components. The field of CPS has been identified as a key area of research, and CPSs are expected to play a major role in the design and development of future systems. In this paper, we survey recent advancements made in the development and applications of CPSs. We classify the existing research work based on their characteristics and identify the future challenges. We also discuss the examples of prototypes of CPSs. The aim of this survey is to enable researchers and system designers to get insights into the working and applications of CPSs and motivate them to propose novel solutions for making wide-scale adoption of CPS a tangible reality.

Design Techniques and Applications of Cyberphysical Systems: A Survey

System integration is the elephant in the china store of large-scale cyber-physical system (CPS) design. It would be hard to find any other technology that is more undervalued scientifically and at the same time has bigger impact on the presence and future of engineered systems. The unique challenges in CPS integration emerge from the heterogeneity of components and interactions. This heterogeneity drives the need for modeling and analyzing cross-domain interactions among physical and computational/networking domains and demands deep understanding of the effects of heterogeneous abstraction layers in the design flow. To address the challenges of CPS integration, significant progress needs to be made toward a new science and technology foundation that is model based, precise, and predictable. This paper presents a theory of composition for heterogeneous systems focusing on stability. Specifically, the paper presents a passivity-based design approach that decouples stability from timing uncertainties caused by networking and computation. In addition, the paper describes cross-domain abstractions that provide effective solution for model-based fully automated software synthesis and high-fidelity performance analysis. The design objectives demonstrated using the techniques presented in the paper are group coordination for networked unmanned air vehicles (UAVs) and high-confidence embedded control software design for a quadrotor UAV. Open problems in the area are also discussed, including the extension of the theory of compositional design to guarantee properties beyond stability, such as safety and performance.

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Toward a Science of Cyber–Physical System Integration

Cyberphysical systems (CPSs) are perceived as the pivotal enabler for a new era of real-time Internetbased communication and collaboration among value-chain participants, e.g., devices, systems, organizations, and humans. The CPS utilization in industrial settings is expected to revolutionize the way enterprises conduct their business from a holistic viewpoint, i.e., from shop-floor to business interactions, from suppliers to customers, and from design to support across the whole product and service lifecycle. Industrial CPS (ICPSs) blur the fabric of cyber (including business) and physical worlds and kickstart an era of systemwide collaboration and information-driven interactions among all stakeholders of the value chain. Therefore, ICPSs are expected to empower the transformation of industry and business at large to a digital, adaptive, networked, and knowledge-based industry with significant long-term impact on the economy, society, environment, and citizens.

Industrial Cyberphysical Systems: A Backbone of the Fourth Industrial Revolution

Machine-to-machine (M2M) communications emerge to autonomously operate to link interactions between Internet cyber world and physical systems. We present the technological scenario of M2M communications consisting of wireless infrastructure to cloud, and machine swarm of tremendous devices. Related technologies toward practical realization are explored to complete fundamental understanding and engineering knowledge of this new communication and networking technology front.

Machine-to-machine communications: Technologies and challenges

A method to passivate a given system by using an input–output transformation matrix is introduced. This matrix generalizes the commonly used methods of series, feedback, and feedforward to passivate a linear or nonlinear system. Through an appropriate design of this matrix, positive passivity indices can be guaranteed for the system. Furthermore, this transformation matrix allows the use of a nonpassive system as a controller to guarantee the passivity and finite-gain $\mathcal{L}_2$ stability of a negative feedback configuration. The passivation parameters can be selected to improve system performance. The results are illustrated by considering nonlinear systems and linear systems with input/output delay. To validate the theory, simulation results in CarSim and Simulink are presented.

Control Design Using Passivation for Stability and Performance

While designing controllers that guarantee the passivity of a closed loop system has a long history, much less attention has been paid to the situation when the control actions are performed by a human. We consider as an example a human who is driving a car. The behavior of human controllers as drivers has been modeled in the literature as a linear time invariant system cascaded with a time delay. We show that such a human model is not passive. In order to guarantee passivity of a closed loop system with a human controller, we use a passivation method. Through an appropriate design of the passivation parameters, positive passivity indices can be guaranteed for the closed loop system. The passivation parameters can be selected by solving an optimization problem such as minimizing the tracking error. To validate our theory, we provide simulation results in CarSim and Simulink.

On guaranteeing passivity and performance with a human controller

In this paper, we apply an input-output transformation passivation method developed in our previous work to an Adaptive Cruise Control system and analyze the system's performance. A co-simulation framework that makes use of an online optimization method called extremum-seeking is used to determine the passivation parameters. It is known that systems with input-output time-delays are not passive. Additionally, time-delays are unavoidable in automotive systems and commonly emerge in software implementations, communication units, as well as driver's behavior. We show that by using our passivation method, we can passivate a time-delay system and improve its overall performance by using an extremum-seeking co-simulation framework. To validate our work, we present simulation results in CarSim and Simulink.

Passivation and performance optimization using an extremum seeking co-simulation framework with application to Adaptive Cruise Control systems

In this paper, we study system performance in passivity based control designs. In particular, we consider the passivation method of [1], we extend it so to use non-positive passivation parameters and transfer functions, and present results to passivate systems that are not finite-gain stable. The passivation parameters are selected according to non-derivative based optimization methods when the system dynamics are unknown. We show that by tuning the passivation parameters, desired system performance can be achieved in addition to guaranteeing passivity for the system. To validate our results, we present simulations in CarSim/Simulink.

Shige Wang

Papers

Toward a Science of Cyber–Physical System Integration

Control Design Using Passivation for Stability and Performance

On guaranteeing passivity and performance with a human controller

Passivation and performance optimization using an extremum seeking co-simulation framework with application to Adaptive Cruise Control systems

Performance optimization based on passivation of systems with applications to systems with input/output delay