ACM Transactions on Cyber-Physical Systems

Although wireless control is one of the key technologies for future industries, most wireless networks are only used for monitoring. When wireless networks are applied to transmit control commands, the uncertain link qualities and limited network resources may destroy the performance of multi-loop control systems. Hence, it is critical to allocate these resources to optimize the control performance as the network condition changes and plants evolve. This paper presents comprehensive optimal scheduling strategies for wireless control systems based on adaptive dynamic programming. Firstly, we propose an effective adaptive dynamic programming scheduling (ADPS) strategy to solve the optimal scheduling problem based on the single-step control performance at run-time while significantly reducing computational complexity. Moreover, to overcome the ”short-sightedness” of single-step performance prediction, we extend ADPS to ADPS-m ( m ulti-step prediction), which optimizes multi-step performance by incorporating a longer-horizon evolution of the plants. Furthermore, we propose ADPS-H ( H eterogeneous flow scheduling) to support heterogeneous flows with different data rates and sizes, and ADPS-H-m ( m ulti-step prediction for H eterogeneous flow scheduling), which schedules heterogeneous flows in a longer prediction horizon. We prove that all these scheduling strategies can achieve optimality and stability under mild assumptions. Extensive experiments integrating TOSSIM and MATLAB/Simulink are performed to evaluate all of the proposed methods in case studies of four- and ten-loop control systems. The simulation results demonstrate that these strategies can effectively improve the control performance at lower computing costs under both cyber and physical disturbances. Under the noise level of -76 dBm, for the four-loop case, ADPS achieves the same control performance as the linear programming while saving 99.5% of the execution time. ADPS-m further improves the control performance by up to 27.0% compared with ADPS at the prediction horizon of 3, and ADPS-H-m improves the performance by up to 32.3% and 8.4% compared with round-robin and ADPS-H, respectively. And the ten-loop case indicates the effectiveness and scalability of the proposed approaches.

Ruijie Fu

Lancong Guo

An Zou

Cailian Chen

Xinping Guan

Yehan Ma

Comprehensive Optimal Network Scheduling Strategies for Wireless Control Systems

无线控制系统综合优化网络调度策略

Autopilot systems are typically composed of an “inner loop” providing stability and control, whereas an “outer loop” is responsible for mission-level objectives, such as way-point navigation. Autopilot systems for unmanned aerial vehicles are predominately implemented using Proportional-Integral-Derivative (PID) control systems, which have demonstrated exceptional performance in stable environments. However, more sophisticated control is required to operate in unpredictable and harsh environments. Intelligent flight control systems is an active area of research addressing limitations of PID control most recently through the use of reinforcement learning (RL), which has had success in other applications, such as robotics. Yet previous work has focused primarily on using RL at the mission-level controller. In this work, we investigate the performance and accuracy of the inner control loop providing attitude control when using intelligent flight control systems trained with state-of-the-art RL algorithms—Deep Deterministic Policy Gradient, Trust Region Policy Optimization, and Proximal Policy Optimization. To investigate these unknowns, we first developed an open source high-fidelity simulation environment to train a flight controller attitude control of a quadrotor through RL. We then used our environment to compare their performance to that of a PID controller to identify if using RL is appropriate in high-precision, time-critical flight control.

William Koch

Renato Mancuso

Richard West

Azer Bestavros

ACM Trans. Cyber-Phys. Syst.

Reinforcement Learning for UAV Attitude Control

无人机姿态控制的强化学习

Space Cyber-Physical Systems (S-CPS) such as spacecraft and satellites strongly rely on the reliability of onboard computers to guarantee the success of their missions. Relying solely on radiation-hardened technologies is extremely expensive, and developing inflexible architectural and microarchitectural modifications to introduce modular redundancy within a system leads to significant area increase and performance degradation. To mitigate the overheads of traditional radiation hardening and modular redundancy approaches, we present a novel Hybrid Modular Redundancy (HMR) approach, a redundancy scheme that features a cluster of RISC-V processors with a flexible on-demand dual-core and triple-core lockstep grouping of computing cores with runtime split-lock capabilities. Further, we propose two recovery approaches, software-based and hardware-based, trading off performance and area overhead. Running at 430MHz, our fault-tolerant cluster achieves up to 1160MOPS on a matrix multiplication benchmark when configured in non-redundant mode and 617 and 414 MOPS in dual and triple mode, respectively. A software-based recovery in triple mode requires 363 clock cycles and occupies 0.612 mm 2 , representing a 1.3% area overhead over a non-redundant 12-core RISC-V cluster. As a high-performance alternative, a new hardware-based method provides rapid fault recovery in just 24 clock cycles and occupies 0.660 mm 2 , namely ∼ 9.4% area overhead over the baseline non-redundant RISC-V cluster. The cluster is also enhanced with split-lock capabilities to enter one of the available redundant modes with minimum performance loss, allowing execution of a mission-critical portion of code when in independent mode, or a performance section when in a reliability mode, with &lt;400 clock cycles overhead for entry and exit. The proposed system is the first to integrate these functionalities on an open-source RISC-V-based compute device, enabling finely tunable reliability vs. performance trade-offs.

Michael Rogenmoser

Yvan Tortorella

Davide Rossi

Francesco Conti

Luca Benini

Hybrid Modular Redundancy: Exploring Modular Redundancy Approaches in RISC-V Multi-Core Computing Clusters for Reliable Processing in Space

混合模块冗余：探索RISC-V多核计算集群中的模块冗余方法以实现空间可靠处理

Abstract Cyber resilience is the ability of a system to resist and recover from a cyber attack, thereby restoring the system's functionality. Effective design and development of a cyber resilient system requires experimental methods and tools for quantitative measuring of cyber resilience. This paper describes an experimental method and test bed for obtaining resilience-relevant data as a system (in our case – a truck) traverses its route, in repeatable, systematic experiments. We model a truck equipped with an autonomous cyber-defense system and which also includes inherent physical resilience features. When attacked by malware, this ensemble of cyber-physical features (i.e., “bonware”) strives to resist and recover from the performance degradation caused by the malware's attack. We propose parsimonious mathematical models to aid in quantifying systems’ resilience to cyber attacks. Using the models, we identify quantitative characteristics obtainable from experimental data, and show that these characteristics can serve as useful quantitative measures of cyber resilience.

Michael J. Weisman

Alexander Kott

Jason E. Ellis

Brian J. Murphy

Travis W. Parker

Sidney Smith

Joachim Vandekerckhove

Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

网络弹性定量测量：建模与实验

Recent work has considered personalized route planning based on user profiles, but none of it accounts for human trust. We argue that human trust is an important factor to consider when planning routes for automated vehicles. This article presents a trust-based route-planning approach for automated vehicles. We formalize the human-vehicle interaction as a partially observable Markov decision process (POMDP) and model trust as a partially observable state variable of the POMDP, representing the human’s hidden mental state. We build data-driven models of human trust dynamics and takeover decisions, which are incorporated in the POMDP framework, using data collected from an online user study with 100 participants on the Amazon Mechanical Turk platform. We compute optimal routes for automated vehicles by solving optimal policies in the POMDP planning and evaluate the resulting routes via human subject experiments with 22 participants on a driving simulator. The experimental results show that participants taking the trust-based route generally reported more positive responses in the after-driving survey than those taking the baseline (trust-free) route. In addition, we analyze the trade-offs between multiple planning objectives (e.g., trust, distance, energy consumption) via multi-objective optimization of the POMDP. We also identify a set of open issues and implications for real-world deployment of the proposed approach in automated vehicles.

Shili Sheng

Erfan Pakdamanian

Kyungtae Han

Ziran Wang

John Lenneman

David Parker

Lu Feng

Planning for Automated Vehicles with Human Trust

自动化车辆的人类信任规划

This paper introduces a slip-aware networked vehicle model and proposes an adaptive time-delay control framework for connected autonomous driving systems’ cooperative adaptive cruise control and safety of the intended functionality. In order to improve the vehicular network safety by conveying the amount of longitudinal slip ratio along with the vehicle kinematic states, the innovative slip-aware model makes use of an auxiliary state variable representation that includes wheel slips. The proposed framework enables the formation of platoons consisting of vehicles from multiple manufacturers with similar dynamics, with each vehicle requiring state measurements and longitudinal slip information only from its preceding vehicle. To ensure robustness against external disturbances and model uncertainties, an artificial time-delayed control-based technique is implemented to control the entire networked vehicle system. In order to achieve disturbance rejection along the string of vehicles, control protocols have to be designed to ensure string stability of the whole vehicle platoon. The robust law is augmented with a dual-rate adaption law in order to tackle the over estimation and under estimation problem of switching gain. Subsequently, Lyapunov stability analysis is conducted to show that the inter-vehicular states are steered within a small region in the neighborhood of the origin, under the proposed adaptive-robust control scheme. Numerical simulations are also carried out to validate the robustness of the developed distributed control framework.

Rajasree Sarkar

Arunava Banerjee

Ehsan Hashemi

Adaptive Time-Delay Control for Cooperative Platooning Considering Slip

考虑滑移的协同编队自适应时延控制

The increasing ubiquity of material-extrusion-based additive manufacturing is motivating cybersecurity researchers to explore its offensive and defensive landscape. Being a physical system, 3D printers have non-zero tolerance specifications for precision and trueness parameters. While a single-bit change in a digital data file is sufficient to fail its integrity and is easily detected through methods such as hashing, the printing process (and subsequently the printed object) remains compliant within the tolerance zone. This study systematically analyzes the material extrusion process and identifies four attack opportunities where low-magnitude kinetic cyberattacks exploit the physical process compliance zone to sabotage the printed part’s mechanical properties. The attacks are demonstrated on ASTM-compliant tensile and flexure bars through a man-in-the-middle attack scenario by hijacking the network layer communication between the 3D printer and the printer control machine. The physically stealthy attacks did not produce any evident deformation in the parts’ dimensions and mass, while the destructive tests confirm that they are still effective in modifying the tensile and bending strength by up to 25%. The effectiveness of the attacks in bypassing the defenses is assessed by implementing one of the leading detection schemes described in the current literature. The attacks were either not detected at all or detected with a significantly high false negative rate at various attack magnitudes.

Muhammad Haris Rais

Muhammad Ahsan

Irfan Ahmed

Sabotaging material extrusion-based 3D printed parts through low-magnitude kinetic manipulation attacks

通过低幅度动力操纵攻击破坏基于材料挤出的3D打印部件

Cyber-physical systems (CPS), robotics, the Internet of Things (IoT), and automotive systems are integral to modern technology. They are characterized by their safety criticality, accuracy, and real-time control requirements. Control software plays a crucial role in achieving these objectives by managing and coordinating the operations of various sub-systems. This paper presents a novel systematic mapping study (SMS) for control software engineering, analyzing 115 peer-reviewed papers. The study identifies, classifies, and maps existing solutions, providing a comprehensive and structured overview for practitioners and researchers. Our contributions include (i) a unique classification of literature into six research themes—engineering phases, engineering approaches, engineering paradigms, engineering artefacts, target application domains, and engineering concerns; (ii) insights into the specificity of approaches to target technologies and phases; (iii) the prominence of model-driven approaches for design and testing; (iv) the lack of end-to-end engineering support in existing approaches; and (v) the emerging role of agile-based methods versus the dominance of waterfall-based methods. This paper’s significance lies in its thorough analysis and the high-level mapping of the solution space, offering new perspectives and a detailed roadmap for future research and innovation in control software engineering. The findings will guide advancements and best practices in the field, underscoring the paper’s impact.

Amar Banerjee

Venkatesh Choppella

Control Software Engineering Approaches for Cyber-Physical Systems: A Systematic Mapping Study

网络物理系统控制软件工程方法：系统映射研究

Contract-based design is a method to facilitate modular design of systems. While there has been substantial progress on the theory of contracts, there has been less progress on practical algorithms for the algebraic operations in the theory. In this paper, we present 1) principles to implement a contract-based design tool at scale and 2) Pacti, a tool that can efficiently compute these operations. We illustrate the use of Pacti in a variety of case studies.

Inigo Incer

Apurva Badithela

Josefine B. Graebener

Piergiuseppe Mallozzi

Ayush Pandey

Nicolas Rouquette

Sheng-Jung Yu

Albert Benveniste

Benoit Caillaud

Richard M. Murray

Alberto Sangiovanni-Vincentelli

Sanjit A. Seshia

Pacti: Assume-Guarantee Contracts for Efficient Compositional Analysis and Design

Pacti：用于高效组合分析与设计的假设-保证契约

短名	ACM Trans. Cyber-Phys. Syst.
Journal Impact	2.12
国际分区	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS(Q3)

ISSN	2378-962X, 2378-9638
h-index	23

涉及主题	计算机科学工程类操作系统数学物理人工智能计算机安全程序设计语言生物量子力学经济计算机网络热力学地理电信信息物理系统分布式计算统计电气工程法学政治学管理实时计算生态学
出版信息	出版商: Association for Computing Machinery (ACM)，出版周期: ，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 2017，原创研究文献占比: 97.06%，自引率:5.00%， Gold OA占比: 3.85%

ACM Transactions on Cyber-Physical Systems

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Comprehensive Optimal Network Scheduling Strategies for Wireless Control Systems

Reinforcement Learning for UAV Attitude Control

Hybrid Modular Redundancy: Exploring Modular Redundancy Approaches in RISC-V Multi-Core Computing Clusters for Reliable Processing in Space

Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

Planning for Automated Vehicles with Human Trust

Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

Adaptive Time-Delay Control for Cooperative Platooning Considering Slip

Sabotaging material extrusion-based 3D printed parts through low-magnitude kinetic manipulation attacks

Control Software Engineering Approaches for Cyber-Physical Systems: A Systematic Mapping Study

Pacti: Assume-Guarantee Contracts for Efficient Compositional Analysis and Design