183,247 research outputs found
Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems
We consider the problem of allocating radio resources over wireless
communication links to control a series of independent wireless control
systems. Low-latency transmissions are necessary in enabling time-sensitive
control systems to operate over wireless links with high reliability. Achieving
fast data rates over wireless links thus comes at the cost of reliability in
the form of high packet error rates compared to wired links due to channel
noise and interference. However, the effect of the communication link errors on
the control system performance depends dynamically on the control system state.
We propose a novel control-communication co-design approach to the low-latency
resource allocation problem. We incorporate control and channel state
information to make scheduling decisions over time on frequency, bandwidth and
data rates across the next-generation Wi-Fi based wireless communication links
that close the control loops. Control systems that are closer to instability or
further from a desired range in a given control cycle are given higher packet
delivery rate targets to meet. Rather than a simple priority ranking, we derive
precise packet error rate targets for each system needed to satisfy stability
targets and make scheduling decisions to meet such targets while reducing total
transmission time. The resulting Control-Aware Low Latency Scheduling (CALLS)
method is tested in numerous simulation experiments that demonstrate its
effectiveness in meeting control-based goals under tight latency constraints
relative to control-agnostic scheduling
Cyber-Physical Co-Design of Wireless Control Systems
Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption in process industries because of its advantages in lowering deployment and maintenance cost in challenging environments. While early success of industrial WSANs has been recognized, significant potential remains in exploring WSANs as unified networks for industrial plants.
This thesis research explores a cyber-physical co-design approach to design wireless control systems. To enable holistic studies of wireless control systems, we have developed the Wireless Cyber-Physical Simulator (WCPS), an integrated co-simulation environment that integrates Simulink and our implementation of WSANs based on the industrial WirelessHART standard. We further develop novel WSAN protocols tailored for advanced control designs for networked control systems. WCPS now works as the first simulator that features both linear and nonlinear physical plant models, state-of-art WirelessHART protocol stack, and realistic wireless network characteristics. A realistic wireless structural control study sheds light on the challenges of WSC and the limitations of a traditional structural control approach under realistic wireless conditions. Systematic emergency control results demonstrate that our real-time emergency communication approach enables timely emergency handling, while allowing regular feedback control loops to effectively share resources in WSANs during normal operations. A co-joint study of wireless routing and control highlights the importance of the co-design approach of wireless networks and control
Design and Real-World Evaluation of Dependable Wireless Cyber-Physical Systems
The ongoing effort for an efficient, sustainable, and automated interaction between humans, machines, and our environment will make cyber-physical systems (CPS) an integral part of the industry and our daily lives. At their core, CPS integrate computing elements, communication networks, and physical processes that are monitored and controlled through sensors and actuators. New and innovative applications become possible by extending or replacing static and expensive cable-based communication infrastructures with wireless technology. The flexibility of wireless CPS is a key enabler for many envisioned scenarios, such as intelligent factories, smart farming, personalized healthcare systems, autonomous search and rescue, and smart cities.
High dependability, efficiency, and adaptivity requirements complement the demand for wireless and low-cost solutions in such applications. For instance, industrial and medical systems should work reliably and predictably with performance guarantees, even if parts of the system fail. Because emerging CPS will feature mobile and battery-driven devices that can execute various tasks, the systems must also quickly adapt to frequently changing conditions. Moreover, as applications become ever more sophisticated, featuring compact embedded devices that are deployed densely and at scale, efficient designs are indispensable to achieve desired operational lifetimes and satisfy high bandwidth demands.
Meeting these partly conflicting requirements, however, is challenging due to imperfections of wireless communication and resource constraints along several dimensions, for example, computing, memory, and power constraints of the devices. More precisely, frequent and correlated message losses paired with very limited bandwidth and varying delays for the message exchange significantly complicate the control design. In addition, since communication ranges are limited, messages must be relayed over multiple hops to cover larger distances, such as an entire factory. Although the resulting mesh networks are more robust against interference, efficient communication is a major challenge as wireless imperfections get amplified, and significant coordination effort is needed, especially if the networks are dynamic.
CPS combine various research disciplines, which are often investigated in isolation, ignoring their complex interaction. However, to address this interaction and build trust in the proposed solutions, evaluating CPS using real physical systems and wireless networks paired with formal guarantees of a system’s end-to-end behavior is necessary. Existing works that take this step can only satisfy a few of the abovementioned requirements. Most notably, multi-hop communication has only been used to control slow physical processes while providing no guarantees. One of the reasons is that the current communication protocols are not suited for dynamic multi-hop networks.
This thesis closes the gap between existing works and the diverse needs of emerging wireless CPS. The contributions address different research directions and are split into two parts. In the first part, we specifically address the shortcomings of existing communication protocols and make the following contributions to provide a solid networking foundation:
• We present Mixer, a communication primitive for the reliable many-to-all message exchange in dynamic wireless multi-hop networks. Mixer runs on resource-constrained low-power embedded devices and combines synchronous transmissions and network coding for a highly scalable and topology-agnostic message exchange. As a result, it supports mobile nodes and can serve any possible traffic patterns, for example, to efficiently realize distributed control, as required by emerging CPS applications.
• We present Butler, a lightweight and distributed synchronization mechanism with formally guaranteed correctness properties to improve the dependability of synchronous transmissions-based protocols. These protocols require precise time synchronization provided by a specific node. Upon failure of this node, the entire network cannot communicate. Butler removes this single point of failure by quickly synchronizing all nodes in the network without affecting the protocols’ performance.
In the second part, we focus on the challenges of integrating communication and various control concepts using classical time-triggered and modern event-based approaches. Based on the design, implementation, and evaluation of the proposed solutions using real systems and networks, we make the following contributions, which in many ways push the boundaries of previous approaches:
• We are the first to demonstrate and evaluate fast feedback control over low-power wireless multi-hop networks. Essential for this achievement is a novel co-design and integration of communication and control. Our wireless embedded platform tames the imperfections impairing control, for example, message loss and varying delays, and considers the resulting key properties in the control design. Furthermore, the careful orchestration of control and communication tasks enables real-time operation and makes our system amenable to an end-to-end analysis. Due to this, we can provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics.
• We propose control-guided communication, a novel co-design for distributed self-triggered control over wireless multi-hop networks. Self-triggered control can save energy by transmitting data only when needed. However, there are no solutions that bring those savings to multi-hop networks and that can reallocate freed-up resources, for example, to other agents. Our control system informs the communication system of its transmission demands ahead of time so that communication resources can be allocated accordingly. Thus, we can transfer the energy savings from the control to the communication side and achieve an end-to-end benefit.
• We present a novel co-design of distributed control and wireless communication that resolves overload situations in which the communication demand exceeds the available bandwidth. As systems scale up, featuring more agents and higher bandwidth demands, the available bandwidth will be quickly exceeded, resulting in overload. While event-triggered control and self-triggered control approaches reduce the communication demand on average, they cannot prevent that potentially all agents want to communicate simultaneously. We address this limitation by dynamically allocating the available bandwidth to the agents with the highest need. Thus, we can formally prove that our co-design guarantees closed-loop stability for physical systems with stochastic linear time-invariant dynamics.:Abstract
Acknowledgements
List of Abbreviations
List of Figures
List of Tables
1 Introduction
1.1 Motivation
1.2 Application Requirements
1.3 Challenges
1.4 State of the Art
1.5 Contributions and Road Map
2 Mixer: Efficient Many-to-All Broadcast in Dynamic Wireless Mesh Networks
2.1 Introduction
2.2 Overview
2.3 Design
2.4 Implementation
2.5 Evaluation
2.6 Discussion
2.7 Related Work
3 Butler: Increasing the Availability of Low-Power Wireless Communication Protocols
3.1 Introduction
3.2 Motivation and Background
3.3 Design
3.4 Analysis
3.5 Implementation
3.6 Evaluation
3.7 Related Work
4 Feedback Control Goes Wireless: Guaranteed Stability over Low-Power Multi-Hop Networks
4.1 Introduction
4.2 Related Work
4.3 Problem Setting and Approach
4.4 Wireless Embedded System Design
4.5 Control Design and Analysis
4.6 Experimental Evaluation
4.A Control Details
5 Control-Guided Communication: Efficient Resource Arbitration and Allocation in Multi-Hop Wireless Control Systems
5.1 Introduction
5.2 Problem Setting
5.3 Co-Design Approach
5.4 Wireless Communication System Design
5.5 Self-Triggered Control Design
5.6 Experimental Evaluation
6 Scaling Beyond Bandwidth Limitations: Wireless Control With Stability Guarantees Under Overload
6.1 Introduction
6.2 Problem and Related Work
6.3 Overview of Co-Design Approach
6.4 Predictive Triggering and Control System
6.5 Adaptive Communication System
6.6 Integration and Stability Analysis
6.7 Testbed Experiments
6.A Proof of Theorem 4
6.B Usage of the Network Bandwidth for Control
7 Conclusion and Outlook
7.1 Contributions
7.2 Future Directions
Bibliography
List of Publication
Decoding the `Nature Encoded\u27 Messages for Wireless Networked Control Systems
Because of low installation and reconfiguration cost wireless communication has been widely applied in networked control system (NCS). NCS is a control system which uses multi-purpose shared network as communication medium to connect spatially distributed components of control system including sensors, actuator, and controller. The integration of wireless communication in NCS is challenging due to channel unreliability such as fading, shadowing, interference, mobility and receiver thermal noise leading to packet corruption, packet dropout and packet transmission delay. In this dissertation, the study is focused on the design of wireless receiver in order to exploit the redundancy in the system state, which can be considered as a `nature encoding\u27 for the messages. Firstly, for systems with or without explicit channel coding, a decoding procedures based on Pearl\u27s Belief Propagation (BP), in a similar manner to Turbo processing in traditional data communication systems, is proposed to exploit the redundancy in the system state. Numerical simulations have demonstrated the validity of the proposed schemes, using a linear model of electric generator dynamic system. Secondly, we propose a quickest detection based scheme to detect error propagation, which may happen in the proposed decoding scheme when channel condition is bad. Then we combine this proposed error propagation detection scheme with the proposed BP based channel decoding and state estimation algorithm. The validity of the proposed schemes has been shown by numerical simulations. Finally, we propose to use MSE-based transfer chart to evaluate the performance of the proposed BP based channel decoding and state estimation scheme. We focus on two models to evaluate the performance of BP based sequential and iterative channel decoding and state estimation. The numerical results show that MSE-based transfer chart can provide much insight about the performance of the proposed channel decoding and state estimation scheme.
In this dissertation, the study is focused on the design of wireless receiver in order to exploit the redundancy in the system state, which can be considered as a `nature encoding\u27 for the messages. Firstly, for systems with or without explicit channel coding, a decoding procedures based on Pearl\u27s Belief Propagation (BP), in a similar manner to Turbo processing in traditional data communication systems, is proposed to exploit the redundancy in the system state. Numerical simulations have demonstrated the validity of the proposed schemes, using a linear model of electric generator dynamic system.
Secondly, we propose a quickest detection based scheme to detect error propagation, which may happen in the proposed decoding scheme when channel condition is bad. Then we combine this proposed error propagation detection scheme with the proposed BP based channel decoding and state estimation algorithm. The validity of the proposed schemes has been shown by numerical simulations.
Finally, we propose to use MSE-based transfer chart to evaluate the performance of the proposed BP based channel decoding and state estimation scheme. We focus on two models to evaluate the performance of BP based sequential and iterative channel decoding and state estimation. The numerical results show that MSE-based transfer chart can provide much insight about the performance of the proposed channel decoding and state estimation scheme
Wireless Information Transfer with Opportunistic Energy Harvesting
Energy harvesting is a promising solution to prolong the operation of
energy-constrained wireless networks. In particular, scavenging energy from
ambient radio signals, namely wireless energy harvesting (WEH), has recently
drawn significant attention. In this paper, we consider a point-to-point
wireless link over the narrowband flat-fading channel subject to time-varying
co-channel interference. It is assumed that the receiver has no fixed power
supplies and thus needs to replenish energy opportunistically via WEH from the
unintended interference and/or the intended signal sent by the transmitter. We
further assume a single-antenna receiver that can only decode information or
harvest energy at any time due to the practical circuit limitation. Therefore,
it is important to investigate when the receiver should switch between the two
modes of information decoding (ID) and energy harvesting (EH), based on the
instantaneous channel and interference condition. In this paper, we derive the
optimal mode switching rule at the receiver to achieve various trade-offs
between wireless information transfer and energy harvesting. Specifically, we
determine the minimum transmission outage probability for delay-limited
information transfer and the maximum ergodic capacity for no-delay-limited
information transfer versus the maximum average energy harvested at the
receiver, which are characterized by the boundary of so-called "outage-energy"
region and "rate-energy" region, respectively. Moreover, for the case when the
channel state information (CSI) is known at the transmitter, we investigate the
joint optimization of transmit power control, information and energy transfer
scheduling, and the receiver's mode switching. Our results provide useful
guidelines for the efficient design of emerging wireless communication systems
powered by opportunistic WEH.Comment: to appear in IEEE Transactions on Wireless Communicatio
Optimal Energy Allocation for Kalman Filtering over Packet Dropping Links with Imperfect Acknowledgments and Energy Harvesting Constraints
This paper presents a design methodology for optimal transmission energy
allocation at a sensor equipped with energy harvesting technology for remote
state estimation of linear stochastic dynamical systems. In this framework, the
sensor measurements as noisy versions of the system states are sent to the
receiver over a packet dropping communication channel. The packet dropout
probabilities of the channel depend on both the sensor's transmission energies
and time varying wireless fading channel gains. The sensor has access to an
energy harvesting source which is an everlasting but unreliable energy source
compared to conventional batteries with fixed energy storages. The receiver
performs optimal state estimation with random packet dropouts to minimize the
estimation error covariances based on received measurements. The receiver also
sends packet receipt acknowledgments to the sensor via an erroneous feedback
communication channel which is itself packet dropping.
The objective is to design optimal transmission energy allocation at the
energy harvesting sensor to minimize either a finite-time horizon sum or a long
term average (infinite-time horizon) of the trace of the expected estimation
error covariance of the receiver's Kalman filter. These problems are formulated
as Markov decision processes with imperfect state information. The optimal
transmission energy allocation policies are obtained by the use of dynamic
programming techniques. Using the concept of submodularity, the structure of
the optimal transmission energy policies are studied. Suboptimal solutions are
also discussed which are far less computationally intensive than optimal
solutions. Numerical simulation results are presented illustrating the
performance of the energy allocation algorithms.Comment: Submitted to IEEE Transactions on Automatic Control. arXiv admin
note: text overlap with arXiv:1402.663
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