Bounded Network Delay Research Articles

Event-triggered stabilization of uncertain scalar switched linear systems with bounded network delay

This paper aims to stabilize an uncertain scalar switched linear system whose feedback information is transmitted over a digital communication network. The system has a scalar state. That network can only supply a finite data rate to represent the state and suffers from time-varying bounded network delay. Due to the unknown mode switch time and the unknown network delay, mode mismatch between the plant and the controller is unavoidable. By applying reachable set approximation and propagation approaches, this paper quantitatively investigates the effects of mode mismatch and model uncertainty on the system’s stability and designs communication and control strategies to guarantee the desired stability. Moreover, it proposes some novel event-triggered sampling strategies, under which the required stabilizing bit rate can be lower than that required by traditional periodic sampling strategies. Simulations are done to verify the obtained results.

Event‐triggered stabilization of multi‐dimensional nonlinear systems under communication constraints

AbstractThis article investigates the input‐to‐state stability of a multi‐dimensional nonlinear system, which transmits feedback information through an unreliable communication network with bounded network delay and occasional dropouts. In order to stabilize the system and save the occupied communication resources, we propose a model‐based periodic event‐triggered control strategy which can make full use of feedback packets, especially the information contained in their triggering time instants. However, both the network delay and feedback dropouts will reduce the amount of information extracted from triggering/sampling time instants, and significantly degrade the system performance. To handle them, this article provides a novel encoding and decoding method to make use of the timing information and the bits inside each feedback packet for both state and output feedback cases. Compared with the conventional time‐driven strategies, the proposed event‐triggered one can stabilize the concerned nonlinear system at a lower bit rate. The effectiveness and bit rate advantage of the proposed strategy are further illustrated through simulations.

An event-triggered consensus protocol for quantized second-order multi-agent systems with network delay and process noise

This paper focuses on the quantized consensus problem of discrete-time second-order multi-agent systems which suffer from bounded process noise. In such systems, neighboring agents exchange information through a digital network that has only a finite bit rate and is subject to bounded network delay. Network delay may exacerbate the effects of quantization error and degrade the control performance by reducing the information to be extracted from receiving time instants of exchange packets. To handle network delay and save communication bit rates, an event-triggered distributed control protocol based on a dynamic encoding–decoding policy is proposed. Under the proposed event-triggered protocol, the asymptotic consensus of the concerned noise-free multi-agent systems can be achieved at a lower bit rate than that of periodic sampling control. This bit rate superiority results from the fact that our protocol makes use of the extra information being extracted from the event-triggering time instants. Moreover, it is shown that no higher bit rate is required to guarantee the desired consensus in the existence of bounded process noise. Simulations are done to demonstrate the effectiveness of our consensus protocol. As shown by our numerical examples, the occupied bit rate to ensure the desired consensus can be saved by up to 50% compared with periodic sampling strategies.

Feedback Stabilization of Switched Linear Systems With Bounded Network Delay Under Finite Data Rates

This paper aims to stabilize a switched linear system which transmits its feedback information through digital communication networks. It investigates the effects of three factors on stabilization of the concerned system, including bounded network delay, unknown switching time instants and limited information to represent the system state. The network delay cannot be precisely known, may degrade the system’s performance and even destabilize it. Compared with the earlier work on delay-free switched linear systems, it needs to place stricter restrictions on the feedback data rate conditions and the average dwell time. It assumes that the switching is slow enough in the sense of combined dwell time and average dwell time, each individual mode is stabilizable and the available feedback data rate is high enough, but still finite. It proposes some encoding and control strategies to stabilize the switched linear systems with bounded network delay under some feedback data rate conditions.

Model-Based Periodic Event-Triggered Control Strategy to Stabilize a Scalar Nonlinear System

This article focuses on the problem of stabilizing a scalar continuous-time nonlinear system under bounded network delay and process noise. In order to save the feedback network's bandwidth, a model-based periodic event-triggered control policy is utilized to maintain longer intersampling intervals, which are at least as long as the sampling period of periodic policies. Furthermore, the event-triggering condition is only checked intermittently at fixed time instants, i.e., the sampling time instants. Without acknowledgment (ACK), the updating of nominal models at the sensor and at the controller are asynchronous. The two cases, where the network delay is either less than the sampling period or larger than the sampling period, are investigated. In comparison with periodic sampling methods, our scheme can make full use of the received data packets, particularly their sampling time instant information, which yields a lower occupied bit rate while guaranteeing the desired input-to-state stability. Note that the obtained bit rate conditions are only related to the Lipschitz parameter, the bound of network delay, the number of quantization bits, and the sampling period. The bounded process noise will not incur any increase of the stabilizing bit rate under the proposed strategy.

Sufficient bit rate conditions to stabilize an uncertain scalar nonlinear system based on event triggering

This paper considers to stabilize an uncertain scalar continuous-time nonlinear system with bounded network delay and process noise, which transmits all feedback signals through a digital communication network. In order to save the bandwidth of the feedback network, stability is expected to be maintained at as low as possible feedback bit rate. Based on event triggering, this paper proposes a model-based event-triggered sampling strategy to guarantee the desired input-to-state stability of the concerned system. Due to the bounded network delay, the receiving time instant of a feedback packet cannot be precisely controlled by the sensor, i.e., the receiving time instant is not always equal to its sampling time instant. Their gap, i.e., the network delay, determines how much information can be carried through the receiving time instant and makes great impact on the system’s stability. Sufficient bit rate conditions to stabilize that system are derived. The conditions are determined by the parameter of Lipschitz condition, the upper bound of the network delay and the system uncertainty. Compared with the periodic sampling strategies, a lower bit rate is required by the proposed event-triggered strategy. Simulations are done to verify the effectiveness of the achieved stabilizing bit rate conditions.

Bit-Rate Conditions to Stabilize a Continuous-Time Linear System With Feedback Dropouts

This technical note considers the input-to-state stability of a continuous-time linear system, which sends feedback signals from the sensor to the controller over a nondeterministic communication network with bounded network delay and occasional dropouts. Not only the bits inside each feedback packet, but also the sampling time instant of that packet can carry information. Due to processing delay and network delay, the controller cannot precisely know the sampling time of a packet and can only approximate it with the receive time instant of that packet. The difference between the sampling and receive time instants of a packet is referred to as timing error, which reduces the amount of information extracted from the receive time instant. By additionally extracting information from receive time instants of feedback packets, we may stabilize the concerned system in the input-to-state sense at a lower bit rate than the approaches utilizing only the bits inside feedback packets. Besides timing error, nondeterministic dropouts of feedback packets may also harm the stability of the concerned system. By simultaneously considering timing error and feedback dropouts, we derive some stabilizing bit-rate conditions that are determined by the unstable eigenvalues of the system matrix, the dropout rate, and the upper bound on the timing error. These stabilizing bit-rate conditions are not disturbed by bounded process noise.

Predictive control and scheduling codesign in network control systems

A codesign approach combining predictive control compensation and network scheduling is presented in this paper to overcome the adverse influences of stochastic time delays and packet losses encountered in network-based real-time control systems. The state estimation and control prediction compensation algorithms are used for the random network delays in the feedback and forward channels, and the stability criteria are analyzed. The proper sampling rate is given with network scheduling to meet the desired system performance, while the network-induced delay is tolerated. Simulations show that the codesign approach works well with the bounded network delay.

A MIXED-METRIC ROUTING WITH OPTIMAL FLOW DISTRIBUTION FOR MPLS NETWORKS

This paper proposes a new routing system for IP network traffic engineering. In this system, the link cost metrics are chosen to reflect the congestion level in terms of the number of flows traversing a given link as well as its residual bandwidth. This cost is used in the design of a dynamic routing for MPLS networks. At the same time, an optimal distribution of network flows is found, and used to impose a balanced traffic loading overall network links. This in turns, have led to a bounded network delay performance. Results have shown robustness of the proposed routing technique over networks with arbitrary topologies and heavy traffic demands.