Number Of Consecutive Packet Dropouts Research Articles

Stability Analysis and Controller Design of Networked Active Vehicle Suspension System Subject to Delays and Packet Losses

In this paper, the stability analysis and control design of networked control systems (NCS) subject to network induced delay and packet dropouts, the study is aiming to maximize the allowable upper bound of network induced delay together with the number of consecutive packet dropouts, The analysis method utilizes a new Lyapunov-Krasovskii (LKF) functional to provide less conservative results. The delay-dependent stability criteria based on improved Wirtinger inequality and reciprocally convex combination inequality are derived in terms of linear matrix inequalities (LMI). Finally, numerical examples are given to show the effectiveness of the proposed analysis method compared to other existing methods.

Improved robust H ∞ stability analysis and stabilisation of uncertain and disturbed networked control systems with network-induced delay and packets dropout

This paper is concerned with stability analysis and stabilisation of uncertain Networked Control Systems (NCS) with network-induced delay and packet dropouts. This proposal aims at maximising the allowable upper bound of network-induced delay, together with the number of consecutive packet dropouts, from which uncertain and disturbed NCS plants are stable. A novel augmented Lyapunov–Krasovskii functionals (LKF), dependent on both the lower and upper bounds of the network-induced time-varying delay, is considered to derive the proposed delay-dependent LMI-based stability conditions. Relaxation of these conditions are obtained by exploiting simple and double integral Wirtinger's inequalities to introduce more degrees of freedom from the LKF terms than existing related conditions in the literature. Finally, numerical examples and simulation results are presented to illustrate the effectiveness and the conservatism improvement raised by this proposal compared to previous related results.

Data-based predictive control for networked nonlinear systems with packet dropout and measurement noise

In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closed-loop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.

Robust stability of a class of Networked Control Systems

Networked Control Systems (NCSs) affected with packet dropouts and scheduling are considered. The undesirable effects of packet dropouts and scheduling, such as instability or deteriorated performance, are addressed by application of a protocol and controller co-design method. The used method exploits Model Predictive Control (MPC) framework and the flexible NCS architecture which allows for distributed computation. Uniform Global Asymptotic Stability (UGAS) is established by assuming a finite bound on the number of consecutive packet dropouts and appropriate modifications to often adopted MPC stability-related assumptions. Two approaches that demonstrate UGAS are provided. The proof of one approach consists of finding an appropriate Lyapunov candidate function, while the other uses a cascade stability idea.

State Estimation of Discrete-Time Takagi-Sugeno Fuzzy Systems in a Network Environment.

In this paper, we investigate the H∞ filtering problem of discrete-time Takagi'Sugeno (T-S) fuzzy systems in a network environment. Different from the well used assumption that the normalized fuzzy weighting function for each subsystem is available at the filter node, we consider a practical case in which not only the measurement but also the premise variables are transmitted via the network medium to the filter node. For the network characteristics, we consider the multiple packet dropouts which are described by using a Markov chain. It is assumed that the filter uses the most recent packet. If there are packet dropouts occurring, the filter adopts the information for the last received packet. Suppose that the mode of the Markov chain is ordered according to the number of consecutive packet dropouts from zero to a preknown maximal value. For each mode of the Markov chain, it only has at most two jumping actions: 1) jump to the first mode and the current packet is transmitted successfully and 2) jump to the next mode and the number of consecutive packet dropouts increases by one. We aim to design mode-dependent and fuzzy-basis-dependent T-S fuzzy filter by using the transmitted packet subject to the described network issue. With the augmentation technique, we obtain a stochastic filtering error system in which the filter parameters and the Markovian jumping variable are all involved. A sufficient condition which guarantees the stochastic stability and the H∞ performance is derived with the Lyapunov method. Based on the sufficient condition, we propose the filter design method and the filter parameters can be determined by solving a set of linear matrix inequalities (LMIs). A tunnel-diode circuit in a network environment is presented to show the effectiveness and the advantage of the proposed design approach.

Packetized MPC with dynamic scheduling constraints and bounded packet dropouts

We study a Networked Control System architecture which uses a communication network in the controller–actuator links. The network is affected by packet dropouts and allows access to only one plant input node at each time instant. This limits control performance significantly. To mitigate these limitations we propose a control and network protocol co-design method. Succinctly, the underlying features of the proposed method are as follows: a sequence of predicted optimal control values over a finite horizon, for an optimally chosen input node, is obtained using Model Predictive Control ideas; the entire resulting sequence is sent to the chosen input node; a smart actuator is used to store the predictions received and apply them accordingly. We show that if the number of consecutive packet dropouts is uniformly bounded, then partial nonlinear gain ℓ2 stability and also a more traditional linear gain ℓ2 stability can be ensured via appropriate choice of design parameters and the right assumptions. Whilst our results apply to general nonlinear discrete-time multiple input plants affected by exogenous disturbances, for a disturbance-free case we prove that Global Asymptotic Stability follows from our main result. Moreover, we show that by imposing stronger assumptions, Input-to-State Stability is achievable as well. Finally we demonstrate the potential of the proposed method via simulations.

Sparse Packetized Predictive Control for Networked Control Over Erasure Channels

We study feedback control over erasure channels with packet-dropouts. To achieve robustness with respect to packet-dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. To reduce the data size of packets, we propose to adopt sparsity-promoting optimizations, namely, ell-1-ell-2 and ell-2-constrained ell-0 optimizations, for which efficient algorithms exist. We derive sufficient conditions on design parameters, which guarantee (practical) stability of the resulting feedback control systems when the number of consecutive packet-dropouts is bounded.

Dynamic output feedback of networked control systems with partially known Markov chain packet dropouts

SummaryIn this paper, a class of networked control systems with output feedback control and H ∞ performance is discussed. It considers packet dropouts in both measurement (S/C) and actuation (C/A) channels. Markovian chain principle is used in modeling the packet dropouts in S/C and C/A channels. The time scale adopted in these two independent homogeneous Markov chain is linear with the physical time. The model also takes into consideration the late arriving packets. The effect of interaction between packet dropouts in both channels on the stability of system, when the networks of both (S/C) and (C/A) channels overlap is also examined. Sufficient condition for the existence of H ∞ output feedback controller is presented and it is shown that it is dependent on the upper bounds of the number of consecutive packet dropouts. The developed stability analysis and control scheme is also investigated with partially known transition probability matrices. Finally, a numerical example has been given to show the effectiveness of developed method. Copyright © 2013 John Wiley & Sons, Ltd.

H∞ Controller Design of Networked Control Systems with Markov Packet Dropouts

This paper presents an H∞ controller design method for networked control systems (NCSs) with bounded packet dropouts. A new model is proposed to represent packet dropouts satisfying a Markov process and late-arrival packets. The closed-loop NCS with a state-feedback controller is transformed into a Markov system, which is convenient for the controller synthesis. Two types of state-feedback control laws are taken into account. Sufficient conditions on the existence of controllers for stochastic stability with an H∞ disturbance attenuation level are derived through a Lyapunov function dependent on the upper bound of the number of consecutive packet dropouts. A numerical example is finally provided to show the effectiveness of the proposed method.

Output feedback control of networked control systems with packet dropouts in both channels

This paper is concerned with the problem of H∞ output feedback control for networked control systems with packet dropouts in both sensor-to-controller and controller-to-actuator channels. Packet dropouts in these two links are modeled as two independent Markov chains, whose transition probability matrices are sparse so that it is easy to obtain. Moreover, late arrivals are considered in the model as well. Sufficient conditions for the solvability of design problems of H∞ output feedback controllers are presented and are dependent on the upper bounds of the number of consecutive packet dropouts. The validity of the proposed approaches are illustrated by a numerical example.

Robust stability of packetized predictive control of nonlinear systems with disturbances and Markovian packet losses

We study a predictive control formulation for uncertain discrete-time non-linear uniformly continuous plant models where controller output data is transmitted over an unreliable communication channel. The channel introduces Markovian data-loss and does not provide acknowledgments of receipt. To achieve robustness with respect to dropouts, at every sampling instant the controller transmits packets of data. These contain possible control inputs for a finite number of future time instants, and minimize a finite horizon cost function. At the actuator side, received packets are buffered, providing the plant inputs. Within this context, we adopt a stochastic Lyapunov function approach to establish stability results of the networked control system. A distinguishing aspect of this work is that it considers situations where the maximum number of consecutive packet dropouts has unbounded support.

Input-to-state stability of hybrid systems with receding horizon control in the presence of packet dropouts

We analyze the stability of a constrained piecewise continuous hybrid system that is controlled by a receding horizon controller across an unreliable communication channel. We assume the presence of a buffer at the actuator to store the control input sequence received from the controller to compensate for any possible packet dropouts in future transmissions. Input-to-state stability is considered under the assumption that the number of consecutive packet dropouts is bounded using tightened state constraints in the optimization problem solved by the controller.

Control over erasure channels: stochastic stability and performance of packetized unconstrained model predictive control

SUMMARYIn this work, we consider the control of discrete‐time constrained nonlinear systems over unreliable packet‐based communication networks. The random packet dropouts are modeled by a two‐state Markov chain, and no acknowledgments of receipt are assumed. To weaken the impact of the packet dropouts, the controller transmits packets containing more than one future control input, and a suitable buffering is applied at the plant actuator side. Because the Markov chain model adopted does not ensure the number of consecutive packet dropouts to be bounded, deterministic stability cannot be guaranteed. Hence, we are interested in stochastic stability of the closed loop instead. We propose an unconstrained model predictive control scheme without additional terminal weighting term for the calculation of the control inputs. Two major advantages of this unconstrained model predictive control scheme can be emphasized. First, to guarantee stochastic stability, we do not require the knowledge of a global control Lyapunov function as terminal cost term but instead only a less restrictive controllability assumption. Second, guaranteed performance bounds on the expected infinite horizon cost of the closed loop can be obtained. Copyright © 2012 John Wiley & Sons, Ltd.

Sparse Representations for Packetized Predictive Networked Control

We investigate a networked control architecture for LTI plant models with a scalar input. Communication from controller to actuator is over an unreliable network which introduces packet dropouts. To achieve robustness against dropouts, we adopt a packetized predictive control paradigm wherein each control packet transmitted contains tentative future plant input values. The novelty of our approach is that we seek that the control packets transmitted be sparse. For that purpose, we adapt tools from the area of compressed sensing and propose to design the control packets via on-line minimization of a suitable L1/L2 cost function. We then show how to choose parameters of the cost function to ensure that the resultant closed loop system be practically stable, provided the maximum number of consecutive packet dropouts is bounded. A numerical example illustrates that sparsity reduces bit-rates, thereby making our proposal suited to control over unreliable and bit-rate limited networks.

Optimal Filtering for Systems With Multiple Packet Dropouts

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <?Pub Dtl=""?>This paper is concerned with the optimal filtering problem for discrete-time stochastic linear systems with multiple packet dropouts, where the number of consecutive packet dropouts is limited by a known upper bound. Without resorting to state augmentation, the system is converted to one with measurement delays and a moving average (MV) colored measurement noise. An unbiased optimal filter is developed in the linear least-mean-square sense. Its solution depends on the recursion of a Riccati equation and a Lyapunov equation. A numerical example shows the effectiveness of the proposed filter. </para>