Multi-rate Networked Systems Research Articles

Neural-network-based output feedback control for networked multirate systems: A bit rate allocation scheme

This paper deals with the neural-network (NN)-based output feedback control problem for a class of networked systems with unknown nonlinearities under the effects of bit rate constraints. Considering the physical conditions/requirements in practical applications, the sampling period of sensors is assumed to be different from the state updating period of the system. For the purpose of facilitating digital communications over networks, a group of encoders is utilized to convert the measurement signal into codewords with limited bit lengths. A so-called bit rate constraint is introduced to capture the bandwidth-limited nature of communication network. To handle the unknown nonlinearity of the multirate system, both the NN-based observer and NN-based controller are designed to generate the desired state estimates and control input signals, respectively. Then, a unified framework is established to analyze the boundedness of the estimation error and system state as well as the neural network weights. The effects of the bit rate constraint on the resultant control performance is also analyzed. Subsequently, sufficient conditions are derived to guarantee the existence of the required NN-based output feedback controller. A particle-swarm-optimization-based (PSO-based) algorithm is developed to co-design the desired controller parameter and the bit rate allocation strategy. Finally, an illustrative example is given to verify the effectiveness of the proposed control strategy.

Detection of intermittent faults for nonuniformly sampled multi-rate systems with dynamic quantisation and missing measurements

ABSTRACT This paper is concerned with the fault detection problem for a class of networked multi-rate systems with nonuniform sampling and dynamic quantization. The sampling interval of the measurements is allowed to be nonuniform that is governed by a time-homogenous Markov process with partly unknown and uncertain transition probabilities. The measured output is quantized by a dynamic quantizer and then transmitted through communication network subject to data missing. The main purpose of the problem under consideration is to design sampling-interval-dependent fault detection filters such that, in the simultaneous presence of nonuniform sampling, dynamic quantization, intermittent faults as well as missing measurements, the robustness of residuals with respect to the disturbance and the sensitivity of the residuals against the fault are guaranteed. Finally, a three-tank system is utilized to illustrate the effectiveness of the proposed fault detection scheme.

Event-Based Finite-Time Filtering for Multirate Systems With Fading Measurements

In this paper, the finite-time filtering problem is investigated for a class of wireless networked multirate systems (NMSs) with fading channels. The system measurements are transmitted through fading channels described by a modified stochastic Rice fading model, and the event-based wireless relay communication scheme is proposed to determine whether the received fading measurements in the relay nodes should be transmitted to the filter. With the aid of the stochastic analysis approach, sufficient conditions are established under which the stochastic finite-time boundedness (FTB) of the estimation error dynamics is guaranteed and the prescribed finite-time $H_{\infty }$ performance constraint is achieved. Based on the derived conditions, the addressed finite-time filtering problem of NMSs is recast as a convex optimization one that can be solved via the semidefinite program method. Furthermore, the explicit expression of the desired filter is obtained by means of the feasibility of certain matrix inequalities. Two additional optimization problems are considered with respect to the FTB parameter and the finite-time $H_{\infty }$ performance index. Finally, a numerical simulation example on a continuous stirred tank reactor is employed to show the effectiveness of the filtering scheme proposed in this paper.

Fault detection filter design for networked multi‐rate systems with fading measurements and randomly occurring faults

In this study, the fault detection (FD) problem is investigated for a class of networked multi-rate systems (NMSs) with network-induced fading channels and randomly occurring faults. The stochastic characteristics of the fading measurements are governed by mutually independent random channel coefficients over the known interval [0,1]. By applying the lifting technique, the system model for the observer-based FD is established. With the aid of the stochastic analysis approach, sufficient conditions are established under which the stochastic stability of the error dynamics for the state estimation is guaranteed and the prescribed H ∞ performance constraint on the error dynamics for the fault estimation is achieved. Based on the established conditions, the addressed FD problem of NMSs is recast as a convex optimisation one that can be solved via the semi-definite program method, and the explicit expression of the desired FD filter is derived by means of the feasibility of certain matrix inequalities. The main results are specialised to the networked single-rate systems that are a special case of the NMSs. Finally, two simulation examples are utilised to illustrate the effectiveness of the proposed FD method.

Variance-constrained state estimation for networked multi-rate systems with measurement quantization and probabilistic sensor failures

Summary This paper is concerned with the variance-constrained state estimation problem for a class of networked multi-rate systems (NMSs) with network-induced probabilistic sensor failures and measurement quantization. The stochastic characteristics of the sensor failures are governed by mutually independent random variables over the interval [0,1]. By applying the lifting technique, an augmented system model is established to facilitate the state estimation of the underlying NMSs. With the aid of the stochastic analysis approach, sufficient conditions are derived under which the exponential mean-square stability of the augmented system is guaranteed, the prescribed H∞ performance constraint is achieved, and the individual variance constraint on the steady-state estimation error is satisfied. Based on the derived conditions, the addressed variance-constrained state estimation problem of NMSs is recast as a convex optimization one that can be solved via the semi-definite program method. Furthermore, the explicit expression of the desired estimator gains is obtained by means of the feasibility of certain matrix inequalities. Two additional optimization problems are considered with respect to the H∞ performance index and the weighted error variances. Finally, a simulation example is utilized to illustrate the effectiveness of the proposed state estimation method. Copyright © 2016 John Wiley & Sons, Ltd.

Variance-constrained state estimation for networked multi-rate systems with measurement quantization and probabilistic sensor failures

Variance-constrained state estimation for networked multi-rate systems with measurement quantization and probabilistic sensor failures