Measurement Size Reduction Research Articles

Energy efficient nonfragile control protocol for nonlinear large‐scale systems with input quantization

SummaryThe problem of robust stabilization for a class of nonlinear large‐scale systems with the energy constraints and time‐varying actuator faults is addressed in this article. In the considered system, the stabilization criteria is achieved via a sensor‐network‐based distributed fault‐tolerant controller. Moreover to limit the consumption of energy by the sensors, the measurement size reduction technique and communication rate reduction approach are implemented such that the resulting closed‐loop system is stable within a predefined extended passive performance index level. In particular, the sensor signal quantization technique is used to reduce the frequency and size of the transmitted data packet in the communication sequence. Based on the switched system theory and Lyapunov approach, a new set of sufficient conditions is obtained in the form of linear matrix inequality constraints to ensure the exponential stabilization of the considered system. The developed fault‐tolerant resilient control gains are designed by resorting to the cone complementarity linearization algorithm. Moreover, a nonisothermal continuous stirred‐tank reactor with interconnection is considered as an example to demonstrate the effectiveness of the proposed design technique.

Mixed [formula omitted] and passivity-based resilient controller for nonhomogeneous Markov jump systems

In this paper, the robust mixed H∞ and passivity-based control problem is investigated for a class of discrete-time Markov jump nonlinear systems with uncertainties, quantization and time-varying transition probabilities. In addition, the time-varying transition probability matrices in the considered system are described by a polytope set. Further, the measurement size reduction technique is implemented which consists of two factors, namely, the logarithmic quantization and the measurement element selection scheme. In order to reflect the imprecision in controller implementation, the additive controller gain problem is considered. Based on the Lyapunov stability theory, a new set of conditions is derived such that the resulting closed-loop Markov jump system is stochastically stable with a prescribed mixed H∞ and passivity performance index. Finally, the effectiveness of the proposed control scheme is illustrated by two numerical examples including an application example based on a DC motor device.

Hybrid-triggered state feedback H∞ control for networked control systems with stochastic nonlinearity and quantization

This paper is concerned with the state feedback H∞ control problem for hybrid-triggered networked control systems (NCSs) with stochastic nonlinearity and state quantization. In order to establish a higher utilization of the network resources, a hybrid-triggered transmission scheme (HTTS) and measurement size reduction scheme are introduced. Firstly, the HTTS is presented such that the signal can be transmitted according to the law. Then the measurement size reduction scheme, i.e., the logarithmic quantization is applied. Then, considering the effect of HTTS and quantization, the original NCSs model is reformulated as a new hybrid-triggered NCSs with communication delay. By using Lyapunov functional method and linear matrix inequality technique, sufficient conditions for stochastical stability with a prescribed H∞ performance level are established, and the design of controller and trigger parameters can be obtained. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

Containment Control of Linear Multiagent Systems With Aperiodic Sampling and Measurement Size Reduction.

The containment control problem for generally linear multiagent systems with aperiodic sampling intervals and measurement size reduction is considered in this paper. Under the assumption that the sampling interval changes from a finite set, an improved protocol is proposed, such that a larger sampling interval can be obtained to achieve containment. By using the properties of Laplacian matrix and the newly developed protocol, the containment control problem is transformed into the stability problem of a discrete-time switched linear system. A sufficient condition is obtained that ensures all the followers converge to the convex hull formed by the state of leaders, and such a sufficient condition is presented in terms of linear matrix inequalities, which are independent of the node of network. To further reduce the communication among agents, a switching-type measurement size reduction scheme is introduced. An optimization problem is proposed for the corresponding controller design. Finally, two simulation studies are conducted to show the effectiveness and advantage of the proposed control algorithms.

Robust fuzzy-model-based filtering for nonlinear networked systems with energy constraints

The fuzzy-model-based H∞ filtering for a class of discrete-time wireless nonlinear networked systems with energy constraints is investigated in this paper. Due to the limitation of transmission power, the measurement data is not transmitted at each sampling instant, and it is scheduled here. Two techniques are proposed to reduce the transmission power, i.e., event-based transmission protocol and measurement size reduction scheme. Firstly, a new event-based transmission protocol is presented such that the transmission occurs only when the designed event occurs. Then, the measurement size reduction technique is applied. The so-called measurement size reduction technique consists of two parts: the logarithmic quantization and the stochastic measurement element selection. The simultaneous utilization of above two techniques can significantly reduce the energy consumption in such a wireless networked system. By constructing the fuzzy-mode-dependent Lyapunov functional, sufficient conditions are derived such that the filtering error system is stochastically stable with a prescribed H∞ performance level. An optimization problem is presented to determine the optimal filter gains. The effectiveness of the proposed filter design scheme is illustrated by a simulation study on the nonlinear truck-trailer system.

Network-based H∞ synchronization control of time-delay neural networks with communication constraints

This paper is concerned with the network-based [Formula: see text] synchronization control for a class of discrete time-delay neural networks, and attention is focused on how to reduce the communication rate since the communication resource is limited. Techniques such as the measurement size reduction, signal quantization and stochastic signal transmission are introduced to achieve the above goal. An uncertain switched system model is first proposed to capture the above-networked uncertainties. Based on the switched system theory and Lyapunov stability approach, a sufficient condition is obtained such that the closed-loop synchronization system is exponentially stable in the mean-square sense with a prescribed [Formula: see text] performance level. The controller gains are determined by solving a set of linear matrix inequalities (LMIs). A numerical example is finally presented to show the effectiveness of the proposed design method.

Energy-Efficient Distributed Filtering in Sensor Networks: A Unified Switched System Approach.

This paper is concerned with the energy-efficient distributed filtering in sensor networks, and a unified switched system approach is proposed to achieve this goal. For the system under study, the measurement is first sampled under nonuniform sampling periods, then the local measurement elements are selected and quantized for transmission. Then, the transmission rate is further reduced to save constrained power in sensors. Based on the switched system approach, a unified model is presented to capture the nonuniform sampling, the measurement size reduction, the transmission rate reduction, the signal quantization, and the measurement missing phenomena. Sufficient conditions are obtained such that the filtering error system is exponentially stable in the mean-square sense with a prescribed H∞ performance level. Both simulation and experiment studies are given to show the effectiveness of the proposed new design technique.

Energy‐efficient distributed control of large‐scale systems: A switched system approach

SummaryThis paper is concerned with the sensor‐network‐based distributed control of large‐scale systems with the power constraint. In the underlying system, the measurement is firstly sampled under nonuniform sampling periods, which are varying in a given set. Then, the measurement size reduction technique and communication rate reduction method are used to save the constrained power in sensor networks. Specifically, only one element of sampled measurement is chosen at each sampling time instant, and it is then quantized and transmitted to the neighbouring controllers. Based on the switched system approach, a unified model is presented to capture the nonuniform sampling, the measurement size reduction, the transmission rate reduction and the controller failure phenomenon. A new sufficient condition is obtained such that the filtering error system is exponentially stable in the mean‐square sense with a prescribed H∞ performance level. Based on this condition, the controller gains are designed by using the cone complementarity linearization algorithm. Finally, a simulation study is given to show the effectiveness of the proposed new design technique. Copyright © 2015 John Wiley & Sons, Ltd.

Energy-efficient [formula omitted] filtering over wireless networked systems—A Markovian system approach

This paper is concerned with the energy-efficient filtering over wireless networked systems, and a Markovian system approach is proposed to achieve this goal. Firstly, the local measurement is stochastically sampled under nonuniform sampling periods, then the measurement size reduction scheme is applied and only one element of measurement is stochastically selected for quantization. Then, a stochastic transmission protocol is introduced to further save power. Based on the Markovian system approach, a new model is presented for the nonuniform sampling, the measurement size reduction, the signal quantization and the stochastic signal transmission. Sufficient conditions are obtained such that the filtering error system is exponentially stable in the mean-square sense with a prescribed H∞ performance level. A simulation study is given to show the effectiveness of the proposed new design technique.

Nonfragile H∞ filtering for wireless‐networked systems with energy constraint

This article is concerned with the nonfragile filtering for wireless‐networked systems with energy constraint. To achieve the energy‐efficient goal, the local measurement is first sampled by nonuniform sampling, then we only choose one measurement to transmit it to the remote filter. In the filter design, the random occurring filter gain variation problem is taken into account. A new stochastic switched system model is presented to capture the nonuniform sampling, the measurement size reduction, and the random filter gain phenomena. Based on the switched system approach, stochastic system analysis, and Lyapunov stability theory, a sufficient condition is presented such that the filtering error system is exponentially stable in the mean‐square sense and a prescribed performance level is also guaranteed. The effectiveness of the proposed new method is illustrated by a simulation example. © 2015 Wiley Periodicals, Inc. Complexity 21: 79–89, 2016