Limited Communication Channels Research Articles

Detection and stabilization for discrete-time descriptor systems via a limited capacity communication channel

This paper addresses the state estimation and stabilization for linear discrete-time descriptor systems. It is assumed that the estimator and controller can only receive the transmitted sequence of finite coded signals via a limited digital communication channel. Both coder–decoder and coder–decoder–controller procedures are proposed, in which a compensation term is introduced to meet the compatible requirement. In addition, an effective method for selecting the compensation term is presented. Detection and stabilization conditions in terms of linear matrix inequality are obtained. Finally, an example is given to illustrate the effectiveness of design procedures.

CHAOTIC SYNCHRONIZATION WITH LIMITED INFORMATION

The problem of synchronization of two identically chaotic systems coupled through a limited capacity communication channel (LCCC) is addressed. Using the sampled and encoded information, an impulsive control designed is applied to the response system by resetting its initial state at the beginning of every sampling interval. It is shown that synchronization can be achieved based on the requirement imposed on the number of values taken by the coder, the sampling period and Lipschitz constant of the chaotic system. Based on this requirement, an explicit coder–decoder pair is proposed for chaotic synchronization via a LCCC. Finally, the numerical simulation for the Chua's chaotic system is shown to illustrate the obtained result.

H∞ filtering for discrete-time systems with randomly varying sensor delays

This paper investigates an H ∞ filtering problem for discrete-time systems with randomly varying sensor delays. The stochastic variable involved is a Bernoulli distributed white sequence appearing in measured outputs. This measurement mode can be used to characterize the effect of communication delays and/or data-loss in information transmissions across limited bandwidth communication channels over a wide area. H ∞ filtering of this class of systems is used to design a filter using the measurements with random delays to ensure the mean-square stochastic stability of the filtering error system and to guarantee a prescribed H ∞ filtering performance. A sufficient condition for the existence of such a filter is presented in terms of the feasibility of a linear matrix inequality (LMI). Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.

Set-valued state estimation for uncertain continuous-time systems via limited capacity communication channels

This paper addresses a problem of set-valued state estimation for uncertain continuous-time systems via limited capacity communication channels. The uncertainty of the systems satisfies an integral quadratic constraint. Using results from the robust Kalman filtering, we design a coder/decoder-estimator pair that allows us to construct set-valued state estimate of the systems via communication channels.

On Networked Control Architectures for MIMO Plants

In this work we focus on control of MIMO LTI plants and explore the potential benefits of replacing a traditional diagonal non-networked control architecture with a networked full MIMO one. Diagonal terms of the networked MIMO architecture employ transparent links, whereas the off-diagonal terms use communication channels which are subject to signal-to-noise ratio constraints. Within this setup, we show how to design LTI coding systems which optimize overall performance. Unsurprisingly, for high-quality channels the full MIMO architecture is preferable to decentralized architectures. However, our analysis reveals that the achievable performance in the networked situation may become arbitrarily poor, if the signal-to-noise ratio constraints in the communication links are sufficiently severe. In these cases, traditional decentralized controller structures are preferable. In the present work, we limit our analysis to the two-input two-output case and illustrate our results for networked control systems with bit-rate limited communication channels.

State estimation via limited capacity noisy communication channels

The paper addresses a state estimation problem involving communication errors and capacity constraints. Discrete-time partially observed linear systems perturbed by stochastic unbounded additive disturbances are studied. Unlike the classic theory, the sensor signals are communicated to the estimator over a limited capacity noisy digital link modeled as a stochastic discrete memoryless channel. It is shown that the capability of the noisy channel to ensure state estimation with a bounded in probability error is identical to its capability to transmit information with as small probability of error as desired. In other words, the classic Shannon capacity of the channel constitutes the boundary of the observability domain. It is shown that whenever the Shannon capacity bound is met, a reliable observation can be ensured by means of a state estimator consuming a bounded (as time progresses) computational complexity and memory per unit time. The corresponding state estimator is constructed explicitly and is based on the classic block coding approach, so that traditional block encoding–decoding procedures can be employed for its implementation.

Detectability and Output Feedback Stabilizability of Nonlinear Networked Control Systems

This note addresses problems of detectability and output feedback stabilizability of nonlinear systems with globally Lipschitz nonlinearities via limited capacity digital communication channels. The main results are given in terms of Riccati algebraic inequalities. A simulation result on the control of a flexible joint robotic system is also presented

Adaptive Coding for Transmission of Position Information Over the Limited-band Communication Channel1

The problem is considered of transmission object position estimates using band limited communication channels. Due to advances in technology, it is feasible to have a tracking filter attached to the sensor, and transmit only the condensed information as a tradeoff between computation and communication requirements. This paper proposes a scheme, which minimizes transmission data rate by sending adaptively encrypted innovations. It is assumed that the second derivative of the object position is bounded above by the known constant, and the sample rate is the design parameter. Adaptive tuning procedure for the coder range parameter is proposed and numerically studied.

<tex>$H_infty$</tex>Control for Networked Systems With Random Communication Delays

This note is concerned with a new controller design problem for networked systems with random communication delays. Two kinds of random delays are simultaneously considered: i) from the controller to the plant, and ii) from the sensor to the controller, via a limited bandwidth communication channel. The random delays are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution. The observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and also achieve the prescribed H/sub /spl infin// disturbance attenuation level. The addressed controller design problem is transformed to an auxiliary convex optimization problem, which can be solved by a linear matrix inequality (LMI) approach. An illustrative example is provided to show the applicability of the proposed method.

Analysis and synthesis of networked control systems: Topological entropy, observability, robustness and optimal control

This paper extends the concept of topological to the case of uncertain dynamical systems. We address problems of observability and optimal control via limited capacity digital communication channels. The main results are given in terms of inequalities between date rate of the communication channel and topological entropy of the open-loop system. Topological entropy is calculated for some classes of uncertain dynamical systems.

ANALYSIS AND SYNTHESIS OF NETWORKED CONTROL SYSTEMS: TOPOLOGICAL ENTROPY, OBSERVABILITY, ROBUSTNESS AND OPTIMAL CONTROL

This paper extends the concept of topological entropy to the case of uncertain dynamical systems. We address problems of observability and optimal control via limited capacity digital communication channels. The main results are given in terms of inequalities between date rate of the communication channel and topological entropy of the open-loop system. Topological entropy is calculated for some classes of uncertain dynamical systems.

The problem of optimal robust Kalman state estimation via limited capacity digital communication channels

This paper considers a state estimation problem for a continuous-time uncertain system via a digital communication channel with bit-rate constraints. The estimated state must be quantized, coded and transmitted via a limited capacity digital communication channel. Optimal and suboptimal recursive coder–decoder state estimation schemes are proposed and investigated.

Role of Software in Spacecraft Accidents

The first and most important step in solving any problem is understanding the problem well enough to create effective solutions. To this end, several software-related spacecraft accidents were studied to determine common systemic factors. Although the details in each accident were different, very similar factors related to flaws in the safety culture, the management and organization, and technical deficiencies were identified. These factors include complacency and discounting of software risk, diffusion of responsibility and authority, limited communication channels and poor information flow, inadequate system and software engineering (poor or missing specifications, unnecessary complexity and software functionality, software reuse without appropriate safety analysis, violation of basic safety engineering practices in the digital components), inadequate review activities, ineffective system safety engineering, flawed test and simulation environments, and inadequate human factors engineering. Each of these factors is discussed along with some recommendations on how to eliminate them in future projects.

Robust stabilization of linear uncertain discrete-time systems via a limited capacity communication channel

The paper considers the problem of robust stabilization of linear uncertain discrete-time systems via limited capacity communication channels. We consider the case when the control input is to be transmitted via communication channel with a bit-rate constraint. A constructive method to design a robustly stabilizing controller is proposed.

The problem of LQG optimal control via a limited capacity communication channel

The paper addresses a LQG optimal control problem involving bit-rate communication capacity constraints. A discrete-time partially observed system perturbed by white noises is studied. Unlike the classic LQG control theory, the control signal must be first encoded, then transmitted to the actuators over a digital communication channel with a given bandwidth, and finally decoded. Both the control law and the algorithms of encoding and decoding should be designed to archive the best performance. The optimal control strategy is obtained. It is shown that where the estimator-coder separation principle holds, the controller-coder one fails to be true.

Scheduling of a limited communication channel for optimal control

In this paper a method for optimal off-line scheduling of a limited resource used for control purposes is presented. For various reasons, real-time communication channels are prone to have limited bandwidth. To overcome this obstacle, the rate of actions must be chosen accordingly at design time, both with respect to the limitation of the resource and to control performance. A resulting off-line schedule implements the rate of actions as a repetitive sequence of communication instants. Periodic control theory is used to define a cost functional for LQ-control, that measures the performance of a sampled-data system in relation to a desired continuous time performance. In contrast to uniform sampling, the communication sequence is here allowed to be time-varying. This approach results in a complex combinatorial optimization problem, whose solution gives the optimal off-line schedule, i.e., the sequence in which the actions should take place. The optimization problem is solved by a neighborhood search method where a heuristic method is used to generate initial guesses close to the optimum. The optimal schedule is typically such that the sampling is non-uniform, but the resulting LQ-control law is time-varying and takes this non-uniform sampling into account.

군집 선행차량의 원격제어를 위한 통신 채널의 최적 스케줄링

A remote control strategy for vehicles in Intelligent Vehicle Highway System (IVHS) is considered. An optimal scheduling of a limited communication channel is proposed for lead vehicle control in a platoon. The optimal scheduling problem is to find the optimal communication sequence that minimizes the cost obtained inherently by an optimal control without the communication constraint. In this paper, the PID control law which guarantees the string stability is used for the lead vehicle control. The fact that the PID control law is equivalent to the approximately linear quadratic tracker allows to obtain the performance measure to find an optimal sequence. Simulations are conducted with five maneuvering platoons to evaluate the optimality of the obtained sequence.

Iconic representation for progressive transmission of medical images

Progressive image transmission (PIT) has been shown to be effective in providing timely delivery of medical images over limited bandwidth communication channels. A novel method for identifying regions of interest and producing iconic caricatures is presented. The generation of these caricatures is designed as a first step in a context-based form of progressive image transmission. Regions of interest are identified but images are not segmented. The identification of regions of interests uses shape information provided by multi-scale medial axis (MMA). This approach avoids the need for prior knowledge to label regions of an image. An approximate labelling is used to create iconic images. The results presented show improved ability to detect low contrast regions and delineation appropriate to the context to provide a good caricature. These results confirm that robust and reliable iconic representation can be generated without prior knowledge of image content. The method described also has potential for extension to colour and 3D image data sets.

Set-valued state estimation via a limited capacity communication channel

This paper considers a state estimation problem for a linear continuous-time system via a limited capacity communication channel. The observation must be coded and transmitted via a limited capacity digital communication channel. A recursive order-decoder state estimation scheme is proposed and investigated.

Joint optimization of communication rates and linear systems

We consider a linear control system in which several signals are transmitted over communication channels with bit rate limitations. With the coding and medium access schemes of the communication system fixed, the achievable bit rates are determined by the allocation of communications resources such as transmit powers and bandwidths, to different communication channels. We model the effect of bit rate limited communication channels by uniform quantization and the quantization errors are modeled by additive white noises whose variances depend on the achievable bit rates. We optimize the stationary performance of the linear system by jointly allocating resources in the communication system and tuning parameters of the controller.