Adaptive Guaranteed-Performance Consensus Control for Multiagent Systems With an Adjustable Convergence Speed

Adaptive guaranteed-performance consensus control problems for multi-agent systems are investigated, where the adjustable convergence speed is discussed. This paper firstly proposes a novel adaptive guaranteed-performance consensus protocol, where the communication weights can be adaptively regulated. By the state space decomposition method and the stability theory, sufficient conditions for guaranteed-performance consensus are obtained, as well as the guaranteed-performance cost. Moreover, since the convergence speed is usually adjusted by changing the algebraic connectivity in existing works, which increases the communication burden and the load of the controller, and the system topology is always given in practical applications, the lower bound of the convergence coefficient for multi-agent systems with the adaptive guaranteed-performance consensus protocol is deduced, which is linearly adjustable approximately by changing the adaptive control gain. Finally, simulation examples are introduced to demonstrate theoretical results

Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies

The goal of this paper is to propose novel strategies for adaptive learning of signals defined over graphs, which are observed over a (randomly time-varying) subset of vertices. We recast two classical adaptive algorithms in the graph signal processing framework, namely, the least mean squares (LMS) and the recursive least squares (RLS) adaptive estimation strategies. For both methods, a detailed mean-square analysis illustrates the effect of random sampling on the adaptive reconstruction capability and the steady-state performance. Then, several probabilistic sampling strategies are proposed to design the sampling probability at each node in the graph, with the aim of optimizing the tradeoff between steady-state performance, graph sampling rate, and convergence rate of the adaptive algorithms. Finally, a distributed RLS strategy is derived and is shown to be convergent to its centralized counterpart. Numerical simulations carried out over both synthetic and real data illustrate the good performance of the proposed sampling and reconstruction strategies for (possibly distributed) adaptive learning of signals defined over graphs.Comment: Submitted to IEEE Transactions on Signal Processing, September 201

On the performance of routing algorithms in wormhole-switched multicomputer networks

This paper presents a comparative performance study of adaptive and deterministic routing algorithms in wormhole-switched hypercubes and investigates the performance vicissitudes of these routing schemes under a variety of network operating conditions. Despite the previously reported results, our results show that the adaptive routing does not consistently outperform the deterministic routing even for high dimensional networks. In fact, it appears that the superiority of adaptive routing is highly dependent to the broadcast traffic rate generated at each node and it begins to deteriorate by growing the broadcast rate of generated message

Performance limitations of subband adaptive filters

In this paper, we evaluate the performance limitations of subband adaptive filters in terms of achievable final error terms. The limiting factors are the aliasing level in the subbands, which poses a distortion and thus presents a lower bound for the minimum mean squared error in each subband, and the distortion function of the overall filter bank, which in a system identification setup restricts the accuracy of the equivalent fullband model. Using a generalized DFT modulated filter bank for the subband decomposition, both errors can be stated in terms of the underlying prototype filter. If a source model for coloured input signals is available, it is also possible to calculate the power spectral densities in both subbands and reconstructed fullband. The predicted limits of error quantities compare favourably with simulations presented

Criterion-Related Validity of the Children\u27s Occupational Performance Questionnaire

This study examined concurrent, criterion-related validity of a new measure of occupational performance for children, the Children’s Occupational Performance Questionnaire (COP-Q). The COP-Q is completed by caregivers of children to measure performance in five areas of occupation: Activities of Daily Living, Instrumental Activities of Daily Living, Social Participation, Play/Leisure, and Education/Work. Scores from a sample of children ranging in age from birth to 18 years were correlated with scores from the Vineland Adaptive Behavior Scales-II (VABS), a well-established assessment tool of adaptive behavior that measures similar functional areas as the COP-Q. The results indicated that the COP-Q correlates highly and significantly with the constructs measured by the VABS including social interaction, communication, daily living skills, and to a lesser extent, motor skills. The strong relations between these measures suggest that adaptive behavior and occupational performance address similar constructs, and the results supported the validity of the COP-Q as a measure of occupational performance

Analysis and Design of Adaptive OCDMA Passive Optical Networks

OCDMA systems can support multiple classes of service by differentiating code parameters, power level and diversity order. In this paper, we analyze BER performance of a multi-class 1D/2D OCDMA system and propose a new approximation method that can be used to generate accurate estimation of system BER using a simple mathematical form. The proposed approximation provides insight into proper system level analysis, system level design and sensitivity of system performance to the factors such as code parameters, power level and diversity order. Considering code design, code cardinality and system performance constraints, two design problems are defined and their optimal solutions are provided. We then propose an adaptive OCDMA-PON that adaptively shares unused resources of inactive users among active ones to improve upstream system performance. Using the approximated BER expression and defined design problems, two adaptive code allocation algorithms for the adaptive OCDMA-PON are presented and their performances are evaluated by simulation. Simulation results show that the adaptive code allocation algorithms can increase average transmission rate or decrease average optical power consumption of ONUs for dynamic traffic patterns. According to the simulation results, for an adaptive OCDMA-PON with BER value of 1e-7 and user activity probability of 0.5, transmission rate (optical power consumption) can be increased (decreased) by a factor of 2.25 (0.27) compared to fixed code assignment.Comment: 11 pages, 11 figure