Use of fly-by-wire technology for aircraft flight controls have resulted in an improved performance and reliability along with achieving reduction in control system weight. Implementation of full authority digital engine control has also resulted in more intelligent, reliable, light-weight aircraft engine control systems. Greater reduction in weight can be achieved by replacing the wire harness with a wireless communication network. The first step towards fly-by-wireless control systems is likely to be the introduction of wireless sensor networks (WSNs). WSNs are already finding a variety of applications for both safety-critical and nonsafety critical distributed systems. Some of the many potential benefits of using WSN for aircraft systems include weight reduction, ease of maintenance and an increased monitoring capability. This paper discusses the application of WSN for several aircraft systems such as distributed aircraft engine control, aircraft flight control, aircraft engine and structural health monitoring systems. A brief description of each system is presented along with a discussion on the technological challenges. Future research directions for application of WSN in aircraft systems are also discussed.

In this paper, we address the issue of the stability of distributed engine control systems under communication constraints and, in particular, for packet dropouts. We propose a control design procedure, labeled decentralized distributed full-authority digital engine control and based on a two-level decentralized control framework. We show that the packet dropping margin, which is a measure of stability robustness under packet dropouts, is largely dependent on the closed-loop controller structure and that, in particular, a block-diagonal structure is more desirable. Thus, we design a controller in a decentralized framework to improve the packet dropping margin. The effect of different mathematical partitioning on the packet dropping margin is studied. The proposed methodology is applied to an F100 gas turbine engine model, which clearly demonstrates the usefulness of decentralization in improving the stability of distributed control under packet dropouts.Nomenclature K 2 = spectral condition number of a matrix = max , where are eigenvalues with a positive real part = independent and identically distributed Bernoulli random process = spectral radius of a matrix = Kronecker product k k 2 = spectral norm of a matrix # = Moore-Penrose inverse of a matrix

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