J Control Theory Appl 2011 9 (1) 28–33 DOI 10.1007/s11768-011-0242-9
Application of wireless sensor networks to aircraft control and health management systems Rama K. YEDAVALLI, Rohit K. BELAPURKAR Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus Ohio 43210, U.S.A.
Abstract: 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. Keywords: Wireless sensor networks; Distributed turbine engine control; Fly-by-wireless; Aircraft engine health monitoring; Aircraft structural monitoring; Communication constraints
1
Introduction
A typical commercial/military aircraft consists of a number of safety-critical systems, such as aircraft engine control system, aircraft flight control systems and nonsafety critical systems, such as structural and engine health monitoring systems, aircraft cabin environmental control system, inflight entertainment system, etc. These systems demand a large number of real-time sensors for their optimal operation. Current systems, which are based on wired connections, are complex, difficult to route, heavy and prone to damage and degradation due to wear. The Airbus A380, for instance, has over 300 miles of cables consisting of approximately 98,000 wires and 40,000 connectors [1]. Cable routing is quite a complex task, as for example, the power cable and electrical signal cable should be physically separated to avoid electrical interference and can hinder airline customization during manufacturing. Also, inaccessible sensor access point locations and harsh environmental conditions impose physical restrictions on the use of a wire harness. This results in the degradation of wiring causing catastrophic failures. For example, according to a U.S. Navy report, 6 aircraft were lost due to electrical failure over a 10 year period, about 78 aircrafts are made nonmission capable due to wiring faults each year and wiring faults cause more than 1000 mission aborts each year [2]. Replacement of the current wire harness-based sensors with a wireless sensor network (WSN) can help to achieve the goal of increasing the number of sensors as well as increasing the system redundancy. It will also reduce the aircraft system weight and lead to improved fuel efficiency and reduced carbon emissions. Replacing the physical cabling by wireless connections also offers significant benefits in flexibility, interoperability, mass reduction and improved robustness. Use of WSN also enables reduction in direct costs, mainte-
nance cost and obsolescence costs. As most of the current sensors have double/quadruple redundancy in the form of sensor hardware and wire harnesses, the use of WSN can result in huge weight savings. In a recent study, it was shown that the use of a wireless communication network can result in 90 lbs. weight reduction of Cessna 310R control systems, which increases its range by around 10%. Also, in the same study, assuming only a 50% wire reduction, 267 lbs. weight saving was shown to be achieved for an SH 60 military helicopter control system [3]. Fig. 1 shows the approximate locations of a few typical sensors required for aircraft flight control systems. As seen in the figure, the sensors are sparsely located increasing the wire harness length.
Fig. 1 Typical sensor locations of a commercial aircraft [4].
Received 18 October 2010. c South China University of Technology and Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg 2011
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This paper aims to discuss the various applications of WSN to aircraft control systems along with addressing the key technical challenges for their successful implementation. Future research directions for WSN-based aircraft systems will also be identified in this paper. The paper is organized as follows. In Section 2, we will briefly discuss the applications of WSN for aircraft control systems, specifically for flight control and aircraft engine control of commercial/military aircrafts and unmanned aerial vehicles (UAVs). This will be followed by a discussion on the use of WSN for aircraft engine maintenance & fault diagnostics and also for aircraft structural health monitoring. Technical challenges for implementation of WSNs for aircraft systems will be discussed in Section 3. Finally in Section 4, we will conclude this paper with a discussion on the future research directions for aircraft control and health management systems based on WSNs.
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Application of WSNs for aircraft systems
WSNs consist of a cluster of spatially distributed intelligent sensors designed to monitor a physical parameters, such as vibration, temperature, strain, pressure, etc. Each sensor node within the network performs the function of sensing, data processing and wireless data transmission and is powered by an individual power source. Use of microelectromechanical systems (MEMS) technology enables production of low-cost, low-power multifunctional sensors having very small size and light weight. The concepts, applications and research issues for applications of wireless sensor networks are widely discussed in [5,6]. Wireless sensor networks for aerospace applications such as space structures, spacecraft and ground testing equipment was studied in [7]. Aircraft systems can be broadly classified as safetycritical systems and nonsafety critical systems. Failures in safety-critical aircraft systems are determined unacceptable and could result in loss of life, damage to the environment or significant damage to the aircraft. Safety-critical systems which can benefit from the use of WSN are engine control systems and flight control systems for both commercial/military aircraft as well as for UAV. 2.1 Distributed aircraft engine control The present aircraft engine control systems are based on a centralized architecture in which all the sensors and actuators are individually connected to the engine controller, known as full authority digital engine control (FADEC). Heavily shielded analog wire harnesses are used for these point-to-point connections between sensor/actuator nodes and FADEC. Thermal as well as mechanical shielding of the current centralized engine control systems imparts a heavy weight penalty. Also, the current centralized architecture has a high obsolescence cost as well as a high maintenance cost. Before implementing WSN for aircraft engine control, an intermediate step is to move towards a distributed control architecture. In distributed engine control (DEC), the functions of FADEC are distributed at the component level. Each sensor/actuator is replaced by a smart sensor/actuator. These smart modules include local processing capability to allow modular signal acquisition and conditioning, and diagnostics and health management functionality. Dual channel digital serial communication network is used to connect these smart modules with FADEC. Fig. 2 shows the schematic of FADEC based on distributed control architecture.
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Fig. 2 FADEC based on distributed architecture.
Distributed engine control allows the implementation of advanced engine control technologies, for example, active clearance control, active stall and surge control, active combustion control and adaptive/intelligent control techniques which will improve aerothermodynamic efficiency, lower emissions and also help to reduce the control system weight. The distributed control approach is inherently more powerful, flexible, and scalable than a centralized control approach. Detailed studies of distributed engine control architecture can be found in [8∼10]. After successful implementation of distributed engine control based on fiber optics/ wired communication network, a progression can be made towards wireless architecture. Initially, WSN can be used only for the redundant sensors of distributed engine control system. An ideal distributed engine control architecture, which will make use of the advantages of WSN, will have actuators with wired connections in order to provide a secure, reliable control system architecture. However, there are major technical challenges to the realization of DEC. High temperature electronics, selection of appropriate communication architecture, and partitioning of the centralized controller are some of them. As the performance of the DEC will be dependent on the performance of the communication network, selection of the appropriate communication architecture is very important. Addition of the serial communication channel will introduce a number of communications constraints which must be considered to obtain the desired functionality of the controller. These constraints include time delays, packet dropouts and bit-rate limitations. Time delays and packet dropouts can degrade the controller performance or in worst case, can even destabilize the system. Hence, it is very important to study control of safety-critical distributed systems under these communication constraints. Decentralized distributed full authority digital engine control was proposed and studied for stability under time delays and packet dropouts in [11, 12]. As each of the smart nodes will be operating at adverse environmental conditions including harsh vibrations and high temperatures, it is necessary to develop reliable electronics capable of operating at these harsh conditions with low maintenance requirement. Several commercial off-theshelf (COTS) electronic components based on silicon-oninsulator (SOI) are available which can operate at temperatures up to 250 ◦ C. Silicon carbide (SiC)-based electronic components operating upto 500 ◦ C are one of the promising technologies that has to be further developed in order to successfully implement WSN-based distributed engine control. Also, since this is a safety-critical system, the reliability of the energy harvesting techniques needs to be further im-
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proved. The use of ethernet and wireless technologies for on-board systems, remote operational monitoring, testing and control of aircraft engine systems are well discussed in [13, 14]. 2.2 WSN for aircraft engine health management An aircraft engine is a complex system requiring regular maintenance to ensure flight safety. Engine maintenance, repair and overhaul (MRO) operations are time consuming and costly. Hence, in order to improve the time-on-wing of aircraft engines, it is desired to perform condition-based maintenance, which uses real-time data to schedule maintenance. Although the current maintenance methods do use sensors for monitoring, data is not stored or transmitted on a real time basis. This prevents the use of advanced health monitoring methods which require real time data analysis. Use of WSN for aircraft engine health monitoring will enable implementation of condition-based monitoring algorithms due to availability of real-time data. Each of the sensor nodes of the WSN will communicate with an onboard diagnostics and health monitoring system, which will store the data points for the entire flight. Once on ground, this data will be transmitted to the maintenance workshop through wireless communication. This will allow the use of online as well as offline diagnostic algorithms. Also, since the data communication will take place using a wireless network, huge infrastructural investments will not be required. As engine health monitoring is not a safety-critical system, certification of WSN-based engine health monitoring will be less complex than for WSN-based distributed engine control systems. However, availability of high temperature electronics will still be one of the major obstacles for successful implementation of WSN for engine health management. Use of wireless technology for in-flight monitoring of the temperature of aircraft gas turbine engines was studied in [15], and reference [16] provides an overview of an architecture based on WSN for engine health monitoring. 2.3 Fly-by-wireless aircraft flight control system The aircraft flight control systems consist of flight control surfaces, cockpit controls, sensors and communication linkages between cockpit control and flight control actuators. In the current fly-by-wire (FBW) flight control systems, flight control computers determine the control action, which is transmitted to the control actuator through wire harnesses. FBW flight control systems improves the handling characteristics of an aircraft by providing high-integrity automatic stabilization of an aircraft over the entire flight envelope and for all loading conditions. Triple/quadruple channel redundancy increases the safety and reliability of the flight control systems. Use of FBW flight control systems not only reduces the control system weight and reduces maintenance complexities, but also reduces the pilot workload by performing other functions like stall prevention, etc. Implementation of FBW enables to limit the aircraft within its structural and aerodynamic limitations, which is known as, flight envelope protection. However, these systems still retain the bulky and heavy hydraulic systems for actuating the control surfaces. Use of electrical or electro-hydraulic actuators will further reduce the weight, but will also require additional sensing elements. Intelligent flight control systems (IFCS) are being developed to safely control the aircraft in the presence of structural damage or failure during flight. This requires development of complex and intelli-
gent control algorithms, which in turn call for an increase in the number of sensors. Military aircrafts and in particular, UAVs will greatly benefit from the use of IFCS. Increasing the number of sensors, without a substantial increase in weight and complexity, is possible only by implementation of WSN. WSN will enable integration of several systems into one, for example, the use of WSN for both aircraft engine control and aircraft flight control will allow integration between flight control and propulsion control, which can significantly improve performance of military aircrafts as well as UAVs. Also, there will be greater flexibility for adding functionality or improving the performance of the aircraft after initial design and production. One of the other advantage of using fly-by-wireless flight control systems based on WSN is that if the pilots or flight deck controls become inoperable or incapacitated, ground-based air traffic control (ATC) or adjacent military aircraft with necessary electronics, can control the aircraft. Flight control systems being safety-critical systems are of extreme importance to improve the reliability and performance of WSN in order to obtain flight certification. Performance of WSN in an electromagnetic and radiation environment and under lightning strikes, which both are prevalent for commercial/military aircraft and UAVs needs to be studied. The effect of signal jamming on robustness of WSN has to be studied in depth, in particular for WSN based flight control systems of commercial aircrafts. The potential of WSN-based flight control systems as a backup for FBW flight control systems also needs to be evaluated. For high endurance UAV or for UAV having flexible/morphing wings, a common WSN for both aircraft flight control and aircraft structural control can greatly improve the flight performance. Optimum bandwidth reduction algorithms for increasing the number of sensors without a significant increase in their power requirement also have to be developed. Fig. 3 shows fly-by-wireless flight control systems with WSN.
Fig. 3 Fly-by-wireless aircraft flight control system.
2.4 WSN for aircraft structural health monitoring Because of the increasing use of composite materials for aircraft structures, it is necessary to develop novel methods for aircraft structural health monitoring. Most of the failures of the laminated composite structures originate with delamination of layers. In case of metal aircraft structures, cracks are developed in metal structures which grow over time leading to failures. For both of these cases, visual inspection is not a reliable method for failure detection. This calls for a vibration analysis-based failure detection method. Current scheduled aircraft structure maintenance methods have a high maintenance cost. Several studies have been
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conducted to develop health monitoring algorithms which use the data from strain sensors embedded into the composite structure. WSN can be embedded into the composite structure which will harvest the vibration energy and will transmit the real-time data to the central health monitoring unit. These sensors will be used to monitor the internal parameters like cracks, strain as well as external parameters like temperature, load, etc. Use of WSN, powered by energy harvesting techniques will increase the number of sensors as well as their life. Also, real-time data will enable the use of condition-based maintenance, thereby preventing catastrophic failure of aircraft structures. Although the use of MEMS is one of the promising technologies for implementation of WSN-based aircraft structural monitoring, optimum energy harvesting and power management methods for MEMS sensors have to be further improved. The integration of sensors and airframe has to be studied; in particular, the effect on the structural strength of composite materials due to embedded sensors has to be studied. If the sensor is to be attached on top of the aircraft structure, its interaction with the air flow needs to be investigated. An aircraft structural health monitoring system based on WSN is described in [17] while the structural health monitoring and reporting (SHMR) system, which uses wireless sensors was proposed and tested in [18]. Use of WSN for aircraft tire structural health monitoring is studied in [19]. 2.5 Other nonsafety critical systems Several other nonsafety critical systems that can also benefit from the WSN technology are discussed below. Aircraft hydraulic monitoring systems Hydraulic systems play a very important role in powering primary and secondary flight control systems as well as several other utility systems including undercarriage, wheelbrakes, cargo doors, loading ramps, etc. As failures in hydraulic systems may result in loss of maneuverability of the aircraft, it is necessary to monitor the temperatures, pressures and flow rates of hydraulic fluids. Conditionbased maintenance methods can also benefit from additional sensors; for example, filter blockage sensors can help the ground crew to monitor the condition of filter elements of hydraulic systems. By replacing the conventional sensors by WSN, it will be possible not only to display the signals to the gages in cockpit, but also to the ground servicing personnel for conducting on-wing aircraft engine maintenance. Environmental control systems Environmental control systems (ECS) provide air supply with optimum humidity and sufficient oxygen concentration to the passengers and crew and are also used for thermal control of the avionics, fuel and hydraulic systems. The efficiency of aircraft engines is often decreased due to increase in avionics heat load and due to inefficient air supply systems. Use of WSN for ECS will help to increase their reliability as well to improve the efficiency of the aircraft engines. De-misting, anti-icing systems can also benefit by the use of WSN. Emergency systems Use of WSN for smoke and fire detection systems, emergency lighting systems, passenger address systems, etc. can help to reduce the weight and wiring complexity of these systems along with increasing their reliability.
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3 Technical challenges Some of the technological challenges for implementing safety-critical control systems based on WSN are as follows. 3.1 Control under communication constraints The communication between sensors, controllers and actuators for both distributed engine control systems based on WSN and fly-by-wireless flight control systems will occur through a shared bandwidth-limited wireless network. The use of a wireless communication channel introduces a number of communication constraints, which have to be considered during the controller design. Two of such communication constraints that can have significant effects on the performance of the control system are network-induced time delays and packet dropouts. The network-induced delay can be further sub-divided into sensor-to-controller delay, controller-to-actuator delay, and the computational delay in the controller. Sensor-to-controller delay and controller-toactuator delay will depend on the communication protocol and can be either constant, time varying or random in nature. Network congestion and channel quality can also result in random network transmission delay. This delay can destabilize a system designed without considering the delay or can degrade the system performance. Packet dropouts in wireless communication can occur due to transmission errors, long transmission delays or due to packet collisions. References [20∼23] provide a brief introduction to networked control systems (NCS) and also present a survey on the recent developments in stability of NCS under communication constraints. In wireless communication networks, systems with packet dropouts can be described by stochastic models. The packet dropping of the wireless network can be modeled as an independent and identically distributed (i.i.d.) Bernoulli process with a packet dropping probability (PDP). The maximum PDP that a networked control system can tolerate before becoming unstable is called packet dropout margin (PDM). By improving PDM, which can be viewed as a measure of stability robustness for a system with packet dropouts, the stability of networked control systems with packet dropouts can be improved. A new framework, labeled decentralized distributed full authority digital engine control (D2 FADEC) was proposed in [11, 12] and was studied for stability under time delays and packet dropouts. It was shown that the PDM is dependent on a closed-loop system matrix structure and that a controller design based on a decentralized framework further improves the PDM. 3.2 MAC protocols for wireless control systems Each sensor node within the WSN has limited energy and computational resources. In order to make optimal use of these finite resources, a number of protocols based on medium access control (MAC) have been developed. These protocols stress on energy efficiency by reducing the energy loss due to wireless medium. Several MAC protocols like carrier sense multiple access (CSMA), IEEE 802.15.4, IEEE 802.11 are discussed in [24]. Since MAC protocols focus on energy efficiency and not on reduction in communication delay or packet dropouts, the performance of control systems based on these protocols is limited. Research should be conducted to design MAC protocols which are not only energy efficient, but also offer high quality of service (QoS) in terms of time delay, bandwidth utilization and
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data loss due to packet collisions. A very few studies have focused on this approach. For example, a cross-layer framework for an integrated design of wireless networks and distributed controllers, which significantly improves the performance and stability of the controller, is presented in [25]. 3.3 Dedicated spectrum for wireless aircraft systems Before implementing WSN for safety critical systems, it is necessary to ensure that their operability will not be compromised due to interference between various wireless networks. The WSNs should not interfere with the aircraft communication, navigation, and surveillance radio systems and the intra-aircraft wireless communication. The effect of crew/passenger portable wireless electronics devices on WSN also has to be considered during design of WSN. 3.4 Optimum power source Powering all the sensors using the conventional batteries will not only increase the size and weight of the system but will also limit their service life and will require expensive maintenance. A widely investigated alternative is to use energy harvesting techniques to generate electrical power for operating these sensors. WSN can operate almost maintenance free by use of both energy harvesting methods and by implementing strict power management [26,27]. Vibration-based harvesting technique is seen as one of the promising techniques for aerospace applications. Current vibration energy harvesters are constructed as mechanical resonators with a transducer element that converts motion into electricity. They are further divided into three groups of generators based on their physical transduction principle: piezoelectric, electrostatic, and electromagnetic. Piezoelectric vibration-based energy converters deliver the highest efficiency at lowest cost and increased life cycle. Piezo ceramic bimorph beams and MEMS-based piezo resonators can be used to harvest the energy from vibrations while bulk ceramic and fiber composites directly bonded to the aircraft structure can be used to harvest strain energy. As there is a significant temperature gradient between the cabin lining and aircraft shell, thermoelectric generators can also be used to harvest this energy. The operation of these thermoelectric devises is based on Seebeck-effect and it has been shown that a MEMS-based thermoelectric generator can be efficiently used to generate sufficient power. Use of MEMS-based steam microturbines to generate electricity from waste heat of engine exhaust should also be investigated. 3.5 Certification of aircraft wireless systems Use of wireless communication networks for safety critical functions of an aircraft require a very high degree of safety assurance and certification [28]. The Federal Aviation Administration (FAA) has certified a number of onaircraft wireless radio frequency (RF) systems which include wireless smoke and fire detection systems passenger wireless network systems and cabin emergency lighting systems with wireless controls. However, all these systems are nonsafety critical systems and typically operate in an unlicensed spectrum. Specific regulations for aircraft wireless systems do not exist and there is a need to develop specific regulations for such novel applications of WSN. Such regulations are necessary to ensure that there is no interference between portable electronic devices carried by passengers,
existing airplane radio transmitters and transmitters within the proposed WSN. There is no worldwide spectrum allocated specifically for fly by wireless systems. The new certification rules must ensure that WSN are protected against unauthorized introduction and modification of data, denial or loss of service, gradual degradation of service and introduction of misleading or false data. The current FAA regulations expect physical isolation between safety critical and other communications networks like passenger entertainment networks. Use of WSN for the entire aircraft makes physical isolation challenging. The new regulations must also address security threats including safety threats, business threats, channel jamming attacks, etc.
4 Conclusions The aerospace industry will greatly benefit from the use of WSN. These benefits through weight savings, reduction in subsystems design complexity and improved conditionbased maintenance will directly benefit the airlines in terms of additional revenues as well as lower operational and maintenance cost. Use of WSN-based engine health monitoring and aircraft structural health monitoring will enable the development of safety-critical systems such as WSN based distributed engine control and fly-by-wireless aircraft flight control systems. However, there are a few significant technical challenges for the successful implementation of wireless sensor networks. Future research should be directed in addressing the below given technical challenges. Safety-critical distributed control systems should be studied for stability and performance under communication constraints like time delays and packet dropouts. Research should be conducted to reduce the conservativeness of the existing random delay stability conditions. The effect of bitrate constraints on system stability and performance also needs to be evaluated. Research needs to be conducted in the area of information fusion of wireless sensor networks for aircraft systems. Routing protocols should be developed to make efficient use of the limited power supply, limited communication bandwidth and limited computing power. Energy harvesting methods needs further improvement in the terms of efficiency and reliability. Development of high temperature electronics will enable the use of WSN for aircraft engine control and health monitoring. New wireless aircraft certification regulations needs to be developed to address the various security and safety threats. A dedicated global spectrum for WSN for aircraft applications needs to be developed. References [1] M. Heinen. The A380 program[R]//Global Investor Forum, 2006. [2] J. Collins. The challenges facing U.S. navy aircraft electrical wiring systems[C]//Proceedings of the 9th Annual Aging Aircraft Conference, 2006. [3] K. Kiefer. Real-world experience in wireless instrumentation and control systems[C]//Proceedings of the CANEUS “Fly-by-Wireles” Workshop, 2007. [4] R. P. G. Collinson. Introduction to Avionics Systems[M]. Berlin: Springer-Verlag, 2002. [5] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, et al. Wireless sensor
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[20] J. P. Hespanha, P. Naghshtabrizi, Y. Xu. A survey of recent results in networked control systems[J]. Proceedings of the IEEE, 2007, 95(1): 138 – 162. [21] W. Zhang, M. Branicky, S. Phillips. Stability of networked control systems[J]. IEEE Control Systems Magazine, 2001, 21(1): 84 – 99. [22] J. Baillieul, P. J. Antsaklis. Control and communication challenges in networked real-time systems[J]. Proceedings of the IEEE, 2007, 95(1): 9 – 28. [23] J. P. Richard. Time-delay systems: An overview of some recent advances and open problems[J]. Automatica, 2003, 39(10): 1667 – 1694. [24] K. Kredo II, P. Mohapatra. Medium access control in wireless sensor networks[J]. Computer Networks, 2007, 51(4): 961 – 994. [25] X. Liu, A. Goldsmith. Wireless network design for distributed control[C]//Proceedings of the IEEE Conference on Decision and Control. New York: IEEE, 2004: 2823 – 2829. [26] L. Mateu, F. Moll. Review of energy harvesting techniques and applications for microelectronics[C]//Proceedings of SPIE. Bellingham, WA: SPIE-International Society for Optical Engineering, 2005: 359 – 373. [27] S. Roundy, D. Steingart, L. Frechette, et al. Power sources for wireless sensor networks[C]//Proceedings of the 1st European Workshop on Wireless Sensor Networks. Berlin: Springer-Verlag, 2004: 1 – 17. [28] K. Sampigethaya, R. Poovendran, L. Bushnell, et al. Secure wireless collection and distribution of commercial airplane health data[J]. IEEE Aerospace and Electronic Systems Magazine, 2009, 34(7): 14 – 20. Rama K. YEDAVALLI received his B.S. degree in Electrical Engineering and M.S. degree in Aerospace Engineering from the Indian Institute of Science, India, and Ph.D. degree from the School of Aeronautics and Astronautics of Purdue University in 1974, 1976 and 1981, respectively. He is currently a professor in the Department of Mechanical and Aerospace Engineering at the Ohio State University, Columbus, OH. He is a fellow of IEEE and a fellow of ASME and an associate fellow of AIAA. He is the recipient of the O. Hugh Schuck Best Paper Award by the American Automatic Control Council in 2001. Dr. Yedavalli’s research and teaching interests include robustness and sensitivity issues in linear uncertain dynamical systems, estimation and fault diagnostics of propulsion systems, control of smart structural systems, networked control systems, dynamics and control of flexible structures, aircraft, spacecraft, automotive, robotic, energy, and other mechanical control systems. E-mail:
[email protected]. Rohit K. BELAPURKAR joined the Ohio State University, U.S.A. in 2006 and is currently pursuing Ph.D. degree in the Department of Mechanical and Aerospace Engineering. He obtained his B.S. degree in Mechanical Engineering from University of Pune, India, in 2006 and M.S. degree in Aerospace Engineering from the Ohio State University, in 2008. His research interests include distributed aircraft engine control, networked control systems, time delay systems, decentralized control systems, sensor networks, nonlinear control theory, and robust control of safety-critical distributed systems. E-mail:
[email protected].
