The Development of Neural Network Based System Identification ...

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16 CHAPTER 2 LITERATURE REVIEW on-board in any of the system components [Roadmap, 2005]. According to US Defence Department UAS Roadmap 2010-2035, humans are not a part of UAS but rather an external system interacting with the UAS [Roadmap, 2005]. There are a number of important fields of science and technology that are directly related to UAV research such as aerodynamics, propulsion, structural, flight dynamic and control, flight performance and electronic system integration into UAV platform. On the other hand, a fully autonomous UAV indicates that an airframe is capable of performing given missions successfully within a pre-defined scope. This can be achieved through the use of onboard sensors and manipulation systems without human or external system involvement [Kendoul, 2012]. Rotorcraft or helicopters have been used as an experimental platform for UAV research throughout academics and aeronautical industries. Helicopter based UAS offers many potential capabilities in both civil and military applications such as surveillance, aerial mapping, cinematography, high structure inspection, natural disaster damage assessment and monitoring operations. Technological advancements in this exciting area have enabled a helicopter based UAS to operate autonomously, which reduces risk and a pilot’s workload while flying in close proximity flight patterns. Any type of aircraft may serve as the base airframe for a UAS application. Traditionally, fixed-wing aircrafts have been preferred as the aerial platforms simply because of their simple structures, and being efficient and easy to build and maintain. The autopilot design is easier for fixed-wing aircraft than for rotary-wing aircraft because the fixed-wing aircraft have relatively simple, symmetric, and decoupled dynamics [Shim, 2000]. However, helicopter-based UAS have been desirable for certain applications where the unique helicopter’s flying capabilities are required. The rotorcraft can take off and land within limited space and they can also hover and cruise at very low speed which makes them the perfect vehicle for tracking or searching out ground targets. The helicopter based aerial platform is also much more efficient than fixed wing type aircraft that usually requires a runway for take-off and landing. However, the helicopter based UAV capabilities are also limited with disadvantages which are listed as follows: • More complicated mechanical structure.
2.1 INTRODUCTION 17 • Inefficient flight dynamics: lower maximum speed, shorter mission range. • More accurate and complicated navigation sensor requirement. • Inherently unstable and relatively poorly known dynamics. Difficult control system design. Typical helicopters or rotorcraft based UAS are classified into five categories that differ on several characteristics [Kendoul, 2012, Eisenbeiss, 2004]. Figure 2.1 shows the classification of helicopter UAS based on attributes such as the total weight of the aircraft, payload, range, service ceiling and endurance. Most unmanned aerial vehicle platforms available at the University of Canterbury consist of rotorcraft based UAS from Category 3 and 4. The UAS from Category 3 is based on commercially available remote control (RC) helicopter and requires considerable amount of work to integrate the autopilot system into the aerial platform. Nevertheless, the aerial platform used in this research was selected from Category 3 UAS which offers larger payload capacity and longer endurance than Category 4 or 5. Thus, better payload capacity and endurance would make the selection of Category 3 UAS much more suitable for longer monitoring and surveillance applications such as aerial mapping, cinematography, high structure inspection and natural disaster damage assessment. A helicopter based UAS requires three main autonomy elements such as guidance, navigation and control (GNC) to enable them to execute above-mentioned missions autonomously. The overview of autonomous system components for helicopter based UAS is given in Figure 2.2. As described in Kendoul [2012], the navigation function for helicopter UAS involves the process of acquisition and analysis of sensory data and how to use them to infer the vehicle’s state informations (position, orientation, velocity). The navigation process also includes the capabilities to build an internal model of the surrounding environments within UAS operation using perception techniques such as mapping, object recognition, obstacle and target detection. These capabilities are essential for operating a UAS to ensure that it can successfully complete an assigned mission. The guidance function for a helicopter based UAS demonstrate the high level planning and decisions making process to enable successful missions or goal execution.
Page 1: The Development of Neural Network B
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Chapter 4 NEURAL NETWORK BASED SYST
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4.3 SYSTEM IDENTIFICATION WITH NEUR
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4.4 SUMMARY 117 Segment 1 Segment 2
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Chapter 5 NN BASED SYSTEM IDENTIFIC
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5.6 ON-LINE SYSTEM IDENTIFICATION 1
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5.6 ON-LINE SYSTEM IDENTIFICATION 1
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5.7 MODEL PERFORMANCE COMPARISON US
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5.8 SUMMARY 151 methods such as wei
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5.8 SUMMARY 153 would enable the im
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156 CHAPTER 6 NEURAL NETWORK BASED
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Chapter 7 FLIGHT CONTROL SYSTEM DES
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7.2 FLIGHT TESTS IMPLEMENTATION 185
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7.3 EXPERIMENTAL RESULTS 187 1 0.8
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7.3 EXPERIMENTAL RESULTS 189 Longit
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7.3 EXPERIMENTAL RESULTS 191 Pitch
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7.3 EXPERIMENTAL RESULTS 193 Flight
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7.3 EXPERIMENTAL RESULTS 195 140 Ya
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7.3 EXPERIMENTAL RESULTS 197 indica
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7.3 EXPERIMENTAL RESULTS 199 20 100
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7.3 EXPERIMENTAL RESULTS 201 Yaw Ra
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7.3 EXPERIMENTAL RESULTS 203 mainta
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7.3 EXPERIMENTAL RESULTS 205 Yaw Ra
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7.4 SUMMARY 207 data measured from
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210 CHAPTER 8 CONCLUSIONS AND FUTUR
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212 CHAPTER 8 CONCLUSIONS AND FUTUR
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214 REFERENCES B. W. Bequette. Non-
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216 REFERENCES Konstantinos Dalamag
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218 REFERENCES Wayne Johnson. Helic
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220 REFERENCES B. Mettler, Mark B.
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222 REFERENCES V. R. Puttige and S.
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224 REFERENCES D.H. Shim. Hierarchi
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226 REFERENCES Nikos Vitzilaios and
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