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研究生： 李志升
Lee, Chi-Seng
論文名稱： 限制型預測控制應用於固定翼無人飛機橫向飛行控制器之設計與實踐
Design and Implementation of Lateral Flight Controller Using Constrained Predictive Control for a Fixed-Wing Unmanned Aerial Vehicle
指導教授： 蕭飛賓
Hsiao, Fei-Bin
學位類別： 博士
Doctor
系所名稱： 工學院 - 航空太空工程學系
Department of Aeronautics & Astronautics
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 201
中文關鍵詞： 預測控制 、移動時域控制 、子空間識別法 、預測誤差法 、二次最佳化問題 、無人飛機
外文關鍵詞： Model Predictive Control, Receding Horizon Control, Subspace, Prediction Error Method, Quadratic Programming problem, Unmanned Aerial Vehicle
相關次數： 點閱：113  下載：3 
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    • 本論文的研究目的在於運用預測控制理論去進行固定翼無人飛機(UAV)系統之橫向飛行控制器設計與飛測驗證。預測控制之主要特性在於它直接利用受控體的數學模型去預測系統本身在有限時域(finite horizon)之響應，再透過最佳化特定性能指標以取得最佳化的控制信號，亦即移動時域(receding horizon)之控制策略。另外，預測控制理論能夠把受控體在輸入、輸出和狀態變數裏的限制一併考慮進去。當受控體在現實環境操作時，免不了會遇到一些無可避免的限制，預測控制可透過線上解決有限制最佳化問題(constrained optimization problem)，例如二次最佳化問題(quadratic programming problem)，讓系統在達成控制目標之餘也能夠滿足所有的限制條件。此特點對飛機的飛行控制器的設計非常有利，因為飛行控制所仰賴的控制翼面在移動角度和移動速度上一般都有不可超越的物理上限值。另外，飛機的飛行響應也必須維持在一些安全範圍，如滾轉速率不能太快，否則有可能會造成飛機結構不能負荷而導致災難性的後果。有鑒於此，本文利用國立成功大學無人飛機與微衛星實驗室所自行研發的黑面琵鷺號無人飛機系統為研究平台，將預測控制理論應用和實踐於橫向飛行控制器的設計上，同時並詳細地描述無限制和有限制的預測控制器之設計流程，也探討個別控制器之性能和穩定性的表現。此外本文利用系統鑑別(system identification)的方法去取得黑面琵鷺號無人飛機的橫向動態模型，其中主要方法為子空間識別法(subspace identification)和預測誤差法(prediction error method)。 最後，經由電腦模擬和實際飛行測試，本文成功的驗證了雖然預測控制器的演算法因為需要即時解決有限制最佳化問題而偏複雜，把它實踐於如無人飛機飛行般的高頻寬控制平台上是可行且務實的。

    This thesis explores the feasibility and practicality of using the predictive control approach to design the lateral flight controller for a fixed-wing unmanned aerial vehicle (UAV). One of the primary features of predictive control is the control theory’s ability to consider the future implication of current control actions by explicitly computing the predicted system response over a finite horizon, i.e. the receding horizon strategy. The optimal control input is then determined by optimizing some measure of the predicted performance. Another important advantage that comes with the receding horizon strategy is the ability to respect constraints imposed upon the control inputs, state and output variables. The systematic handling of constraint violations is achieved by solving a constrained optimization problem, e.g. the quadratic programming (QP) problem at each sampling instant. The capability makes the predictive control highly attractive in the design of flight controllers for aircraft. The control surfaces of a fixed-wing aircraft are often physically limited in terms of deflection angle and angular speed. Furthermore, the operation of an aircraft often needs to be confined within a safe flight envelop which means it is vital to ensure that some flight parameters, e.g. the roll rate do not exceed the corresponding safety limits during flight. In this work, the predictive control strategy, formulated in unconstrained and constrained optimization problems, is implemented on the lateral flight control of the Spoonbill UAV –– an existing UAV research platform of the Remotely-Piloted Vehicle and Microsatellite Research Laboratory, National Cheng Kung University, Taiwan. Part of this dissertation is devoted to the modeling effort where a discrete-time linear state-space model that describes the lateral motion of the Spoonbill UAV is obtained via system identification method. In particular, the system identification routine features the utilization of subspace and prediction error method in a complementary manner. In the mean time, the complete synthesis of the lateral flight controller for the Spoonbill UAV within the framework of predictive control theory is presented. Simulation experiments are conducted to investigate various issues pertaining to the effectiveness and characteristics of the predictive flight controller. Finally, successful flight test results demonstrate the viability of the predictive control strategy and show that despite the heavy computational requirement due to the online optimization routine, it is both feasible and practical to implement the predictive control strategy on a high-bandwidth application such as the inner-loop control of a fixed-wing UAV.

    摘要 i ABSTRACT iii Extended Chinese Abstract v ACKNOWLEDGMENTS xiii CONTENTS xiv LIST OF TABLES xix LIST OF FIGURES xxi NOMENCLATURE xxiv Chapter 1 Introduction 1 1.1 Background 1 1.2 Literature Review 6 1.3 Motivations and Objectives 10 1.4 Dissertation Overview 11 Chapter 2 Spoonbill UAV System 14 2.1 Air Vehicle 14 2.1.1 Weight Component Breakdown 17 2.1.2 Propulsion System 18 2.1.3 Aircraft Performance 19 2.1.4 Control and Actuation 21 2.2 Onboard Avionics System 23 2.2.1 System Architecture 23 2.2.2 Data Acquisition and Flight Control Program 26 2.2.3 Power Requirement and Distribution 27 2.3 Ground Station 29 2.4 Payload System 31 2.5 Interim Conclusion 31 Chapter 3 System Modeling and Identification 33 3.1 System Modeling 33 3.1.1 Reference Frames 33 3.1.2 Sign Convention 36 3.1.3 Linearized Equations of Motion 37 3.1.4 Discrete-Time Linear State-Space Model 46 3.2 System Identification 47 3.2.1 Prediction Error Method 49 3.2.2 Subspace Method 51 3.2.3 Test Maneuver Design 52 3.3 Trimmed Flight Condition 55 3.4 Identification Results 56 3.5 Model Validation 61 3.5.1 Controllability and Observability 66 3.6 State Observer 67 3.6.1 Kalman Filter 68 3.6.2 Noise Covariance Matrices 70 3.7 Interim Conclusion 76 Chapter 4 Unconstrained Predictive Control 78 4.1 Fundamental Concept of Predictive Control 78 4.2 Prediction with State-Space Model 81 4.3 Unconstrained Problem Formulation 83 4.3.1 Reformulation as a Least-Squares Problem 88 4.4 Reference Trajectory 89 4.5 Structure of Unconstrained Predictive Controller 91 4.6 Tuning Parameters 92 4.6.1 Prediction and Control Horizons 93 4.6.2 Weighting Matrices of Cost Function 94 4.7 Lateral Flight Controller Design and Simulation 95 4.7.1 Simulation Results and Discussion 99 4.8 Stability Issue 104 4.9 Interim Conclusion 106 Chapter 5 Constrained Predictive Control 108 5.1 Constrained Problem Formulation 109 5.1.1 Formulation as a Quadratic Programming Problem 112 5.2 Structure of Constrained Predictive Controller 114 5.3 Solving a Convex Quadratic Programming Problem 115 5.3.1 Convex QP Problems with Equality Constraints 115 5.3.2 Primal Active Set Method 116 5.3.3 Finding an Initial Feasible Point 120 5.3.4 Computational Speed Issue 120 5.4 Feasibility Issue 122 5.5 Lateral Flight Controller Design and Simulation 124 5.5.1 Simulation Results and Discussion 131 5.6 Unconstrained vs. Constrained Predictive Controller 135 5.7 Interim Conclusion 140 Chapter 6 Flight Test Results 143 6.1 Flight Test Setup and Procedures 143 6.2 Unconstrained Predictive Controller 145 6.2.1 Wing-Level Flight 146 6.2.2 Shallow and Deep Turns 146 6.2.3 Dynamic Rolling Maneuvers 147 6.3 Constrained Predictive Controller 154 6.3.1 Wing-Level Flight 154 6.3.2 Shallow and Deep Turns 155 6.3.3 Dynamic Rolling Maneuvers 155 6.4 Interim Conclusion 161 Chapter 7 Concluding Remarks 163 7.1 Summary of Contributions 166 7.2 Future Work 167 REFERENCES 169 Appendix A Onboard Hardware Specifications 178 A.1 Onboard Computer 178 A.2 Onboard Computer Power Supply 179 A.3 Global Navigation Satellite System Receiver 180 A.4 Attitude and Heading Reference System 182 A.5 Sensor Integration Board 183 A.6 Servo Management Board 186 A.7 Servo Motors 187 A.8 Battery Packs 188 A.9 Engine 189 Appendix B Linearization of Rolling Moment and Yawing Moment Equations 190 Appendix C Cross-Validation Results of System Identification 193 VITA 199 PUBLICATION LIST 200

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