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Design of Control Laws and State Observers for Fixed-Wing UAVs: Simulation and Experimental Approaches provides readers with modeling techniques, simulations, and results from r… Read more
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1 Introduction
1.1 Classification of UAVs
1.2 Nonmilitary applications of fixed-wing UAVs
1.3 Control systems in fixed-wing UAVs
1.4 State observer systems in fixed-wing UAVs
2 Aerodynamic principles
2.1 The importance of aerodynamic principles
2.1.1 The atmosphere
2.1.2 Atmospheric pressure
2.1.3 Standard atmosphere
2.1.4 Air temperature
2.1.5 Air density
2.1.6 Airplane wing
2.1.7 Bernoulli theorem
2.1.8 The center of pressure
2.2 Forces acting in flight
2.2.1 Flight opposition (resistance)
2.2.2 Thrust
2.2.3 Lift
2.3 Axes of an airplane
2.3.1 Aircraft control surfaces
2.3.2 The structure of an airplane
2.4 Concluding remarks
3 Equations of motion of a fixed-wing UAV
3.1 Control surfaces of a fixed-wing MAV4 Linear controllers
4.1 PD and PID controllers
4.2 LQR controller
4.3 LQR controller with the discrete-time Kalman filter
4.4 Concluding remarks
5 Nonlinear controllers
5.1 Nested saturation controller
5.2 Backstepping controller
5.3 Sliding mode controller
5.4 Nested saturation with sliding mode
5.5 Nested saturation with 2-SM
5.6 Nested saturation with HOSM
5.7 Backstepping with SM
5.8 Backstepping with 2-SM
5.9 Backstepping with HOSM
5.10 MIT rule based on the gradient method with sliding mode theory
5.11 Concluding remarks
6 State observers
6.1 Applications and concepts of state observers in control theory
6.2 Complementary filters
6.3 Sliding mode observers
6.3.1 Sliding surface
6.3.2 Shear effect and sliding patch
6.3.3 System damping
6.4 Nonlinear extended state observer
6.5 Backstepping observer
6.6 Simulation results of the control laws with observers
6.6.1 PD control law with observers
6.6.2 Backstepping control law with observers
6.6.3 Roll motion simulations with PD control law with observers
6.6.4 Yaw motion simulations with PD control law with observers
6.6.5 Altitude motion simulations with PD control law with observers
6.6.6 Roll motion simulations with backstepping control law with observers
6.6.7 Yaw motion simulations with backstepping control law with observers
6.6.8 Altitude movement simulations with backstepping control law with observers
6.7 Concluding remarks
7 Testbed and experimental results
7.1 Experimental testbed
7.2 Motors or actuators in a testbed
7.3 Inertial measurement unit (IMU)
7.4 Telemetry
7.5 Optocoupler
7.6 Microcontroller and altimeter
7.7 Microprocessor Rabbit 6000
7.8 Li-po battery
7.9 Experimental results for linear and nonlinear controllers
7.9.1 PD controller
7.9.2 PID controller
7.9.3 LQR controller
7.9.4 LQR controller with discrete-time Kalman filter
7.9.5 Backstepping controller
7.10 Experimental results for linear and nonlinear observers
7.10.1 Luenberger observer applied to a fixed-wing UAV with PD control law
7.10.2 SMO applied to a fixed-wing UAV with PD control law
7.10.3 NESO applied to a fixed-wing UAV with PD control law
7.10.4 SMO applied to a fixed-wing UAV with backstepping control law
7.10.5 NESO applied to a fixed-wing UAV with backstepping control law
7.11 Concluding remarks
A Mathematical review
A.1 Vectors
A.2 Linear transformations
A.3 Euclidean norm
A.4 Matrices
A.5 Spectral norm
A.6 P-norms
A.7 Dyadic product, cross product, and antisymmetric matrix
A.8 Topological concepts
A.8.1 Sets
A.8.2 Metric spaces
A.8.3 Linear independence
A.8.4 Sequence convergence
A.9 Functions
A.9.1 Continuous functions
A.9.2 Differentiable functions
A.9.3 Mean value theorem
A.9.4 Implicit function theorem
A.9.5 Gronwall–Bellman inequality
A.10 Contraction mapping
B Kinematics and dynamics background
B.1 Kinematics
B.2 Dynamics
C Stability in the Lyapunov sense
C.1 Direct Lyapunov method
D Fundamentals of linear and nonlinear controllers
D.1 Fundamentals of linear controllers
D.1.1 PID and PD controller theory
D.1.2 Linear quadratic regulator (LQR)
D.2 Fundamentals of nonlinear controllers
D.2.1 Nested saturations
D.2.2 Integrator backstepping
D.2.3 Sliding mode control
D.2.4 Model reference adaptive control (MRAC)
E Discrete-time Kalman filter
F
Linear and nonlinear controllers: programs for the embedded systemF.1 PD controller in altitude
F.2 Backstepping controller in altitude
G Linear and nonlinear state observers: programs for the embedded system
G.1 Luenberger observer with PD controller in yaw
G.2 SMO observer with PD controller in altitude
H MATLAB® program to graph
I Altimeter program
AE
AD
RP
JS