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    • Applied Control Systems 3 UAV Drone 3D Dynamics and Control

    Applied Control Systems 3: UAV drone (3D Dynamics & control)

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    Fees

    ₹ 449 3099

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 449  ₹3,099
    certificate availability

    Yes

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    Udemy

    The syllabus

    Drone architecture from Control Systems point of view

    • Introduction
    • UAV configuration + inertial VS body frame
    • Inputs and outputs of a 6 Degree of Freedom UAV drone
    • Propeller rotation directions 1
    • Propeller rotation directions 2 - Helicopter example
    • 1st control action - Thrust
    • 2nd control action - Roll
    • 3rd control action - Pitch (exercise)
    • 3rd control action - Pitch (solution) + 4th control action - Yaw (exercise)
    • 4th control action - Yaw (solution)
    • Rotation vector direction
    • Clarification on measuring with respect to body or inertial frames
    • Global view of the drone's control architecture
    • Follow up!

    Fundamental kinematics & dynamics equations for a 6 DOF system (Newton - Euler)

    • Kinematics VS Dynamics
    • Measuring the UAV's position (exercise)
    • Measuring the UAV's position (solution)
    • Intro to describing attitudes 1 (exercise)
    • Intro to describing attitudes 2 (solution + new exercise)
    • 2D rotation matrix formulation (solution + new exercise)
    • From 2D to 3D rotations (solution + new exercise)
    • 3D rotation matrix formulation about the Z axis 1 (solution)
    • 3D rotation matrix formulation about the Z axis 2 (solution)
    • Projecting from 3D to 2D (exercise)
    • Projecting from 3D to 2D (solution) + constructing Rx and Ry matrices (exercise)
    • Constructing Ry matrix (solution)
    • Constructing Rx matrix (solution)
    • Orthonormal matrices (exercise)
    • Orthonormal matrices (solution)
    • 3D rotation sequence 1 (exercise)
    • 3D rotation sequence 2 (solution)
    • 3D rotation sequence - example (exercise)
    • 3D rotation sequence - example (solution)
    • Intro to Euler angles (rotation about moving body frames)
    • Intuition on different conventions
    • Fixed VS Moving body frame rotations 1 (exercise)
    • Fixed VS Moving body frame rotations 2 (solution + new exercise)
    • Fixed VS Moving body frame rotations 3 (solution)
    • Rotation matrix conventions - Intro
    • Rotation matrix conventions - R_XYZ matrix product
    • Rotation matrix conventions - R_ZYX matrix product
    • Rotation matrix conventions - R_XYX matrix product
    • Rotation matrix conventions - R_XYZ vs R_ZYX example
    • Rotation matrix conventions - R_XYZ vs R_XYX example
    • Rotation matrix application to the UAV 1
    • Rotation matrix application to the UAV 2
    • Why is a special Transfer matrix needed 1
    • Why is a special Transfer matrix needed 2
    • Why is a special Transfer matrix needed 3
    • Transfer matrix derivation 1 (exercise)
    • Transfer matrix derivation 2 (solution + new exercise)
    • Mathematical derivation of the Rzyx (moving frame) rotation matrix
    • Transfer matrix derivation 4 (solution)
    • Transfer matrix derivation 5
    • Rotation & Transfer matrix application 1 - Kinematics wrap up
    • Rotation & Transfer matrix application 2 - Kinematics wrap up
    • Intro to Dynamics
    • Dot product 1 + Application
    • Dot product 2 +Application
    • Dot product 3 + Application (exercise)
    • Dot product 4 + Application (solution)
    • Cross Product 1
    • Cross Product 2 (Exercise)
    • Cross Product 3 (Solution)
    • Cross Product Application 1
    • Cross Product Application 2 (exercise)
    • Cross Product Application 2 (Solution)
    • Mass moments of inertia & inertia tensor 1
    • Mass moments of inertia & inertia tensor 2 (exercise)
    • Mass moments of inertia & inertia tensor 3 (solution)
    • Mathematical formulas of mass moments of inertia
    • Mathematical formulas of products of inertia
    • Principal axis
    • Mass moment of inertia applied to the UAV
    • Dynamics: Translational Motion (Inertial Frame)
    • Dynamics: Translational Motion (Body Frame) 1
    • Dynamics: Translational Motion (Body Frame) 2
    • Dynamics: Translational Motion (Body Frame) 3
    • Angular momentum VS angular velocity 1
    • Angular momentum VS angular velocity 2
    • Dynamics: Rotational Motion (Inertial frame)
    • Dynamics: Rotational Motion (Body frame) 1
    • Dynamics: Rotational Motion (Body frame) 2
    • Autonomous vehicle lateral acceleration through new lenses
    • Dynamics: Rotational Motion (Body frame) - alternative form (exercise)
    • Dynamics: Rotational Motion (Body frame) - alternative form (solution)

    Specific UAV plant model

    • From 6 DOF Newton-Euler to state-space (exercise)
    • From 6 DOF Newton-Euler to state-space (solution)
    • Applying Force of gravity to the UAV (exercise)
    • Applying Force of gravity to the UAV (solution)
    • Applying control inputs to the UAV (exercise)
    • Gyroscopic effect intuition 1 + control inputs (solution)
    • Gyroscopic effect intuition 2 (exercise)
    • Gyroscopic effect intuition 3 (solution)
    • Gyroscopic effect intuition 4
    • Gyroscopic effect on a UAV intuition 1 (exercise)
    • Gyroscopic effect on a UAV intuition 2 (solution)
    • Gyroscopic effect on a UAV intuition 3
    • Gyroscopic effect on a UAV - Math 1 (exercise)
    • Gyroscopic effect on a UAV - Math 2 (solution)
    • Gyroscopic effect on a UAV - Math 3
    • Gyroscopic effect on a UAV - Math 4
    • From 6 DOF Newton-Euler to state-space - Math 1 (exercise)
    • From 6 DOF Newton-Euler to state-space - Math 2 (solution)
    • UAV plant model schematics 1 (exercise)
    • UAV plant model schematics 2 (solution)
    • Euler state integrator
    • Runge - Kutta integrator 1
    • Runge - Kutta integrator 2
    • Runge - Kutta integrator 3
    • Runge - Kutta integrator 4
    • Runge - Kutta integrator 5
    • Runge - Kutta integrator 6
    • Runge - Kutta integrator 7
    • Runge - Kutta integrator 8
    • From control inputs to rotor angular velocities - blade element theory 1
    • From control inputs to rotor angular velocities - blade element theory 2
    • From control inputs to rotor angular velocities - blade element theory 3
    • From control inputs to rotor angular velocities - blade element theory 4
    • From control inputs to rotor angular velocities - blade element theory 5
    • From control inputs to rotor angular velocities - blade element theory 6
    • From control inputs to rotor angular velocities - blade element theory 7
    • From control inputs to rotor angular velocities - blade element theory 8
    • From control inputs to rotor angular velocities - blade element theory 9
    • From control inputs to rotor angular velocities - blade element theory 10
    • From control inputs to rotor angular velocities - blade element theory 11
    • From control inputs to rotor angular velocities - blade element theory 12
    • From control inputs to rotor angular velocities - blade element theory 13

    Recap of Applied Control Systems 1 - autonomous cars (Math + PID + MPC)

    • Detailed recap 1: car & bicycle lateral equations of motion
    • Detailed recap 2: LTI state - space equations
    • Detailed recap 3: continuous VS discrete LTI
    • Detailed recap 4: system input calculation using Model Predictive Control

    The UAV's global control architecture

    • The global control architecture scheme - Intro
    • The elements of the sequential/cascaded controller
    • Different tasks of each sub-controller
    • The Planner
    • Stronger VS weaker dynamics 1
    • Stronger VS weaker dynamics 2
    • Reference trajectory equations in the planner
    • The affect of the control inputs on future states

    The MPC attitude controller

    • Review of the global control structure
    • Review of the state space equations of the autonomous vehicle
    • The UAV's dynamics and kinematics equations revisited
    • Zero angle roll and pitch assumption 1
    • Zero angle roll and pitch assumption 2
    • Putting the state space equations in the Linear format 1
    • Putting the state space equations in the Linear format 2
    • Putting the state space equations in the Linear format 3
    • Putting the state space equations in the Linear format 4
    • Linear Parameter Varying form 1
    • Linear Parameter Varying form 2
    • Review of the steps from the equations of motion to the plant
    • The dimensions of the state space equation matrices
    • Future state prediction formula 1: simplified LPV-MPC
    • Future state prediction formula 2: simplified LPV-MPC
    • Future state prediction formula 3: nonsimplified LPV-MPC
    • Future state prediction formula 4: nonsimplified LPV-MPC
    • Future state prediction formula 5: nonsimplified LPV-MPC
    • Cost function 1
    • Cost function 2
    • Cost function 3
    • Cost function 4
    • Cost function 5
    • Cost function 6
    • Cost function 7
    • Cost function 8
    • Cost function 9
    • Cost function 10
    • Cost function 11

    Feedback Linearization Controller

    • Equations of motion for position control (inertial frame) - exercise
    • Equations of motion for position control (inertial frame) - solution
    • General feedback control architecture
    • Feedback Linearization Controller schematics - Part 1
    • Differential Equations - intro
    • Differential Equations & the control law
    • Solving differential equations - real roots 1
    • Solving differential equations - real roots 2
    • Solving differential equations - real roots 3
    • Solving differential equations - complex roots 1
    • Solving differential equations - complex roots 2
    • Solving differential equations - complex roots 3
    • Solving differential equations - complex roots 4
    • Using the exponent for controlling a system - exercise
    • Using the exponent for controlling a system - solution
    • Poles & Laplace domain
    • From poles to differential equation constants - exercise
    • From poles to differential equation constants - solution
    • From differential equations to state-space representation
    • Eigenvalues in control engineering & Determinants
    • Computing eigenvectors
    • Laplace VS Fourier frequency domain
    • Moving poles
    • Feedback Linearization Controller schematics - Part 2
    • Simulation results with real & complex poles 1
    • Simulation results with real & complex poles 2
    • Simulation results with real & complex poles 3
    • Feedback Linearization Controller schematics - Part 3
    • Final Stretch - computing the final control inputs - Part 1
    • Final Stretch - computing the final control inputs - Part 2
    • Recommended reading: Great article about Kalman Filters

    The simulation code explanation

    • Intro to (Linux & macOS Terminal) & (Windows Command Prompt)
    • MUST HAVE Matplotlib 3.2.2, NOT Matplotlib 3.3.3
    • Python installation instructions - Ubuntu
    • Python installation instructions - Windows 10
    • Python installation instructions - macOS
    • Simulation analysis & code explanation 1
    • Simulation analysis & code explanation 2
    • Simulation analysis & code explanation 3
    • Simulation analysis & code explanation 4
    • Simulation analysis & code explanation 5
    • Simulation analysis & code explanation 6
    • Simulation analysis & code explanation 7
    • Simulation analysis & code explanation 8
    • Simulation analysis & code explanation 9
    • Simulation analysis & code explanation 10
    • Simulation analysis & code explanation 11
    • Simulation analysis & code explanation 12
    • Simulation analysis & code explanation 13
    • Simulation analysis & code explanation 14
    • Simulation analysis & code explanation 15
    • Basic intro to Python animations tools
    • Simulation codes & course summary document

    Extra: MPC constraints applied to the UAV

    • Recap of MPC constraints in autonomous cars 1
    • Recap of MPC constraints in autonomous cars 2
    • Recap of MPC constraints in autonomous cars 3
    • Recap of MPC constraints in autonomous cars 4
    • Recap of MPC constraints in autonomous cars 5
    • Application of MPC constraints to UAV drone 1
    • Application of MPC constraints to UAV drone 2
    • Application of MPC constraints to UAV drone 3
    • Application of MPC constraints to UAV drone 4
    • Application of MPC constraints to UAV drone 5
    • No solution example (autonomous cars) 1
    • No solution example (autonomous cars) 2
    • Installation of solver libraries - Intro
    • Installation of solver libraries - Ubuntu
    • Installation of solver libraries - Windows 10
    • Installation of solver libraries - MacOS
    • UAV drone Python files WITH MPC constraints
    • MPC constraints for UAV drone - code explanation 1
    • MPC constraints for UAV drone - code explanation 2
    • MPC constraints for UAV drone - code explanation 3
    • MPC constraints for UAV drone - analysis of simulation results

    Last Words

    • Thank You!
    • Well done! You've done it! But don't stop here! Keep going forward!

    Instructors

    Mr Mark Misin

    Mr Mark Misin
    Instructor
    Freelancer

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