UAM - Flight Trajectory Control and Optimization

Epistemic Review

Confidence: 71%

Sources

• Coursera TUM MOOC - Urban Air Mobility, taught by Dr. Luis Rodriguez
• Cost Index - IVAO Documentation Library for understanding the meaning of cost index

To-do

• Understand the system architecture flowchart well
• Write on the RRT-star algorithm and PID Control
• Find out about gain adaptation using neural networks

Trajectory Planning and Optimization

There are 4 systems involved in the planning and optimization of the trajectories of eVTOLs in a UAM system

System	Function
Flight Management System (FMS)	Develop and manage eVTOL operations and keep track of flight schedules Minimizes the cost of energy and the cost of time
Flight Control System (FCS)	Control and track eVTOL trajectories
Traffic Management System (TMS)	Monitor and prevent collisions between eVTOLs
Energy Management System (EMS)	Control and improve the energy usage of eVTOLs

Important considerations for UAM control

• High travel efficiency
• Accounting for a time-varying environment with dynamic obstacles - The scenario may change frequently, with moving obstacles, changing weather etc.
• Accounting for multiple other eVTOLs - Multi-agent systems
• Adaptive planning and prediction of future environments

graph LR

A["FMS"]
B["EMS"]
C["FCS"]
D["Vehicle"]
E["TMS"]
F["Other vehicles"]

A --> B --> C --> D
A <--> E 
F --> E
A <--> D
A -->|Hybrid| C

The FMS essentially expresses an optimal control problem

$$C_{\text{net}}=C_{e}E+C_{t}T$$

Where $C_{\text{net}}$ is the total cost, $C_e$ is the cost per energy unit, $C_t$ is the cost per time spent, $E$ is the total energy used, and $T$ is the total time spent. The aforementioned objective function must be optimized. This is a multi-objective optimization problem and the solutions are represented as a Pareto curve

Cost Index $C_I=\frac{C_t}{C_e}$

Note

It might be confusing at first. A lower $C_e$ implies lower energy costs and yet $C_I$ becomes higher. How so?

The faster the speed of the aircraft, the greater the rate of fuel consumption, which is pretty much an increase in $C_e$

For trajectory collision avoidance, the RRT-star algorithm is predominantly used

Flight Control Systems

PID Control is commonly used for flight control

graph LR

A["Yaw/Pitch/Roll error"]
B["PID"]
C["Yaw/Pitch/Roll torque"]

A --> B --> C

Major players in Quebec

• The Ambular Project
• Canadian Advanced Air Mobility Consortium (CAAM)
• Aero Montreal
• CRIAQ
• Montreal Aerospace Institutes (MAI)