scholarly journals Design and optimal control of a tiltrotor micro-aerial vehicle for efficient omnidirectional flight

2020 ◽  
Vol 39 (10-11) ◽  
pp. 1305-1325
Author(s):  
Mike Allenspach ◽  
Karen Bodie ◽  
Maximilian Brunner ◽  
Luca Rinsoz ◽  
Zachary Taylor ◽  
...  
Keyword(s):  
Optimal Control ◽  
Design Optimization ◽  
System Design ◽  
Optimal Controller ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Robust System ◽  
Six Degree Of Freedom ◽  
Allocation Approach

Omnidirectional micro-aerial vehicles (MAVs) are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and high hover efficiency have been developed independently, a robust system that combines the two has not been demonstrated to date. This paper presents the design and optimal control of a novel omnidirectional vehicle that can exert a wrench in any orientation while maintaining efficient flight configurations. The system design is motivated by the result of a morphology design optimization. A six-degree-of-freedom optimal controller is derived, with an actuator allocation approach that implements task prioritization, and is robust to singularities. Flight experiments demonstrate and verify the system’s capabilities.

Combined Plant and Controller Design Using Decomposition-Based Design Optimization and the Minimum Principle

2010 ◽  
Author(s):  
James T. Allison ◽  
Sam Nazari
Keyword(s):  
Optimal Control ◽  
Design Optimization ◽  
System Design ◽  
Physical System ◽  
Design Problem ◽  
Controller Design ◽  
Minimum Principle ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Augmented Lagrangian Coordination

An often cited motivation for using decomposition-based optimization methods to solve engineering system design problems is the ability to apply discipline-specific optimization techniques. For example, structural optimization methods have been employed within a more general system design optimization framework. We propose an extension of this principle to a new domain: control design. The simultaneous design of a physical system and its controller is addressed here using a decomposition-based approach. An optimization subproblem is defined for both the physical system (i.e., plant) design and the control system design. The plant subproblem is solved using a general optimization algorithm, while the controls subproblem is solved using a new approach based on optimal control theory. The optimal control solution, which is derived using the the Minimum Principle of Pontryagin (PMP), accounts for coupling between plant and controller design by managing additional variables and penalty terms required for system coordination. Augmented Lagrangian Coordination is used to solve the system design problem, and is demonstrated using a circuit design problem.

scholarly journals Analysis of resonant propulsion flapping wing micro aerial vehicle

2020 ◽  
pp. 327-345
Author(s):  
Kun Feng ◽  
Krzysztof Sibilski
Keyword(s):  
Mathematical Models ◽  
Insect Flight ◽  
Flapping Wing ◽  
Micro Aerial Vehicles ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Resonant Property

This article is concerned with the resonant property which is exhibited in insect flight, and analyzes how resonant propulsion works when implemented in powering a flapping wing micro aerial vehicle. This article is divided into three parts. In the first part, information regarding to insect flight, the resonant property, and flapping wing micro aerial vehicles are described. In the second part, mathematical models representing the micro aerial vehicle (basing on the model developed by Bolsman) are applied, simplified and built into simulation in MATLAB. Some interesting properties from the simulations are presented.

Zero Dynamics Study of a Model Helicopter Considering the Effect of Control Point

2008 ◽  
Author(s):  
Mehdi Saffarian ◽  
Farbod Fahimi
Keyword(s):  
Control Strategies ◽  
Control Point ◽  
Design Parameters ◽  
Zero Dynamics ◽  
Aerial Vehicles ◽  
Inertial Parameters ◽  
Model Helicopter ◽  
Aerial Vehicle ◽  
Autonomous Helicopter ◽  
Six Degree Of Freedom

Zero dynamics of a helicopter system is modeled in this study with respect to the control point’s tracking path. The derivation is comprehensive and has been done for the most general flying maneuvers. The approach is based on a six Degree of Freedom (DoF) model of the helicopter’s body, the configuration of the aerodynamic traction, and the geometrical and inertial parameters of the helicopter. Considering the vast grows in the field of Autonomous Aerial Vehicle (UAV), this study can be utilized both for improving the design parameters of an aerial platform, deriving the feasible maneuvering scenarios and working regimes for available systems. Also, the study provides a platform to test the performance and stability of the control strategies for autonomous helicopter systems and other aerial vehicles.

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