Characteristic length and cooling circle
Modular design, outsourcing and open innovation create a complex network of possible end product embodiments in product design for the consumer market. Analyzing each and every possibility in detail is out of the question as resources are limited and module details are often proprietary information. To meet this challenge the thermal engineer needs a feeling about what will and what will not work out, without getting bogged down in too much detail. This paper presents the concepts of characteristic length and cooling circle as an approximate measure for the extent of heat spreading in beam and in flat thin plate geometries. Beam and flat thin plate geometries are widely used by mechanical designers, and being able to assess how much of the geometry is actually thermally affected by a heat source is of great value in thermal decision making and communication. For both geometries an application is discussed and compared to CFD simulations to assess the validity of the approach.
Sense and nonsense thermal requirements [consumer display product example using CFD]
Good thermal requirements form the basis of a good thermal design. Unfortunately, good, workable thermal requirements are a rare commodity. This paper discusses thermal requirements from the setmakers thermal system designer's point of view. Different types of thermal requirements are discussed, and different ways of specification. The famous "max operating ambient" specification is discussed, and a method is presented to get a handle on this difficult specification. The method is demonstrated on CFD calculations on a consumer display product.
L1 Adaptive Controller for Attitude Control of Multirotors
In this work we show an application of L1 Adaptive control theory for attitude control of UAVs. We implement the flight control system on a multirotor to show robustness and precise attitude tracking in the presence of modeling uncertainties and environmental disturbances. We choose backstepping control architecture, since the kinematics and dynamics of multirotors in most cases can be written in strict feedback form. We further exploit the fact that the kinematics of the plant, while free of uncertainties, is nonlinear, which makes it highly suitable for dynamic inversion control at each level of backstepping. On the other hand, plant dynamics is uncertain and is affected by environmental disturbances such as wind gusts, unmodeled dynamics etc. Therefore, we consider 3 variants of the control architecture. The first method uses backstepping to determine the moment demand and augments it with the L1 adaptive controller to account for uncertainties and provide robustness with guaranteed transient performance. The second architecture apply the concept of L1 adaptive backstepping to the same problem; and the third architecture uses L1 backstepping for quaternion representation of the system dynamics, which helps to avoid the singularities associated with Euler angles.