
Rajan Bhandari- Auburn University
Rajan Bhandari
- Auburn University
About
12
Publications
4,799
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
66
Citations
Introduction
Skills and Expertise
Current institution
Publications
Publications (12)
This paper describes the flight test validation of a Trajectory Control System on a subscale lift-plus-cruise vertical takeoff and landing urban air mobility aircraft concept. The aircraft was sized using the Parametric Energy-based Aircraft Configuration Evaluator framework. A simulation model was developed using the Modular Aircraft Dynamics and...
The ongoing development of numerous novel vertical takeoff and landing configurations necessitates flight control system design that enables the Simplified Vehicle Operations paradigm. This paper shows flight test results for one subscale lift-plus-cruise and one tilt-wing configuration employing such a flight control system architecture. Pilot inc...
Conventional aircraft sizing methods face challenges in analyzing all-electric or hybrid-electric novel aircraft configurations, such as those for urban air mobility applications. The vast design space containing both continuous and discrete design variables and competing design objectives necessitates searching for not necessarily a unique optimal...
This work investigates the simplified vehicle operations paradigm, which seeks significant reductions in pilot workload and training requirements through the holistic design of flight control laws, control inceptors, and cockpit displays in the context of vertical takeoff and landing urban air mobility aircraft using piloted flight simulations. Two...
This paper describes the application of a research and development pipeline at the Vehicle Systems, Dynamics, and Design Laboratory to the design, fabrication, and flight testing of a subscale lift-plus-cruise vertical takeoff and landing urban air mobility aircraft concept. The aircraft was sized using the Parametric Energy-based Aircraft Configur...
Questions
Questions (4)
I have been using gamultiobj in Matlab to run my optimization setup. When the GA calls the fitness function it only sends the population to the fitness function as its input. But, I need also the generation to which the population belong. How could that be done as I am not able to edit the Matlab inbuilt functions.
I have running GA optimization using "gamultiobj" in Matlab. The upper bound and lower bound of my design variables are like [10 30 175 1] and [30 60 225 3]. But after convergence, I see the design variables (like all of them) near 20,47,175 and 1. I am not getting a Pareto Front. What could be the possible reasons for that?
I could not find how the "gamultiobj" (a NSGA-II algorithm) penalizes the fitness function for the population violating constraints? Any clues would be appreciated.
Thank you!
I do not find anywhere to use the mutation probability. Any sort of help is appreciated.
Thank you!