The main goal of this paper is to illustrate the development of a satellite attitude simulator testbed for on-ground experimentation of attitude, determination, and control methodologies. This setup aims to be a low-cost alternative to testbeds based on air-bearing couplings. Our system is mainly composed of a suspended base, a single-board processor, a set of reaction wheels, and a battery. The suspension system entails a set of thin high-tensile strength wires converging on a single wire, which is in turn connected to the base. This configuration allows a three degrees-of-freedom rotation range and minimal resistive torque in all the rotations axis. The adjustability of the hanging point at the base, and a set of sliding masses, allow us to achieve a quite accurate superposition of rotation point and center of mass for a quasi-neutral equilibrium. The testbed is completed by a PC workstation, to generate and stream the desired angular rates of the wheels, and a motion capture system for attitude determination.
In this paper we propose a set of guidelines to select a solver for the solution of nonlinear programming problems. With this in mind, we present a comparison of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems. The comparison involves accuracy, convergence rate, and convergence speed. Because of its popularity among research teams in academia and industry, MATLAB is used as common implementation platform for the solvers. Our study includes solvers which are either freely available, or require a license, or are fully described in literature. In addition, we differentiate solvers if they allow the selection of different optimal search methods. As result, we examine the performances of 23 algorithms to solve 60 benchmark problems. To enrich our analysis, we will describe how, and to what extent, convergence speed and accuracy can be improved by changing the inner settings of each solver.
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