The increasing need for testing and prototyping designs under more realistic conditions is responsible for the advancement of new types of simulation. In this scenario, one type of simulation which has gained high notoriety and applicability is the one known as Hardware-in-the-Loop (HIL). This technique allows real and virtual components of a system to be tested together, making it possible to perform tests under realistic (and even extreme) conditions without harming the real system or a prototype built only for testing. The objective of this work was to develop a low-cost HIL simulation platform to be used for many different applications, unlike most commercial ones, that are developed for one exclusive field of application, such as automotive, aerospace, power electronics, among others. Thus, the main contribution of this work is the project of a HIL platform capable of simulating different types of systems, making it possible to validate embedded control strategies designed for them. Two different applications are tested in order to validate the HIL platform: an active suspension and a satellite attitude control air bearing table, both controlled using a discrete Linear Quadratic Regulator (LQR) designed for each of them.INDEX TERMS Active suspension systems, control systems, hardware-in-the-loop, satellite attitude control.

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Model predictive control is increasingly becoming a popular control strategy for a wide range of applications in both industry and academia, mainly motivated by its ability to systematically handle constraints imposed on a system, regardless of its nature. However, this generates high computational demands, limiting the applicability of model predictive control. Field-programmable gate arrays are reconfigurable hardware platforms that allow the parallel implementation of model predictive control, accelerating such algorithms, but most works found in the literature opt to use high-level synthesis tools and fixed-point numeric representation to generate embedded controllers, resulting in faster-designed solutions but not exactly efficient and flexible ones, that can be applied to different scenarios. Regarding such matter, this work proposes the manual implementation (register-transfer level implementation) of linear model predictive control and the usage of floating-point numeric representation applied to a quadrotor system. The initial results obtained using the proposed controller are presented in this article, achieving 29.34 ms of calculation time at 50 MHz for the attitude control of a quadrotor model containing twelve states and four control outputs.