In this study we present a new free tool-chain for model based control design for mechatronic plants applicable to small embedded systems based among other software on the open simulator Scilab-XCos. After a very short introduction of model based design terms this article focuses on the code generator and the other programs of the tool-chain. The design concept is demonstrated by an adaptive self tuning control (STC) of the cart and pendulum system in gantry crane configuration in simulation and on a real laboratory experiment.Index terms: open source, code generation, Scilab-XCos, model based control, parameter identification, embedded systems I. INTRODUCTIONModel-based design (MBD) is a mathematical and visual method of addressing problems associated with designing complex control, signal processing and communication systems. It is used in many motion control, industrial equipment, aerospace, and automotive applications. Model-based design is a methodology applied in designing embedded software. During the past years there is a growing interest of more and more medium to small size engineering companies in order to cut down development time and costs. Common tool-chains are quite expensive commercial solutions due to the origin of MBD in aerospace and automotive industries.Commercial code generators for Matlab-Simulink (M&S) -one of the most complete tool-chains in MBD -, Dymola, etc. do exist. On the other hand, INRIA and others provide free code generators for the outdated Scilab-Scicos -an open source pendant of M&S, e.g., [2], [3], and some more. Scilab-XCos made a major development step concerning the user interface in the last two years but unfortunately the former free code generators do not work anymore. To the best knowledge of the authors there is only one commercial implementation for the new Scilab-XCos suitable for embedded systems.The main idea presented in this paper is the MBD control development for mechatronic plants with a complete free (or low-cost if target hardware is included) tool-chain from the modeling and control design to the hardware realization using an integrated development environment (IDE). Possible fields of application for such a low-cost development toolchain are teaching courses and companies interested in testing this new technology or dealing with MBD projects of moderate complexity.

Often, trajectories for mechanical systems are generated solving some optimization problem. Common approaches include time-optimal, energy optimal, etc., motion profiles. In order to decrease mechanical wear of real plants this profiles provide, e.g., a smooth movement (rest-to-rest) in accordance with restrictions in jerk, acceleration and velocity. There exists a number of methods, to calculate for a given trajectory the plant feed forward action and to design stabilizing controllers. In case of parameter uncertainty the control law often exhibits some adaptive part. Unfortunately, smooth trajectories tend to contain insufficient excitation for adaption and/or identification. Therefore, we propose to consider some measure for the information content concerning some unknown parameters in the trajectory optimization problem.

In this paper we present free tools for model-based optimal input design and parameter estimation. The discussed tool-chain is tailored for the needs of small-and medium sized companies. Its programming core is based on Scilab and the JModelica platform and features input design (DOE), optimal control problems (OCP), and parameter estimation. Finally, the entire tool-chain concept is tested via simulation of a cart and pendulum system.

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In this paper we present a free tool for semi-automated matching of virtual and real prototypes in a wide range of industrial applications. Within the introduction we would like to explain the motivation behind the development of our tool. After a short description of the basic principles of input design for dynamical systems, we are focusing on the individual steps of the tool-chain, implemented in our software.