Magnetic suspension small sphere control experiment table based on model design and automatic code generation

Abstract

The invention discloses a magnetic suspension small sphere control experiment table based on model design and automatic code generation. The magnetic suspension small sphere control experiment table comprises a mechanical part and an electric part, wherein the mechanical part is a magnetic suspension small sphere device; the electric part comprises a PC (Personal Computer) machine, a simulator, a real-time embedded controller, a power amplifier and an eddy current displacement sensor; the PC machine is taken as a host, is based on a physical model design control system and code generation, and is used for downloading into the real-time controller through the simulator; the output of the controller passes through the power amplifier in order to control the coil current of a magnetic suspension small sphere device; the eddy current displacement sensor is used for acquiring the position information of a small sphere, feeding back the position information to the controller, and controlling the small sphere through a closed loop. Through the combination of the magnetic suspension small sphere and a control system development method based on the model and an automatic code generation technology, a good experiment platform is provided for control theory learning, and the magnetic suspension small sphere control experiment table has the characteristics of short control system development time, low cost and the like.

Description

technical field [0001] The invention belongs to the technical field of magnetic levitation, and in particular relates to a magnetic levitation ball control experiment platform based on model design and automatic code generation. Background technique [0002] In recent years, with the rapid development of various industries and industries, the market's demand and requirements for equipment have greatly increased, so the complexity of equipment has also greatly increased, which is specifically reflected in the requirement for equipment to have better performance in high-speed and high-precision performance. The corresponding control objects reflect a greater degree of nonlinear and time-varying problems, and these problems have stricter requirements on the control system. Therefore, the design and development of the control system and new superior control algorithms are also facing great challenges. [0003] The complex nonlinear time-varying system embodied by the above-menti...

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Problems solved by technology

[0002] In recent years, with the rapid development of various industries and industries, the market's demand and requirements for equipment have greatly increased, so the complexity of equipment has also greatly increased, which is specifically reflected in the requirement for equipment to have better performance in high-speed and high-precision performance. The corresponding control objects reflect a greater degree of nonlinear and time-varying problems. These problems have stricter requirements on the control system. Therefore, the design and development of the control system and new superior control algorithms are also facing great challenges.

[0003] The complex nonlinear time-varying system embodied by the above-mentioned control objects makes it difficult or even impossible to establish a system model. However, classical control theory and modern control theory are helpless for the above-mentioned problems due to the precise model requirements of the controlled objects. Therefore, the "intelligent control" theory At present, intelligent control has developed theories and application methods such as expert system, fuzzy control, and neural control, but it is not mature enough, so it is necessary to continue in-depth research on intelligent control.

[0004] Regardless of traditional control theory, modern control theory, or intelligent control methods, simulation is a good way to research and verify the development and design of control systems and control algorithms, but currently there is a widespread separation of simulation research and control implementation. This makes the control algorithm theoretically ahead of the specific application, and there are shortcomings and limitations in solving practical control problems, which also slows down the pace of practical application of the theory.

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