Closed-loop simulation between mechanical and control development environments can help drive design decisions for both the mechanical and control aspects of the design. For example, engineers may choose to replace a ball-screw stage with a linear motor when they discover the given load cannot be moved at the rate they want. They also can check for mechanical interference in the system, accounting for loads on the system and the control algorithm used. On the control side, engineers may choose to use PID with velocity feed-forward instead of regular PID to achieve better control. They also may want to replace PID with fuzzy logic or Model-Free Adaptive control for controlling nonlinear or higher-order systems.
Making decisions such as these on the mechanical and control sides gives engineers a streamlined machine design process. With fewer iterations needed through a physical prototype, engineers can get to market faster and at a lower cost. Virtual prototyping of both mechanical and control designs helps engineers develop proofs of concept before physical prototypes. They can check their control algorithm logic without risking damage to a physical system. Given that the dynamics of the system are accurately modeled, engineers can fine-tune algorithms against high-fidelity simulation.
Making decisions such as these on the mechanical and control sides gives engineers a streamlined machine design process. With fewer iterations needed through a physical prototype, engineers can get to market faster and at a lower cost. Virtual prototyping of both mechanical and control designs helps engineers develop proofs of concept before physical prototypes. They can check their control algorithm logic without risking damage to a physical system. Given that the dynamics of the system are accurately modeled, engineers can fine-tune algorithms against high-fidelity simulation.
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Figure 6. Closed-loop simulation of a mechanical system with a PID algorithm shows the difference in settling times of a badly tuned and a well-tuned PID algorithm. Closed-loop simulations also require less energy to drive the system and result in smoother motion for longer machine life.
The NI SoftMotion Development Module for LabVIEW includes functions for trajectory generation, spline interpolation, and enhanced motion PID that engineers can use to simulate a complete custom motion controller in LabVIEW. With NI SoftMotion functions in LabVIEW, engineers can even create a closed-loop simulation of a multiaxis stage designed in SolidWorks/COSMOSMotion.
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Figure 7. The NI SoftMotion Development Module for LabVIEW provides engineers with functions like trajectory generation and spline interpolation to create closed-loop simulation of multiaxis systems like an XY stage with SolidWorks/COSMOSMotion.
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