Hi Agnes,
The control design of your Neural Network can be modified or normalized to restrict the output within a given range. Alternatively, there are ways by which the scope block can be tweaked to incorporate the overshot range encountered while running your model.
These are as follows:
- Tune controller parameters: This step involves adjusting the gains of the controller to optimize the system's performance. You can use various methods like trial and error, Ziegler-Nichols method, or model-based tuning techniques.
- Using anti-windup mechanism: Anti-windup mechanisms are designed to limit the integrator output when the actuator saturates or reaches its limits. This prevents the accumulation of excessive control action during saturation, reducing overshoot.
- Apply filtering: Filters can help reduce the impact of rapid changes in the system, which can lead to overshoot. Low-pass filters are commonly used to eliminate high-frequency noise.
Please refer to the following documentation to get insights on how scope can be configured to adapt to variety of visualizations: https://www.mathworks.com/help/dsp/ug/configure-time-scope.html
Hope this helps.
