- 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.
How to fix the graph step response system (overshoot/peak) in Simulink
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I already trained a Neural Network on MATLAB, after that I want to simulate that into my control design in Simulink. So, I use gensim to generate the NN block to the simulink. After I run the model in Simulink, it shows a bad results in a graph (blue line). How to overcome this overshoot things? Is there anything wrong with my control design?
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Piyush Dubey
2023 年 6 月 27 日
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:
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.
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