# how can i solve this problem?

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worod 2023년 12월 20일
답변: Sam Chak 2023년 12월 21일

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### 답변 (2개)

Andreas Goser 2023년 12월 21일
With the information given, there is not much to say but to suggest you to do what the message suggests: Reducing the fixed-step size or tightening the error tolerance. If you do not know how to do that - ask that question instead. If it didn't work - try to provide something the community members can reproduce.
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Sam Chak 2023년 12월 21일
FOPID, like the ordinary PID, is a static control architecture. The control parameters require the designer to mathematically set stabilizing values, similar to how the Routh–Hurwitz stability analysis can demonstrate a necessary and sufficient condition for the stability of a linear control system. If destabilizing values are assigned to the control parameters of the FOPID, the system can become highly unstable. This instability may cause certain states to grow exponentially, forcing Simulink to terminate the simulation.
Technical designers typically employ mathematical analysis and formulas, if possible, to determine stabilizing values for control parameters. Alternatively, both technical and non-technical individuals may utilize metaheuristic optimization algorithms, such as the popular Genetic Algorithm (GA) or Particle Swarm Optimization (PSO), allowing the algorithm to autonomously determine values within specified search regions. These regions may encompass both stabilizing and destabilizing values. Throughout iterations and the search for optimal values, the algorithm may inadvertently encounter destabilizing values, leading Simulink to terminate the simulation.
Consider configuring the hyperparameters in gafit() to narrow down the search regions.

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