Model order reduction techniques are methods used to simplify complex mathematical models while retaining their essential characteristics. These techniques are vital for reducing computational costs, making simulations and analyses more efficient, especially in the context of soft robot dynamics where the systems can be highly nonlinear and exhibit complicated behaviors.
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