Derivative finite-differencing step was artificially reduced to be within bound constraints.

警告: Derivative finite-differencing step was artificially
reduced to be within bound constraints. This may adversely affect convergence. Increasing distance between bound constraints, in dimension 172, to be at least 1.1102e-16 may improve results.

解答：
Also, as the warning message tells you, your bounds are very tight in absolute terms. It would be advisable to change the units of your coefficients so that they, and their bounds, are on the order of 1 instead of 1e-8. Even though the tolerance parameters for lsqnonlin (e.g. StepTolerance, FiniteDifferenceStepSize) and the other toolbox solvers have some ability to divine the scale of your parameters and of your cost function, I find that it’s usually best not to rely on that.

自己的问题上下界距离较小这个问题特点决定的不是我能设置的这可咋办说白了就是原始数据不太好

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Derivative finite-differencing step was artificially reduced to be within bound constraints.

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