Fsolve移植问题：MATLAB代码复现结果不符，求解受阻求助

I totally get how frustrating it is to get stuck on this fsolve porting issue—especially after you’ve tried adjusting dimensions to fit the requirements and still aren’t getting matching results. Let’s break down where you might be going wrong and fix this step by step:

1. You’re likely misinterpreting fsolve’s output requirements #

MATLAB’s fsolve doesn’t force you to merge a 6×6 array and 6×1 vector into a single 42×1 array—that’s the core mistake here. Here’s the correct approach depending on what that 6×6 array represents:

• If the 6×6 array is the Jacobian matrix:
  fsolve natively supports returning both the residual vector and Jacobian matrix together. Just enable the Jacobian option:

  options = optimoptions('fsolve', 'Jacobian', 'on');
  [x, fval] = fsolve(@myfun, initial_6x1_vector, options);
  

  Your function should follow this structure:

  function [residual, jacobian] = myfun(x)
      % Compute your 6×1 residual vector
      residual = ...; 
      % Compute your 6×6 Jacobian matrix
      jacobian = ...; 
  end
  

  There’s no need to expand your 6×1 initial point—keep it as is. The solver will handle the Jacobian directly instead of treating it as part of the residual.

• If the 6×6 array is a separate matrix constraint:
  If that 6×6 array needs to satisfy a specific condition (e.g., equal to a zero matrix or target matrix), convert the matrix constraint into a residual vector. Flatten the 6×6 matrix into a 36×1 vector, then concatenate it with your original 6×1 residual to get a 42×1 total residual. Crucially, your initial point stays 6×1—the solver only optimizes the 6 variables you care about, not 42. Expanding the initial point to 42×1 tells fsolve you have 42 variables to solve for, which is not your intent.

2. Validate your target function in isolation #

Before debugging the solver, test your function alone. Feed it the initial point that worked in MATLAB, and check if the output (residual and/or Jacobian) matches exactly what MATLAB returns. If there’s a mismatch here, the problem lies in how you ported the function logic, not the solver setup.

3. Align with MATLAB’s fsolve configuration #

Double-check that you’re using the same solver settings as MATLAB:

• Algorithm (e.g., 'levenberg-marquardt' vs 'trust-region-dogleg')
• Convergence tolerances (TolFun, TolX)
• Maximum iterations (MaxIter)
  Small differences in these settings can lead to divergent results, especially for highly nonlinear problems.

内容的提问来源于stack exchange，提问作者Karan Singh