I don’t know what’s the best way to explain it, but basically I am unable to solve an optimization problem with function quadprog and active-set algorithm while interior-point did it with no problems. The exit flag that I get is 0 (The maximum number of iterations was reached. Solution x might be suboptimal or infeasible). I don’t understand, since the only thing that changes from the interior-point case is the fact that I now have to give an initial value as input. I don’t see why it would be the number of iterations either, I’ve already tried to increase it. I have also tried to debug it but when I try to step into the asqpdense function it takes me to the optimget function, so I don´t really know what is going on.
My code is a little extense and it calls many custom functions, so I don´t know what´s the best way upload it here. It is a MPC problem based on the code provided in GitHub – ARMSLab/slmpc: Successive Linearization Model Predictive Control and explained in Successive linearization based model predictive control of variable stiffness actuated robots | IEEE Conference Publication | IEEE Xplore. It seems that I need to have the solver options set to use the active-set algorithm in order to generate code (which I need), so that’s why I am trying to make active-set work.I don’t know what’s the best way to explain it, but basically I am unable to solve an optimization problem with function quadprog and active-set algorithm while interior-point did it with no problems. The exit flag that I get is 0 (The maximum number of iterations was reached. Solution x might be suboptimal or infeasible). I don’t understand, since the only thing that changes from the interior-point case is the fact that I now have to give an initial value as input. I don’t see why it would be the number of iterations either, I’ve already tried to increase it. I have also tried to debug it but when I try to step into the asqpdense function it takes me to the optimget function, so I don´t really know what is going on.
My code is a little extense and it calls many custom functions, so I don´t know what´s the best way upload it here. It is a MPC problem based on the code provided in GitHub – ARMSLab/slmpc: Successive Linearization Model Predictive Control and explained in Successive linearization based model predictive control of variable stiffness actuated robots | IEEE Conference Publication | IEEE Xplore. It seems that I need to have the solver options set to use the active-set algorithm in order to generate code (which I need), so that’s why I am trying to make active-set work. I don’t know what’s the best way to explain it, but basically I am unable to solve an optimization problem with function quadprog and active-set algorithm while interior-point did it with no problems. The exit flag that I get is 0 (The maximum number of iterations was reached. Solution x might be suboptimal or infeasible). I don’t understand, since the only thing that changes from the interior-point case is the fact that I now have to give an initial value as input. I don’t see why it would be the number of iterations either, I’ve already tried to increase it. I have also tried to debug it but when I try to step into the asqpdense function it takes me to the optimget function, so I don´t really know what is going on.
My code is a little extense and it calls many custom functions, so I don´t know what´s the best way upload it here. It is a MPC problem based on the code provided in GitHub – ARMSLab/slmpc: Successive Linearization Model Predictive Control and explained in Successive linearization based model predictive control of variable stiffness actuated robots | IEEE Conference Publication | IEEE Xplore. It seems that I need to have the solver options set to use the active-set algorithm in order to generate code (which I need), so that’s why I am trying to make active-set work. mpc, quadprog, active-set, optimization, asqpdense MATLAB Answers — New Questions

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