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View Code? Open in Web Editor NEWA Model Predictive Control (MPC) Python library based on the OSQP solver.
Home Page: http://www.marcoforgione.it/pyMPC
License: MIT License
A Model Predictive Control (MPC) Python library based on the OSQP solver.
Home Page: http://www.marcoforgione.it/pyMPC
License: MIT License
Hello,
I am using this repo to control a race car around a track. I've been debugging like crazy, yet the solver always outputs the steering angle as zero. I linearize the dynamics at each time step, so i have to change the matrices A and B at every time step. How can i do it with the given API?
lineq_du = np.ones((Nc+1) * nu)*Dumin
lineq_du[0:nu] += self.uminus1[0:nu] # works for nonscalar u?
This section of cod didn't work if we didn't have scalar inputs. I tried to set a disturbance as input that we can't control, but I have a problem with this part of your code that.
Could you help me, please?
Hello
Could you please suggest some reference books or academic papers on sparse QP formulation, specifically focusing on the input increment terms (ΔuQΔu)?
Thank you very much!
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