Python Codes for Advanced Control
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Python 3.7.x
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cvxpy 1.0.x
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ecos 2.0.7
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cvxopt 1.2.x
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scipy 1.1.0
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numpy 1.15.0
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matplotlib 2.2.2
This is a sample code of Linear-Quadratic Regulator
This is LQR regulator simulation.
This is LQR tracking simulation.
This is a finite horizon optimal control sample code
This is a sample code of a simple Model Predictive Control (MPC) regulator simulation
This is a sample code of a Model Predictive Control (MPC) traget tracking simulation
This is a sample code for model predictive control optimization modeling without any modeling tool (e.g cvxpy)
This means it only use a solver (cvxopt) for MPC optimization.
It includes two MPC optimization functions:
1 opt_mpc_with_input_const()
It can be applied input constraints (not state constraints).
2 opt_mpc_with_state_const()
It can be applied state constraints and input constraints.
This figure is a comparison of MPC results with and without modeling tool.
This is a inverted pendulum mpc control simulation.
This is a API compatible function of MATLAB c2d function.