Python implementation of trajectory optimization for swinging up an inverted pendulum.
Optimal Trajectory is found by solving a nonlinear programming optimization problem, using actuator effor as the cost function. The dynamics constraints are decomposed into equality constraints by using trapezoidal collocation[1], and the cost function is also discretized. The NLP problem is then solved using scipy-optimize.
[1] "https://epubs.siam.org/doi/pdf/10.1137/16M1062569"
