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PyDiffGame is a Python implementation of a Nash Equilibrium solution to Differential Games, based on a reduction of Game Hamilton-Bellman-Jacobi (GHJB) equations to Game Algebraic and Differential Riccati equations, associated with Multi-Objective Dynamical Control Systems

Home Page: https://krichelj.github.io/PyDiffGame/

License: MIT License

Python 100.00%
control-theory riccati-equation differential-game quadrotor multi-objective-optimization matrix-equations differential-equations game-theory bellman-equation hamiltonian

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pydiffgame's Issues

Closed loop finite horizon state space simulation is displays non-physical behavior

Even though solving for the matrix P does provide a reasonable solution,
simulating the result with a corresponding state space does not produce
a reasonable behavior.

This could be due to numerical difficulties during solving caused by the
the numbers in the given example or due to a problem in the model.

Suggested:

  • Try different examples
  • Refactor mode

Control Theory Explanations

Add additional explanations on Control Theory notions, such as closed and open loop, Riccati equation, etc

Add References

Add references to additional packages and mathematical description

DataType error and the following ones

When I tried to run InvertedPendulum.py, I was encountered with the problem

self._m = self._B.shape[1]
AttributeError: 'list' object has no attribute 'shape'

then I changed this sentence into

self._n = len(self._A)#self._A.shape[0]
self._m = len(self._B[0])#self._B.shape[1]

then here came another problem:

File "D:\codes/py_codes/PyDiffGame-master/src\PyDiffGame\PyDiffGame.py", line 466, in __get_are_P_f
P_f_i = are_solver(self._A, B_i, Q_i, R_ii)
File "D:\Software\anaconda\lib\site-packages\scipy\linalg_solvers.py", line 444, in solve_continuous_are
a, b, q, r, e, s, m, n, r_or_c, gen_are = _are_validate_args(
File "D:\Software\anaconda\lib\site-packages\scipy\linalg_solvers.py", line 797, in _are_validate_args
m, n = b.shape
ValueError: too many values to unpack (expected 2)

Could you please tell me how to solve these problems? Thanks for you.

python3 test.py err

in line 172 in PyDiffGame.py should it be as:
A_cl = self.__A - SP_sum
to make A be found by object.

While thanks for your graceful work,I'm new to the diffgame, please could tell more about the differential equation the example used? As dx/dt = Ax + Bu,the meaning in reality?
Could you please give some advice about how to deal with the pursuit/evasion scenarios like two cars with acc and thi controlling?

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