Re: [python-control-discuss] forced response problem for large dt

[Richard M. <mu...@cd...>]

At one point in time we were doing the simulations in control.forced_response differently, using the scipy.integrate.odeint() function.  A brief discussion is here:

  https://github.com/python-control/python-control/issues/48

plus look at the changes here

  https://github.com/python-control/python-control/commit/d7d278ba6072fce1ef28402b7580ffa698424f76#diff-e216ba2d66c950242b1475a045e3cd33

So one other possibility, separate from you quick fix, would be to call scipy.integrate.odeint().


-richard

> On 4 Dec 15, at 13:21, Ryan Krauss <rk...@si...> wrote:
> 
> Apparently I don't know which email list is subscribed.  Sorry if this comes through more than once.
> 
> I am teaching a classical controls class for mechanical engineering undergraduates.  Up till now, I have tried to gloss over state-space.  My students need to do an initial condition simulation for a system that includes actuator saturation.  I have them do this by integrating for one time step at a time using control.forced_response inside a for loop.  We are essentially doing a continuous time approximation of ZOH with the input held constant for each time step.  As the time step gets too large, sp.linalg.expm has to use a higher order pade approximation and eventually throws this error:
> 
> ValueError                                Traceback (most recent call last)
> 
> /Users/rkrauss/git/python-control/zumo_PID_simulation_modified_ss.py in <module>()
> 
>     103     t0 = dt*(i-1)
> 
>     104     t1 = dt*i
> 
> --> 105     to, yo, xo = control.forced_response(G_int, [t0,t1], [v[i],v[i]], X0=X0)
> 
>     106     X0 = xo[:,-1]#<-- save for next time through for loop
> 
>     107     x[i] = squeeze(X0)
> 
> 
> 
> /Users/rkrauss/git/python-control/control/timeresp.pyc in forced_response(sys, T, U, X0, transpose)
> 
>     374                          [np.zeros((n_inputs, n_states + 2 * n_inputs))]])
> 
>     375             print('M=' + str(M))
> 
> --> 376             expM = sp.linalg.expm(M)
> 
>     377             Ad = expM[:n_states, :n_states]
> 
>     378             Bd1 = expM[:n_states, n_states+n_inputs:]
> 
> 
> 
> /usr/local/lib/python2.7/site-packages/scipy/linalg/matfuncs.pyc in expm(A, q)
> 
>     258     # Input checking and conversion is provided by sparse.linalg.expm().
> 
>     259     import scipy.sparse.linalg
> 
> --> 260     return scipy.sparse.linalg.expm(A)
> 
>     261 
> 
>     262 
> 
> 
> 
> /usr/local/lib/python2.7/site-packages/scipy/sparse/linalg/matfuncs.pyc in expm(A)
> 
>     580 
> 
>     581     """
> 
> --> 582     return _expm(A, use_exact_onenorm='auto')
> 
>     583 
> 
>     584 
> 
> 
> 
> /usr/local/lib/python2.7/site-packages/scipy/sparse/linalg/matfuncs.pyc in _expm(A, use_exact_onenorm)
> 
>     635     if structure == UPPER_TRIANGULAR:
> 
>     636         # Invoke Code Fragment 2.1.
> 
> --> 637         X = _fragment_2_1(X, h.A, s)
> 
>     638     else:
> 
>     639         # X = r_13(A)^(2^s) by repeated squaring.
> 
> 
> 
> /usr/local/lib/python2.7/site-packages/scipy/sparse/linalg/matfuncs.pyc in _fragment_2_1(X, T, s)
> 
>     753     exp_diag = np.exp(scale * diag_T)
> 
>     754     for k in range(n):
> 
> --> 755         X[k, k] = exp_diag[k]
> 
>     756 
> 
>     757     for i in range(s-1, -1, -1):
> 
> 
> 
> ValueError: setting an array element with a sequence.
> 
> 
> 
> This is probably ultimately a problem for the scipy people, but my students' project is due in 6 days.  Any suggestions to quickly get the attached simulation code to work for 60Hz simulation, i.e. dt = 1.0/60?
> 
> 
> 
> Thanks,
> 
> 
> 
> Ryan
> 
> 
> --
> Ryan Krauss, Ph.D.
> Associate Professor
> Mechanical Engineering
> Southern Illinois University Edwardsville
> <kp_0_3_rotate_only_less_delay.csv><zumo_PID_simulation_modified_ss.py>------------------------------------------------------------------------------
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