control.optimal.OptimalControlResult¶

class control.optimal.OptimalControlResult(ocp, res, return_states=False, print_summary=False, transpose=None, squeeze=None)¶

Bases: OptimizeResult

Result from solving an optimal control problem.

This class is a subclass of scipy.optimize.OptimizeResult with additional attributes associated with solving optimal control problems.

inputs¶

The optimal inputs associated with the optimal control problem.

Type: ndarray

states¶

If return_states was set to true, stores the state trajectory associated with the optimal input.

Type: ndarray

success¶

Whether or not the optimizer exited successful.

Type: bool

problem¶

Optimal control problem that generated this solution.

Type: OptimalControlProblem

cost¶

Final cost of the return solution.

Type: float

system_simulations, {cost, constraint, eqconst}_evaluations

Number of system simulations and evaluations of the cost function, (inequality) constraint function, and equality constraint function performed during the optimzation.

Type: int

{cost, constraint, eqconst}_process_time

If logging was enabled, the amount of time spent evaluating the cost and constraint functions.

Type: float

Methods

`clear`
`copy`
`fromkeys`	Create a new dictionary with keys from iterable and values set to value.
`get`	Return the value for key if key is in the dictionary, else default.
`items`
`keys`
`pop`	If key is not found, d is returned if given, otherwise KeyError is raised
`popitem`	2-tuple; but raise KeyError if D is empty.
`setdefault`	Insert key with a value of default if key is not in the dictionary.
`update`	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`

__contains__(key, /)¶: True if the dictionary has the specified key, else False.

__delattr__(key, /)¶: Delete self[key].

__delitem__(key, /)¶: Delete self[key].

__dir__()¶: Default dir() implementation.

__eq__(value, /)¶: Return self==value.

__ge__(value, /)¶: Return self>=value.

__getattribute__(name, /)¶: Return getattr(self, name).

__getitem__()¶: x.__getitem__(y) <==> x[y]

__gt__(value, /)¶: Return self>value.

__hash__ = None¶

__iter__()¶: Implement iter(self).

__le__(value, /)¶: Return self<=value.

__len__()¶: Return len(self).

__lt__(value, /)¶: Return self<value.

__ne__(value, /)¶: Return self!=value.

__new__(**kwargs)¶

__setattr__(key, value, /)¶: Set self[key] to value.

__setitem__(key, value, /)¶: Set self[key] to value.

__sizeof__() → size of D in memory, in bytes¶

clear() → None. Remove all items from D.¶

copy() → a shallow copy of D¶

fromkeys(value=None, /)¶: Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)¶: Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items¶

keys() → a set-like object providing a view on D's keys¶

pop(k[, d]) → v, remove specified key and return the corresponding value.¶: If key is not found, d is returned if given, otherwise KeyError is raised

popitem() → (k, v), remove and return some (key, value) pair as a¶: 2-tuple; but raise KeyError if D is empty.

setdefault(key, default=None, /)¶

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None. Update D from dict/iterable E and F.¶: If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values¶