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OpTaS
1.0.7
An optimization-based task specification library for trajectory optimization and model predictive control.
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OpTaS
1.0.7
An optimization-based task specification library for trajectory optimization and model predictive control.
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Unconstrained Quadratic Program. More...
Public Member Functions | |
| def | __init__ (self, SXContainer decision_variables, SXContainer parameters, SXContainer cost_terms) |
| Initializer for the QuadraticCostUnconstrained class. More... | |
 Public Member Functions inherited from optas.optimization.Optimization | |
| None | set_models (self, List[Model] models) |
| Specify the models in the optimization problem. More... | |
| None | specify_quadratic_cost (self) |
| Specify the terms P and q of a quadratic cost function. More... | |
| None | specify_linear_constraints (self, lin_ineq_constraints, lin_eq_constraints) |
| Setup the constraints k(x, p) = M(p).x + c(p) >= 0, and a(x, p) = A(p).x + b(p) == 0. More... | |
| None | specify_nonlinear_constraints (self, SXContainer ineq_constraints, SXContainer eq_constraints) |
| Setup the constraints g(x, p) >= 0, and h(x, p) == 0. More... | |
| None | specify_v (self, List[cs.Function] ineq=[], List[cs.Function] eq=[]) |
| Specify the vertical constraints vector v. More... | |
| def | has_discrete_variables (self) |
Additional Inherited Members | |
| Public Attributes inherited from optas.optimization.Optimization | |
| models | |
| A list of the task and robot models (set during build method in the OptimizationBuilder class) More... | |
| decision_variables | |
| SXContainer containing decision variables. More... | |
| parameters | |
| SXContainer containing parameters. More... | |
| cost_terms | |
| SXContainer containing cost terms. More... | |
| lin_eq_constraints | |
| SXContainer containing linear equality constraints. More... | |
| lin_ineq_constraints | |
| SXContainer containing linear inequality constraints. More... | |
| eq_constraints | |
| SXContainer containing equality constraints. More... | |
| ineq_constraints | |
| SXContainer containing inequality constraints. More... | |
| P | |
| CasADi function that evaluates the P term in the cost function (note, this only applies to problems with a quadratic cost function). More... | |
| q | |
| CasADi function that evaluates the q term in the cost function (note, this only applies to problems with a quadratic cost function). More... | |
| k | |
| CasADi function that evaluates the linear equality constraints. More... | |
| nk | |
| Number of linear inequality constraints. More... | |
| lbk | |
| Lower bound for the linear inequality constraints (i.e. More... | |
| ubk | |
| Upper bound for the linear inequality constraints (i.e. More... | |
| M | |
| CasADi function that evaluates the M term in the linear inequality constraints. More... | |
| c | |
| CasADi function that evaluates the c term in the linear inequality constraints. More... | |
| a | |
| CasADi function that evaluates the linear equality constraints. More... | |
| na | |
| Number of linear equality constraints. More... | |
| lba | |
| Lower bound for the linear equality constraints (i.e. More... | |
| uba | |
| Upper bound for the linear equality constraints (i.e. More... | |
| A | |
| CasADi function that evaluates the A term in the linear equality constraints. More... | |
| b | |
| CasADi function that evaluates the b term in the linear equality constraints. More... | |
| g | |
| CasADi function that evaluates the inequality constraints. More... | |
| ng | |
| Number of inequality constraints. More... | |
| lbg | |
| Lower bound for the inequality constraints (i.e. More... | |
| ubg | |
| Upper bound for the inequality constraints (i.e. More... | |
| h | |
| CasADi function that evaluates the equality constraints. More... | |
| nh | |
| Number of equality constraints. More... | |
| lbh | |
| Lower bound for the equality constraints (i.e. More... | |
| ubh | |
| Upper bound for the equality constraints (i.e. More... | |
| v | |
| CasADi function that evaluates the constraints as a verticle column (set when specify_v is called), see vertcon. More... | |
| nv | |
| Number of vectorized constraints (see vertcon). More... | |
| lbv | |
| Lower bound for the verticle constraints v (i.e. More... | |
| ubv | |
| Upper bound for the verticle constraints v (i.e. More... | |
| dv | |
| CasADi function that evaluates the Jacobian of the constraints v (set when specify_v is called). More... | |
| ddv | |
| CasADi function that evaluates the Hessian of the constraints v (set when specify_v is called). More... | |
| x | |
| Vectorized decision variables. More... | |
| p | |
| Vectorized parameters. More... | |
| f | |
| CasADi function that evaluates the objective function. More... | |
| df | |
| Jacobian of the objective function. More... | |
| ddf | |
| Hessian of the objective function. More... | |
| nx | |
| Number of decision variables. More... | |
| np | |
| Number of parameters. More... | |
| ddg | |
| ddh | |
| Static Public Attributes inherited from optas.optimization.Optimization | |
| float | inf = 1.0e10 |
| big number rather than np.inf More... | |
Unconstrained Quadratic Program.
min f(x, p) where f(x, p) = x'.P(p).x + x'.q(p)
x
The problem is unconstrained, and has quadratic cost function.
| def optas.optimization.QuadraticCostUnconstrained.__init__ | ( | self, | |
| SXContainer | decision_variables, | ||
| SXContainer | parameters, | ||
| SXContainer | cost_terms | ||
| ) |
Initializer for the QuadraticCostUnconstrained class.
@param decision_variables SXContainer containing decision variables. @param parameters SXContainer containing parameters. @param cost_terms SXContainer containing cost terms (must be quadratic). @return Instance of the QuadraticCostUnconstrained class.
Reimplemented from optas.optimization.Optimization.
1.9.1