OpTaS  1.0.7
An optimization-based task specification library for trajectory optimization and model predictive control.
Public Member Functions | List of all members
optas.optimization.QuadraticCostUnconstrained Class Reference

Unconstrained Quadratic Program. More...

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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...
 

Detailed Description

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.

Constructor & Destructor Documentation

◆ __init__()

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.


The documentation for this class was generated from the following file: