LQRContinuous - MapleSim Help
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ControlDesign

  

LQRContinuous

  

design continuous-time linear quadratic state feedback regulator (LQR) for a given pair

 

Calling Sequence

Parameters

Options

Solvability Conditions

Description

Examples

Calling Sequence

LQRContinuous(A, B, Q, R, opts)

Parameters

A

-

Matrix; system matrix of a state-space system

B

-

Matrix or Vector; input matrix of a state-space system

Q

-

Matrix; state weighting matrix

R

-

Matrix; input weighting matrix

opts

-

(optional) equation(s) of the form option = value; specify options for the LQRContinuous command

Options

• 

N = Matrix or Vector

Weighting on the state-input multiplication term in the cost function. If omitted, a zero matrix with appropriate dimensions will be considered.

• 

poles   = true or false True means the eigenvalues of A-BK are returned. See LQR for details. The default value is false.    

• 

riccati  =  true or false True means the solution of the associated Riccati equation is returned. The infinite horizon solution of the following continuous-time Riccati equation (CARE) is returned.

The LQR feedback gain is calculated as

The default value is false.

• 

parameters = {list, set}(name = complexcons)

  

Specifies numeric values for the parameters of sys. These values override any parameters previously specified for sys. The numeric value on the right-hand side of each equation is substituted for the name on the left-hand side in the sys equations. The default is the value of sys given by DynamicSystems:-SystemOptions(parameters).

Solvability Conditions

• 

The pair  must be stabilizable.

• 

The pair  must have no unobservable modes on the imaginary axis.

• 

 (positive definite) and  (positive semidefinite).

Description

• 

The LQRContinuous command calculates the LQR state feedback gain for a given pair.

• 

The optimal state feedback gain, , is calculated such that the quadratic cost function

is minimized by the feedback law u = -Kx subject to the system dynamics

• 

Q and R are expected to be symmetric. If the input Q and/or R are not symmetric, their symmetric part will be considered since their antisymmetric (skew-symmetric) part has no role in the quadratic cost function.

• 

In addition to the state feedback gain, depending on the corresponding option values, the command also returns the closed-loop eigenvalues and the solution of the associated Riccati equation.

• 

Note that the time domain is inherent to the command regardless of the any time domain implications the input pair might have. To be more specific, this command calculates a continuous-time LQR feedback gain for the given input pair even if that pair is initially extracted from a discrete-time state-space.  If the gain is then used for feedback stabilization in discrete time domain, obviously such a mistake in command usage leads to a result which is not theoretically valid.     

Examples

(1)

(2)

(3)

(4)

(5)

(6)

See Also

ControlDesign

ControlDesign[LQR]

ControlDesign[LQRDiscrete]

ControlDesign[LQROutput]

ControlDesign[StateFeedback][Ackermann]

ControlDesign[StateFeedback][PolePlacement]

 


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