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Implement gain-scheduled state-space controller in self-conditioned form depending on two scheduling parameters

The 2D Self-Conditioned [A(v),B(v),C(v),D(v)] block implements a gain-scheduled state-space controller as defined by the equations

in the self-conditioned form

For the rationale behind this self-conditioned implementation,
refer to the Self-Conditioned [A,B,C,D] block reference. This block implements
a gain-scheduled version of the Self-Conditioned [A,B,C,D] block, *v* being
the vector of parameters over which *A*, *B*, *C*,
and *D* are defined. This type of controller scheduling
assumes that the matrices *A*, *B*, *C*,
and *D* vary smoothly as a function of *v*,
which is often the case in aerospace applications.

**A-matrix(v1,v2)***A*-matrix of the state-space implementation. In the case of 2-D scheduling, the*A*-matrix should have four dimensions, the last two corresponding to scheduling variables*v*1 and*v*2. Hence, for example, if the*A*-matrix corresponding to the first entry of*v*1 and first entry of*v*2 is the identity matrix, then`A(:,:,1,1) = [1 0;0 1];`.**B-matrix(v1,v2)***B*-matrix of the state-space implementation. In the case of 2-D scheduling, the*B*-matrix should have four dimensions, the last two corresponding to scheduling variables*v*1 and*v*2. Hence, for example, if the*B*-matrix corresponding to the first entry of*v*1 and first entry of*v*2 is the identity matrix, then`B(:,:,1,1) = [1 0;0 1];`.**C-matrix(v1,v2)***C*-matrix of the state-space implementation. In the case of 2-D scheduling, the*C*-matrix should have four dimensions, the last two corresponding to scheduling variables*v*1 and*v*2. Hence, for example, if the*C*-matrix corresponding to the first entry of*v*1 and first entry of*v*2 is the identity matrix, then`C(:,:,1,1) = [1 0;0 1];`.**D-matrix(v1,v2)***D*-matrix of the state-space implementation. In the case of 2-D scheduling, the*D*-matrix should have four dimensions, the last two corresponding to scheduling variables*v*1 and*v*2. Hence, for example, if the*D*-matrix corresponding to the first entry of*v*1 and first entry of*v*2 is the identity matrix, then`D(:,:,1,1) = [1 0;0 1];`.**First scheduling variable (v1) breakpoints**Vector of the breakpoints for the first scheduling variable. The length of

*v*1 should be same as the size of the third dimension of*A*,*B*,*C*, and*D*.**Second scheduling variable (v2) breakpoints**Vector of the breakpoints for the second scheduling variable. The length of

*v*2 should be same as the size of the fourth dimension of*A*,*B*,*C*, and*D*.**Initial state, x_initial**Vector of initial states for the controller, i.e., initial values for the state vector,

*x*. It should have length equal to the size of the first dimension of*A*.**Poles of A(v)-H(v)*C(v)**Vector of the desired poles of

*A*-*HC*. Note that the poles are assigned to the same locations for all values of the scheduling parameter,*v*. Hence, the number of pole locations defined should be equal to the length of the first dimension of the*A*-matrix.

Input | Dimension Type | Description |
---|---|---|

First | Contains the measurements. | |

Second | Contains the scheduling variable, conforming to the dimensions of the state-space matrices. | |

Third | Contains the scheduling variable, conforming to the dimensions of the state-space matrices. | |

Fourth | Contains the measured actuator position. |

Output | Dimension Type | Description |
---|---|---|

First | Contains the actuator demands. |

If the scheduling parameter inputs to the block go out of range, then they are clipped; i.e., the state-space matrices are not interpolated out of range.

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