LIBRARY

LinearMPCPart

What the LinearMPC.jl components have in common: the MPC object and the dimensions of its signals, read from the object once so that the connector arrays of LinearMPCOptimizer and LinearMPCController can be sized by them.

Usage

MPCComponents.LinearMPCPart()

Parameters:

Name	Description	Units	Default value
mpc	Set-up LinearMPC.jl MPC object wrapped in an MPCRef (see build_linear_mpc)	–
nx	State dimension of the model (derived from mpc)	–	_lmpc_nx(mpc)
nu	Number of controls (derived from mpc)	–	_lmpc_nu(mpc)
ny_meas	Number of measured outputs, the rows of the observer's measurement matrix; 0 without an observer (derived from mpc)	–	_lmpc_ny_meas(mpc)
ndo	Number of estimated offset-free disturbances, 0 for a plain Kalman filter (derived from mpc)	–	_lmpc_ndo(mpc)
nxa	Length of the augmented observer state, nx + ndo (derived)	–	nx + ndo
nr_in	Width of the reference input: 0, ny or ny*Np (derived from mpc)	–	_lmpc_nr_in(mpc)
nd_in	Width of the measured-disturbance input: 0, nd_meas or nd_meas*Np (derived from mpc)	–	_lmpc_nd_in(mpc)
np_in	Width of the generalized-parameter input: 0, np or np*Np (derived from mpc)	–	_lmpc_np_in(mpc)
has_r	Whether the r connector exists (derived)	–	nr_in > 0
has_d	Whether the d connector exists (derived)	–	nd_in > 0
has_dhat	Whether the dhat connector exists (derived)	–	ndo > 0
has_p	Whether the p connector exists (derived)	–	np_in > 0

Source

"""
What the LinearMPC.jl components have in common: the MPC object and the dimensions of its signals,
read from the object once so that the connector arrays of `LinearMPCOptimizer` and
`LinearMPCController` can be sized by them.
"""
partial component LinearMPCPart@[input clk extends Discrete]
  "Set-up LinearMPC.jl MPC object wrapped in an MPCRef (see build_linear_mpc)"
  structural parameter mpc::MPCRef
  "State dimension of the model (derived from mpc)"
  final structural parameter nx::Integer = _lmpc_nx(mpc)
  "Number of controls (derived from mpc)"
  final structural parameter nu::Integer = _lmpc_nu(mpc)
  "Number of measured outputs, the rows of the observer's measurement matrix; 0 without an observer (derived from mpc)"
  final structural parameter ny_meas::Integer = _lmpc_ny_meas(mpc)
  "Number of estimated offset-free disturbances, 0 for a plain Kalman filter (derived from mpc)"
  final structural parameter ndo::Integer = _lmpc_ndo(mpc)
  "Length of the augmented observer state, nx + ndo (derived)"
  final structural parameter nxa::Integer = nx + ndo
  "Width of the reference input: 0, ny or ny*Np (derived from mpc)"
  final structural parameter nr_in::Integer = _lmpc_nr_in(mpc)
  "Width of the measured-disturbance input: 0, nd_meas or nd_meas*Np (derived from mpc)"
  final structural parameter nd_in::Integer = _lmpc_nd_in(mpc)
  "Width of the generalized-parameter input: 0, np or np*Np (derived from mpc)"
  final structural parameter np_in::Integer = _lmpc_np_in(mpc)
  "Whether the r connector exists (derived)"
  final structural parameter has_r::Boolean = nr_in > 0
  "Whether the d connector exists (derived)"
  final structural parameter has_d::Boolean = nd_in > 0
  "Whether the dhat connector exists (derived)"
  final structural parameter has_dhat::Boolean = ndo > 0
  "Whether the p connector exists (derived)"
  final structural parameter has_p::Boolean = np_in > 0
relations
end

Flattened Source

"""
What the LinearMPC.jl components have in common: the MPC object and the dimensions of its signals,
read from the object once so that the connector arrays of `LinearMPCOptimizer` and
`LinearMPCController` can be sized by them.
"""
partial component LinearMPCPart
  "Set-up LinearMPC.jl MPC object wrapped in an MPCRef (see build_linear_mpc)"
  structural parameter mpc::MPCRef
  "State dimension of the model (derived from mpc)"
  final structural parameter nx::Integer = _lmpc_nx(mpc)
  "Number of controls (derived from mpc)"
  final structural parameter nu::Integer = _lmpc_nu(mpc)
  "Number of measured outputs, the rows of the observer's measurement matrix; 0 without an observer (derived from mpc)"
  final structural parameter ny_meas::Integer = _lmpc_ny_meas(mpc)
  "Number of estimated offset-free disturbances, 0 for a plain Kalman filter (derived from mpc)"
  final structural parameter ndo::Integer = _lmpc_ndo(mpc)
  "Length of the augmented observer state, nx + ndo (derived)"
  final structural parameter nxa::Integer = nx + ndo
  "Width of the reference input: 0, ny or ny*Np (derived from mpc)"
  final structural parameter nr_in::Integer = _lmpc_nr_in(mpc)
  "Width of the measured-disturbance input: 0, nd_meas or nd_meas*Np (derived from mpc)"
  final structural parameter nd_in::Integer = _lmpc_nd_in(mpc)
  "Width of the generalized-parameter input: 0, np or np*Np (derived from mpc)"
  final structural parameter np_in::Integer = _lmpc_np_in(mpc)
  "Whether the r connector exists (derived)"
  final structural parameter has_r::Boolean = nr_in > 0
  "Whether the d connector exists (derived)"
  final structural parameter has_d::Boolean = nd_in > 0
  "Whether the dhat connector exists (derived)"
  final structural parameter has_dhat::Boolean = ndo > 0
  "Whether the p connector exists (derived)"
  final structural parameter has_p::Boolean = np_in > 0
relations
metadata {}
end

Test Cases

No test cases defined.

Related

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