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rbmatlab
1.16.09
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rbmatlab
1.16.09
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DEFAULTMODEL.
This class represents a simple model which can be used for prototyping DARE equations. You can set up a new model by passing a descr structure, which should contain information about all the data matrices.
Andreas Schmidt, 2016
Definition at line 18 of file DefaultModel.m.
Public Member Functions | |
| DefaultModel (ModelDescr descr) | |
| function A = | A_coeff () |
| ================================================================= Data functions More... | |
| function A = | A_comp (md) |
| function B = | B_coeff () |
| function B = | B_comp (md) |
| function C = | C_coeff () |
| function C = | C_comp (md) |
| function E = | E_coeff () |
| function E = | E_comp (md) |
| function Q = | Q_coeff () |
| function Q = | Q_comp (md) |
| function R = | R_coeff () |
| function R = | R_comp (md) |
 Public Member Functions inherited from DARE.Model | |
| function pt = | problem_type () |
| function g = | gamma (ModelData model_data, dsim) |
| function n = | closed_loop_norm (ModelData model_data, dsim) |
| CLOSED_LOOP_NORM Implementation of an efficient algorithm for the approximation of the 2-norm of the closed-loop matrix. More... | |
| function [
stable , cleig ] = | closed_loop_stable (ModelData model_data, dsim) |
| CLOSED_LOOP_STABLE Implementation of an efficient algorithm for checking whether the closed loop matrix gives a stable system. This is done by calculting the maximum eigenvalue of the closed loop system. More... | |
| Public Member Functions inherited from ARE.Model | |
|
virtual function [ A , A , B ] = | B_comp (ModelData model_data, this,ModelData model_data) |
| function [
E , A , B , C , Q , R ] = | assemble (md) |
| ASSEMBLE Assembles all the data matrices. This function works for both, the reduced and the full model. More... | |
| function E = | mass_matrix (md) |
| MASS_MATRIX Get the mass matrix of the problem This function is used by the LRFG algorithm for the orthogonalization procedure. More... | |
| function g = | gamma (ModelData model_data, dsim) |
| GAMMA Calculate the value of gamma. This is used by applying the Lyapunov equation method. More... | |
| function R = | R_coeff () |
| function Q = | Q_coeff () |
| function E = | E_coeff () |
| function C = | C_coeff () |
| function B = | B_coeff () |
| function R = | R_comp (ModelData model_data) |
| function Q = | Q_comp (ModelData model_data) |
| function E = | E_comp (ModelData model_data) |
| function C = | C_comp (ModelData model_data) |
| function [
T , y , x ] = | simulate (ModelData model_data, dsim) |
| SIMULATE This function simulates the underlying LTI model If you provide dsim, the closed-loop simulation will be performed. More... | |
| Public Member Functions inherited from AbstractModel.Model | |
| virtual function dsim = | detailed_simulation (ModelData model_data) |
| DETAILED_SIMULATION The function DETAILED_SIMULATION returns an instance of SimData and. More... | |
| virtual function rsim = | rb_simulation (IReducedData reduced_data) |
| REDUCED_SIMULATION This function should return a reduced simulation of type RBSimData. More... | |
| function ModelData model_data = | gen_model_data () |
| GEN_MODEL_DATA Use this function in order to create a class of type ModelData which contains all the large-scale model data such as the discretized operators. More... | |
| function IDetailedData detailed_data = | gen_detailed_data (ModelData model_data) |
| GEN_DETAILED_DATA Call the basis generation algorithm. More... | |
| function IReducedData reduced_data = | gen_reduced_data (IDetailedData detailed_data) |
| GEN_REDUCED_DATA Get the reduced data structures. More... | |
| function pt = | problem_type () |
| PROBLEM_TYPE Use this function to determine the problem type. So consider overwriting it if necessary! TODO: implement a smart interface that automatically generates the correct. More... | |
| function mu = | get_mu () |
| Get the parameter values. More... | |
| function this = | set_mu (mu) |
| Set the parameter values. More... | |
Public Attributes | |
| descr | |
| mu = "[]" | |
| mu_names = {""} | |
| mu_ranges = {""} | |
| Public Attributes inherited from DARE.Model | |
| RB_closed_loop_norm = "fro" | |
| RB_closed_loop_stable = false | |
| Public Attributes inherited from ARE.Model | |
| enable_error_estimator = false | |
| calc_residual = true | |
| RB_gamma_mode = "Kernel" | |
| Additional fields for basis generation: More... | |
| RB_gamma_enabled = 1 | |
| RB_gamma_settings = {""} | |
| p | |
| The number of measurement outputs. | |
| m | |
| The number of control inputs and measurements. | |
| n | |
| model_data | |
| Public Attributes inherited from AbstractModel.Model | |
| mu | |
| mu_names | |
| mu_ranges | |
| Public Attributes inherited from Greedy.LRFG.ModelInterface | |
| RB_greedy_tolerance = 1e-4 | |
| RB_orthonormalize_E = true | |
| RB_error_indicator = "residual" | |
| RB_pod_tolerance = 0.99 | |
| RB_pod_max_extension = 10 | |
| RB_M_train = "Uniform" | |
| function A = DARE.DefaultModel.A_coeff | ( | ) |
================================================================= Data functions
| A | A |
Definition at line 68 of file DefaultModel.m.
1.8.8
