📄 invinit.m
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% ------------------------------> INVINIT.M <------------------------------
% ---------- Switches -----------
regty ='dic'; % Controller type (dic, pid, none)
refty ='siggener'; % Reference signal (siggener/<var. name>)
simul ='simulink'; % Control object spec. (simulink/matlab/nnet)
% ------ General Initializations -------
Ts = 0.20; % Sampling period (in seconds)
samples = 200 ; % Number of samples to be simulated
% -- System to be Controlled (SIMULINK) --
integrator= 'ode45'; % Name of dif. eq. solver (f. ex. ode45 or ode15s)
sim_model = 'spm1'; % Name of SIMULINK model
% --- System to be Controlled (MATLAB) --
mat_model = 'springm'; % Name of MATLAB model
model_out = 'smout'; % Output equation (function of the states)
x0 = [0;0]; % Initial states
% --- System to be Controlled (neural net) --
% The file must contain: NN, NetDeff, W1f, W2f
nnforw = 'forward'; % Name of file
% ----- Inverse Network Specification ------
% The file must contain the variables:
% NN, NetDefi, W1i, W2i
% (i.e. regressor structure, architecture definition, and weight matrices)
nninv = 'inverse'; % Name of file
% ------------ Reference Filter ---------------
Am = [1]; % Filter denominator
Bm = [1]; % Filter numerator
% ------------ Reference signal ------------
dc = 0; % DC-level
sq_amp = 1; % Amplitude of square signals (row vector)
sq_freq = 0.1; % Frequency of square signals (column vector)
sin_amp = [0]; % Amplitude of sine signals (row vector)
sin_freq= [0]'; % Frequency of sine signals (column vector)
Nvar = 0'; % Variance of white noise signal
% -------- Linear Controller Parameters ---------
K=8; % PID parameters
Td=0.8; % PID
alf=0.1; % PID
Wi=0.2; % PID (1/Ti)
% ------- Specify data vectors to plot --------
% Notice that all strings in plot_a and plot_b resp. MUST have the same length
plot_a(1,:) = 'ref_data ';
plot_a(2,:) = 'y_data ';
plot_b(1,:) = 'u_data';
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