thesis/tesi.m

125 lines
3.6 KiB
Matlab

clc
clear all
close all
%TESTS = ["sin_faster", "sin", "circle", "straightline", "reverse_straightline"]
TESTS = ["figure8/fancyreps"]
s_ = size(TESTS);
for i = 1:s_(1)
clear data sim_data
close all
sim_data = load(["tests/robot_common.mat"]);
TEST = convertStringsToChars(TESTS(i))
test_data = load(['tests/' TEST '/common.mat']);
for fn = fieldnames(test_data)'
sim_data.(fn{1}) = test_data.(fn{1});
end
sim_data.q0 = set_initial_conditions(sim_data.INITIAL_CONDITIONS);
[ref dref] = set_trajectory(sim_data.TRAJECTORY, sim_data);
sim_data.ref = ref;
sim_data.dref = dref;
spmd (3)
worker_index = spmdIndex;
data = load(['tests/' num2str(worker_index) '.mat']);
for fn = fieldnames(data)'
sim_data.(fn{1}) = data.(fn{1});
end
sim_data.U_corr_history = zeros(2,1,sim_data.PREDICTION_HORIZON);
sim_data
[t, q, ref_t, U, U_track, U_corr, U_corr_pred_history, Q_pred] = simulate_discr(sim_data);
disp('Done')
end
h = [];
s1_ = size(worker_index);
for n = 1:s1_(2)
h = [h, figure('Name', [TEST ' ' num2str(n)] )];
plot_results(t{n}, q{n}, ref_t{n}, U{n}, U_track{n}, U_corr{n});
end
f1 = [ TEST '/' datestr(datetime)];
f = ['results-diffdrive/' f1];
mkdir(f)
savefig(h, [f '/figure.fig']);
h = [h, figure('Name', 'difference between 1step and multistep')]
subplot(2,1,1)
plot(t{2}, U_corr{2}(:, 1) - U_corr{3}(:, 1))
xlabel('t')
ylabel('difference on w_r between 1-step and multistep')
subplot(2,1,2)
plot(t{2}, U_corr{2}(:, 2) - U_corr{3}(:, 2))
xlabel('t')
ylabel('difference on w_l between 1-step and multistep')
clear h
dsave([f '/workspace_composite.mat']);
copyfile(['tests/' TEST], f);
%video(q{1}', ref_t{1}', 0.1, t{1}, 2, sim_data{1}.tc*0.05, "aa");
%video(q{2}', ref_t{2}', 0.1, t{2}, 2, sim_data{1}.tc*0.05, "aa");
%video(q{3}', ref_t{3}', 0.1, t{3}, 2, sim_data{1}.tc*0.05, "aa");
end
%% FUNCTION DECLARATIONS
% Discrete-time simulation
function [t, q, ref_t, U, U_track, U_corr, U_corr_pred_history, Q_pred] = simulate_discr(sim_data)
tc = sim_data.tc;
steps = sim_data.tfin/tc
q = sim_data.q0';
t = 0;
Q_pred = zeros(sim_data.PREDICTION_HORIZON,3,sim_data.tfin/sim_data.tc + 1);
U_corr_pred_history=zeros(sim_data.PREDICTION_HORIZON,2,steps);
[u_discr, u_track, u_corr, U_corr_history, q_pred] = control_act(t, q, sim_data);
sim_data.U_corr_history = U_corr_history;
U = u_discr';
U_corr = u_corr';
U_track = u_track';
Q_pred(:, :, 1) = q_pred;
for n = 1:steps
sim_data.old_u_corr = u_corr;
sim_data.old_u_track = u_track;
sim_data.old_u = u_discr;
tspan = [(n-1)*tc n*tc];
z0 = q(end, :);
%[v, z] = ode45(@sistema_discr, tspan, z0, u_discr);
[v, z] = ode45(@(v, z) sistema_discr(v, z, u_discr, sim_data), tspan, z0);
q = [q; z];
t = [t; v];
[u_discr, u_track, u_corr, U_corr_history, q_pred] = control_act(t(end), q(end, :), sim_data);
sim_data.U_corr_history = U_corr_history;
U = [U; ones(length(v), 1)*u_discr'];
U_corr = [U_corr; ones(length(v), 1)*u_corr'];
U_track = [U_track; ones(length(v), 1)*u_track'];
Q_pred(:, :, 1+n) = q_pred;
U_corr_pred_history(:,:,n) = permute(U_corr_history, [3, 1, 2]);
end
ref_t = double(subs(sim_data.ref, t'))';
end
%%