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authorNao Pross <np@0hm.ch>2024-05-17 11:41:28 +0200
committerNao Pross <np@0hm.ch>2024-05-17 11:41:28 +0200
commitde891f907e6d7908e75e0da8dddd04c66dfcfd7b (patch)
treefb0253494a27d16f733cdf1d325d6741cf3ed0bb /uav_performance_musyn.m
parentDelete old LQR code (diff)
downloaduav-de891f907e6d7908e75e0da8dddd04c66dfcfd7b.tar.gz
uav-de891f907e6d7908e75e0da8dddd04c66dfcfd7b.zip
Clean up comments
Diffstat (limited to '')
-rw-r--r--uav_performance_musyn.m41
1 files changed, 12 insertions, 29 deletions
diff --git a/uav_performance_musyn.m b/uav_performance_musyn.m
index 6ece761..180be8a 100644
--- a/uav_performance_musyn.m
+++ b/uav_performance_musyn.m
@@ -13,44 +13,27 @@
% PERF Struct performance transfer functions
-function [perf] = uav_performance(params, do_plots)
+function [perf] = uav_performance_musyn(params, do_plots)
% Laplace variable
s = tf('s');
-alpha_max = params.actuators.ServoAbsMaxAngle;
-alpha_max_omega = params.actuators.ServoNominalAngularVelocity;
+% TODO: set proper constraints
+G = 1e2 / (s + 1e2);
-T_xy = params.performance.HorizontalSettleTime;
-T_z = params.performance.VerticalSettleTime;
+W_Palpha = G;
+W_Pomega = G;
-omega_nxy = 5 / T_xy;
-omega_nz = 10 / T_z;
+W_Pxy = G;
+W_Pz = G;
-% W_Palpha = 1 / (s^2 + 2 * alpha_max_omega * s + alpha_max_omega^2);
-% W_Palpha = (1 - W_Palpha / dcgain(W_Palpha)) * .8;
-% W_Pomega = (1 - 1 / (T_z / 5 * s + 1)) * .1;
-
-W_Palpha = make_weight(alpha_max_omega, 15, 1.1, 3);
-W_Pomega = make_weight(omega_nz, 50, 10);
-
-% zeta = 1; % Almost critically damped
-% W_Pxy = 1 / (s^2 + 2 * zeta * omega_nxy * s + omega_nxy^2);
-% W_Pxy = 1 * W_Pxy / dcgain(W_Pxy);
-% W_Pz = 1 / (s^2 + 2 * zeta * omega_nz * s + omega_nz^2);
-% W_Pz = 1 * W_Pz / dcgain(W_Pz);
-
-W_Pxy = make_weight(omega_nxy, 2, 5);
-W_Pz = make_weight(omega_nz, 1, 10);
-
-% Set a speed limit
-W_Pxydot = .2 * tf(1, 1);
-W_Pzdot = .2 * tf(1, 1);
+W_Pxydot = tf(0);
+W_Pzdot = tf(0);
-W_Pphitheta = .01 * tf(1, [.1, 1]);
-W_Ppsi = .01 * tf(1, 1); % don't care
+W_Pphitheta = tf(0);
+W_Ppsi = tf(0);
-W_PTheta = tf(1, [.1, 1]) * eye(3);
+W_PTheta = tf(0);
% Construct performance vector by combining xy and z
W_PP = blkdiag(W_Pxy * eye(2), W_Pz);