diff options
| -rw-r--r-- | uav.m | 19 | ||||
| -rw-r--r-- | uav_model_uncertain.slx | bin | 62649 -> 64772 bytes | |||
| -rw-r--r-- | uav_params.m | 4 | ||||
| -rw-r--r-- | uav_performance_hinf.m | 23 | ||||
| -rw-r--r-- | uav_performance_musyn.m | 40 | ||||
| -rw-r--r-- | uav_sim_step.m | 5 | ||||
| -rw-r--r-- | uav_uncertainty.m | 2 |
7 files changed, 52 insertions, 41 deletions
@@ -157,11 +157,11 @@ if do_musyn nmeas = model.uncertain.Ny; nctrl = model.uncertain.Nu; hinfopt = hinfsynOptions('Display', 'off', 'Method', 'RIC', ... - 'AutoScale', 'on', 'RelTol', 1e-2); + 'AutoScale', 'on', 'RelTol', 1e-3); % Frequency raster resolution to fit D scales - omega_max = 2.5; - omega_min = -3.5; + omega_max = 2; + omega_min = -3; nsamples = (omega_max - omega_min) * 100; omega = logspace(omega_min, omega_max, nsamples); @@ -172,10 +172,10 @@ if do_musyn D_right = tf(eye(model.uncertain.Nv + model.uncertain.Nw + model.uncertain.Nu)); % Maximum degree of D-scales and error - d_scales_max_degree = 4; + d_scales_max_degree = 5; d_scales_max_err = 15; - d_scales_max_err_p = .1; % in percentage - d_scales_improvement_p = .5; % in percentage, avoid diminishing returns + d_scales_max_err_p = .05; % in percentage + d_scales_improvement_p = .25; % in percentage, avoid diminishing returns % Limit order of scaled plant scaled_plant_reduce_ord = 100; @@ -199,7 +199,7 @@ if do_musyn gamma_min = .8; % Maximum number of D-K iterations - niters = 4; + niters = 6; fprintf(' - Will do (max) %d iterations.\n', niters); %% Run D-K iteration @@ -208,8 +208,8 @@ if do_musyn % according to parameters given above d_scales_degrees = { 0, 0, 0, 0, 0, inf, inf; % alpha - 1, 1, 3, 3, 0, inf, inf; % omega - 0, 1, 0, 0, 0, inf, inf; % state + inf, inf, inf, inf, inf, inf, inf; % omega + 0, 0, 0, 0, 0, inf, inf; % state 0, 0, 0, 0, 0, inf, inf; % perf }; @@ -251,6 +251,7 @@ if do_musyn [P_scaled, ~] = prescale(P_scaled, omega_range); n = size(P_scaled.A, 1); + % disabled, seems to work without if false && n > scaled_plant_reduce_ord R = reducespec(P_scaled, 'balanced'); % or ncf R.Options.FreqIntervals = [omega_range{1}, omega_range{2}]; diff --git a/uav_model_uncertain.slx b/uav_model_uncertain.slx Binary files differindex 6f1b050..437c82d 100644 --- a/uav_model_uncertain.slx +++ b/uav_model_uncertain.slx diff --git a/uav_params.m b/uav_params.m index 2ac187e..8963b02 100644 --- a/uav_params.m +++ b/uav_params.m @@ -92,9 +92,9 @@ params.aerodynamics = struct(... 'FlapArea', 23e-3 * 10e-3, ... % in m^2 'FlapAreaUncertainty', .1, ... % in % 'DragCoefficients', [0, 0], ... % TODO - 'DragCoefficientsUncertainties', [.1, .1], ... % in % + 'DragCoefficientsUncertainties', [.0, .0], ... % in % 'LiftCoefficient', 2 * pi, ... % TODO - 'LiftCoefficientUncertainty', .1 ...% in % + 'LiftCoefficientUncertainty', .05 ...% in % ); diff --git a/uav_performance_hinf.m b/uav_performance_hinf.m index 4a6de8a..c8df42a 100644 --- a/uav_performance_hinf.m +++ b/uav_performance_hinf.m @@ -23,26 +23,29 @@ T_alpha = params.actuators.ServoSecondsTo60Deg; T_omega = 0.1; T_xy = 5; -T_z = 10; +T_z = 4; % Inverse performance functions -W_Palpha = make_weight(1/T_alpha, 10, 2); -W_Pomega = make_weight(1/T_omega, 10, 2); +W_Palpha = tf(.8); +W_Pomega = tf(.5); + +W_Ralpha = 1 / ((s * T_alpha)^2 + 2 * T_alpha * s + 1); +W_Romega = 1 / ((s * T_omega)^2 + 2 * T_omega * 1.2 * s + 1); W_Rxy = 1 / ((s * T_xy)^2 + 2 * T_xy * .8 * s + 1); -W_Rz = 1 / (s * T_z + 1); +W_Rz = 1 / ((s * T_z)^2 + 2 * T_z * s + 1); -W_Pxy = tf(5); +W_Pxy = tf(12); W_Pz = tf(1); W_Pxydot = tf(.01); W_Pzdot = tf(.01); -W_Pphitheta = .001 / (s * T_xy + 1); -W_Ppsi = tf(.1); +W_Pphitheta = tf(.005); +W_Ppsi = tf(.3); % Construct performance vector by combining xy and z -W_ref = blkdiag(W_Rxy * eye(2), W_Rz); +W_Rref = blkdiag(W_Rxy * eye(2), W_Rz); W_PP = blkdiag(W_Pxy * eye(2), W_Pz); W_PPdot = blkdiag(W_Pxydot * eye(2), W_Pzdot); @@ -51,7 +54,9 @@ W_PTheta = blkdiag(W_Pphitheta * eye(2), W_Ppsi); perf = struct(... 'FlapAngle', W_Palpha * eye(4), ... 'Thrust', W_Pomega, ... - 'ReferenceFilter', W_ref, ... + 'ReferenceFilter', W_Rref, ... + 'FlapAngleFilter', W_Ralpha * eye(4), ... + 'ThrusterFilter', W_Romega, ... 'Position', W_PP, ... 'Velocity', W_PPdot, ... 'Angles', W_PTheta ... diff --git a/uav_performance_musyn.m b/uav_performance_musyn.m index 5ad5fa5..a521f81 100644 --- a/uav_performance_musyn.m +++ b/uav_performance_musyn.m @@ -22,28 +22,30 @@ s = tf('s'); T_alpha = params.actuators.ServoSecondsTo60Deg; T_omega = 0.1; -T_xy = 8; -T_z = 10; +T_xy = 6; +T_z = 9; % Inverse performance functions +W_Palpha = tf(.2); +W_Pomega = tf(.2); -W_Palpha = make_weight(1/T_alpha, 10, 4); -W_Pomega = make_weight(1/T_omega, 10, 2); +W_Ralpha = 1 / ((s * T_alpha)^2 + 2 * T_alpha * s + 1); +W_Romega = 1 / ((s * T_omega)^2 + 2 * T_omega * s + 1); W_Rxy = 1 / ((s * T_xy)^2 + 2 * T_xy * .8 * s + 1); -W_Rz = 1 / (s * T_z + 1); +W_Rz = 1 / ((s * T_z)^2 + 2 * T_z * s + 1); -W_Pxy = tf(5); +W_Pxy = tf(1); W_Pz = tf(1); W_Pxydot = tf(.01); W_Pzdot = tf(.1); -W_Pphitheta = .001 / (s * T_xy + 1); -W_Ppsi = tf(.1); +W_Pphitheta = tf(.005); +W_Ppsi = tf(.2); % Construct performance vector by combining xy and z -W_ref = blkdiag(W_Rxy * eye(2), W_Rz); +W_Rref = blkdiag(W_Rxy * eye(2), W_Rz); W_PP = blkdiag(W_Pxy * eye(2), W_Pz); W_PPdot = blkdiag(W_Pxydot * eye(2), W_Pzdot); @@ -52,7 +54,9 @@ W_PTheta = blkdiag(W_Pphitheta * eye(2), W_Ppsi); perf = struct(... 'FlapAngle', W_Palpha * eye(4), ... 'Thrust', W_Pomega, ... - 'ReferenceFilter', W_ref, ... + 'ReferenceFilter', W_Rref, ... + 'FlapAngleFilter', W_Ralpha * eye(4), ... + 'ThrusterFilter', W_Romega, ... 'Position', W_PP, ... 'Velocity', W_PPdot, ... 'Angles', W_PTheta); @@ -61,14 +65,14 @@ if do_plots % Bode plots of performance requirements figure; hold on; - bodemag(1/W_Palpha); - bodemag(1/W_Pomega); - bodemag(1/W_Pxy); - bodemag(1/W_Pz); - bodemag(1/W_Pxydot); - bodemag(1/W_Pzdot); - bodemag(1/W_Pphitheta); - bodemag(1/W_Ppsi); + bodemag(W_Palpha); + bodemag(W_Pomega); + bodemag(W_Pxy); + bodemag(W_Pz); + bodemag(W_Pxydot); + bodemag(W_Pzdot); + bodemag(W_Pphitheta); + bodemag(W_Ppsi); grid on; legend('$W_{P,\alpha}$', '$W_{P,\omega}$', ... diff --git a/uav_sim_step.m b/uav_sim_step.m index 65fb36f..2130a3d 100644 --- a/uav_sim_step.m +++ b/uav_sim_step.m @@ -104,7 +104,7 @@ ref_step = ones(1, nsamp); % 1d step function in_step_x = [ noise; step_size_h * ref_step; zeros(2, nsamp) ]; in_step_y = [ noise; zeros(1, nsamp); step_size_h * ref_step; zeros(1, nsamp) ]; -in_step_z = [ noise; zeros(2, nsamp); step_size_v * ref_step ]; +in_step_z = [ noise; zeros(2, nsamp); -step_size_v * ref_step ]; % z points down % Simulation time t = linspace(0, T, nsamp); @@ -152,7 +152,7 @@ if do_plots % Plot limits alpha_max_deg = params.actuators.ServoAbsMaxAngle * to_deg; - euler_lim_deg = 1.5; + euler_lim_deg = .5; omega_max_rpm = (params.actuators.PropellerMaxAngularVelocity ... - params.linearization.Inputs(5)) * to_rpm; omega_min_rpm = -params.linearization.Inputs(5) * to_rpm; @@ -298,6 +298,7 @@ if do_plots % Plot step response from vertical reference to vertical position subplot(2, 2, 3); hold on; plot(t, out_step_z(:, idx.PlotPosition(3))); + plot(t, out_step_z(:, idx.PlotReference(3)), '--'); grid on; title('Vertical Position', 'Interpreter', 'latex'); ylabel('Distance (meters)', 'Interpreter', 'latex'); diff --git a/uav_uncertainty.m b/uav_uncertainty.m index 03b7b3b..045321d 100644 --- a/uav_uncertainty.m +++ b/uav_uncertainty.m @@ -26,7 +26,7 @@ eps_d = params.aerodynamics.DragCoefficientsUncertainties(1); % eps_0 = params.aerodynamics.DragCoefficients(2); eps_omega = max(.5 * eps_T, eps_r); -eps_alpha = max(eps_l + eps_S + 2 * eps_omega, eps_S + eps_d + eps_omega) +eps_alpha = max(eps_l + eps_S + 2 * eps_omega, eps_S + eps_d + eps_omega); b = 12; T = 1; |