%% Clear Workspace and Close figures clear; close all; clc; %% Intialize Laplace variable s = zpk('s'); addpath('STEP'); freqs = logspace(-1, 2, 1000); % Simscape Model - Parameters % <> open('drone_platform.slx'); % Definition of spring parameters: kx = 0.5*1e3/3; % [N/m] ky = 0.5*1e3/3; kz = 1e3/3; cx = 0.025; % [Nm/rad] cy = 0.025; cz = 0.025; % We suppose the sensor is perfectly positioned. sens_pos_error = zeros(3,1); % Gravity: g = 0; % We load the Jacobian (previously computed from the geometry): load('jacobian.mat', 'Aa', 'Ab', 'As', 'l', 'J'); % We initialize other parameters: U = eye(6); V = eye(6); Kc = tf(zeros(6)); % #+name: fig:stewart_platform_plant % #+caption: Considered plant $\bm{G} = \begin{bmatrix}G_d\\G_u\end{bmatrix}$. $D_w$ is the translation/rotation of the support, $\tau$ the actuator forces, $a$ the acceleration/angular acceleration of the top platform % #+RESULTS: % [[file:figs/stewart_platform_plant.png]] %% Name of the Simulink File mdl = 'drone_platform'; %% Input/Output definition clear io; io_i = 1; io(io_i) = linio([mdl, '/Dw'], 1, 'openinput'); io_i = io_i + 1; % Ground Motion io(io_i) = linio([mdl, '/V-T'], 1, 'openinput'); io_i = io_i + 1; % Actuator Forces io(io_i) = linio([mdl, '/Inertial Sensor'], 1, 'openoutput'); io_i = io_i + 1; % Top platform acceleration G = linearize(mdl, io); G.InputName = {'Dwx', 'Dwy', 'Dwz', 'Rwx', 'Rwy', 'Rwz', ... 'F1', 'F2', 'F3', 'F4', 'F5', 'F6'}; G.OutputName = {'Ax', 'Ay', 'Az', 'Arx', 'Ary', 'Arz'}; % Plant Gu = G(:, {'F1', 'F2', 'F3', 'F4', 'F5', 'F6'}); % Disturbance dynamics Gd = G(:, {'Dwx', 'Dwy', 'Dwz', 'Rwx', 'Rwy', 'Rwz'}); % There are 24 states (6dof for the bottom platform + 6dof for the top platform). size(G) % #+RESULTS: % : State-space model with 6 outputs, 12 inputs, and 24 states. % The elements of the transfer matrix $\bm{G}$ corresponding to the transfer function from actuator forces $\tau$ to the measured acceleration $a$ are shown in Figure [[fig:stewart_platform_coupled_plant]]. % One can easily see that the system is strongly coupled. figure; % Magnitude hold on; for i_in = 1:6 for i_out = [1:i_in-1, i_in+1:6] plot(freqs, abs(squeeze(freqresp(Gu(i_out, i_in), freqs, 'Hz'))), 'color', [0,0,0,0.2], ... 'HandleVisibility', 'off'); end end plot(freqs, abs(squeeze(freqresp(Gu(i_out, i_in), freqs, 'Hz'))), 'color', [0,0,0,0.2], ... 'DisplayName', '$G_u(i,j)\ i \neq j$'); set(gca,'ColorOrderIndex',1) for i_in_out = 1:6 plot(freqs, abs(squeeze(freqresp(Gu(i_in_out, i_in_out), freqs, 'Hz'))), 'DisplayName', sprintf('$G_u(%d,%d)$', i_in_out, i_in_out)); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); xlabel('Frequency [Hz]'); ylabel('Magnitude'); ylim([1e-2, 1e5]); legend('location', 'northwest'); % #+name: fig:plant_decouple_jacobian % #+caption: Decoupled plant $\bm{G}_x$ using the Jacobian matrix $J$ % #+RESULTS: % [[file:figs/plant_decouple_jacobian.png]] % We define a new plant: % \[ G_x(s) = G(s) J^{-T} \] % $G_x(s)$ correspond to the transfer function from forces and torques applied to the top platform to the absolute acceleration of the top platform. Gx = Gu*inv(J'); Gx.InputName = {'Fx', 'Fy', 'Fz', 'Mx', 'My', 'Mz'}; % Decoupling using the SVD % <> % In order to decouple the plant using the SVD, first a real approximation of the plant transfer function matrix as the crossover frequency is required. % Let's compute a real approximation of the complex matrix $H_1$ which corresponds to the the transfer function $G_u(j\omega_c)$ from forces applied by the actuators to the measured acceleration of the top platform evaluated at the frequency $\omega_c$. wc = 2*pi*30; % Decoupling frequency [rad/s] H1 = evalfr(Gu, j*wc); % The real approximation is computed as follows: D = pinv(real(H1'*H1)); H1 = inv(D*real(H1'*diag(exp(j*angle(diag(H1*D*H1.'))/2)))); % #+caption: Real part of $G$ at the decoupling frequency $\omega_c$ % #+RESULTS: % | 4.4 | -2.1 | -2.1 | 4.4 | -2.4 | -2.4 | % | -0.2 | -3.9 | 3.9 | 0.2 | -3.8 | 3.8 | % | 3.4 | 3.4 | 3.4 | 3.4 | 3.4 | 3.4 | % | -367.1 | -323.8 | 323.8 | 367.1 | 43.3 | -43.3 | % | -162.0 | -237.0 | -237.0 | -162.0 | 398.9 | 398.9 | % | 220.6 | -220.6 | 220.6 | -220.6 | 220.6 | -220.6 | % Now, the Singular Value Decomposition of $H_1$ is performed: % \[ H_1 = U \Sigma V^H \] [U,~,V] = svd(H1); % #+name: fig:plant_decouple_svd % #+caption: Decoupled plant $\bm{G}_{SVD}$ using the Singular Value Decomposition % #+RESULTS: % [[file:figs/plant_decouple_svd.png]] % The decoupled plant is then: % \[ G_{SVD}(s) = U^{-1} G_u(s) V^{-H} \] Gsvd = inv(U)*Gu*inv(V'); % Verification of the decoupling using the "Gershgorin Radii" % <> % The "Gershgorin Radii" is computed for the coupled plant $G(s)$, for the "Jacobian plant" $G_x(s)$ and the "SVD Decoupled Plant" $G_{SVD}(s)$: % The "Gershgorin Radii" of a matrix $S$ is defined by: % \[ \zeta_i(j\omega) = \frac{\sum\limits_{j\neq i}|S_{ij}(j\omega)|}{|S_{ii}(j\omega)|} \] % This is computed over the following frequencies. % Gershgorin Radii for the coupled plant: Gr_coupled = zeros(length(freqs), size(Gu,2)); H = abs(squeeze(freqresp(Gu, freqs, 'Hz'))); for out_i = 1:size(Gu,2) Gr_coupled(:, out_i) = squeeze((sum(H(out_i,:,:)) - H(out_i,out_i,:))./H(out_i, out_i, :)); end % Gershgorin Radii for the decoupled plant using SVD: Gr_decoupled = zeros(length(freqs), size(Gsvd,2)); H = abs(squeeze(freqresp(Gsvd, freqs, 'Hz'))); for out_i = 1:size(Gsvd,2) Gr_decoupled(:, out_i) = squeeze((sum(H(out_i,:,:)) - H(out_i,out_i,:))./H(out_i, out_i, :)); end % Gershgorin Radii for the decoupled plant using the Jacobian: Gr_jacobian = zeros(length(freqs), size(Gx,2)); H = abs(squeeze(freqresp(Gx, freqs, 'Hz'))); for out_i = 1:size(Gx,2) Gr_jacobian(:, out_i) = squeeze((sum(H(out_i,:,:)) - H(out_i,out_i,:))./H(out_i, out_i, :)); end figure; hold on; plot(freqs, Gr_coupled(:,1), 'DisplayName', 'Coupled'); plot(freqs, Gr_decoupled(:,1), 'DisplayName', 'SVD'); plot(freqs, Gr_jacobian(:,1), 'DisplayName', 'Jacobian'); for in_i = 2:6 set(gca,'ColorOrderIndex',1) plot(freqs, Gr_coupled(:,in_i), 'HandleVisibility', 'off'); set(gca,'ColorOrderIndex',2) plot(freqs, Gr_decoupled(:,in_i), 'HandleVisibility', 'off'); set(gca,'ColorOrderIndex',3) plot(freqs, Gr_jacobian(:,in_i), 'HandleVisibility', 'off'); end set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); hold off; xlabel('Frequency (Hz)'); ylabel('Gershgorin Radii') legend('location', 'northwest'); ylim([1e-3, 1e3]); % Verification of the decoupling using the "Relative Gain Array" % <> % The relative gain array (RGA) is defined as: % \begin{equation} % \Lambda\big(G(s)\big) = G(s) \times \big( G(s)^{-1} \big)^T % \end{equation} % where $\times$ denotes an element by element multiplication and $G(s)$ is an $n \times n$ square transfer matrix. % The obtained RGA elements are shown in Figure [[fig:simscape_model_rga]]. % Relative Gain Array for the coupled plant: RGA_coupled = zeros(length(freqs), size(Gu,1), size(Gu,2)); Gu_inv = inv(Gu); for f_i = 1:length(freqs) RGA_coupled(f_i, :, :) = abs(evalfr(Gu, j*2*pi*freqs(f_i)).*evalfr(Gu_inv, j*2*pi*freqs(f_i))'); end % Relative Gain Array for the decoupled plant using SVD: RGA_svd = zeros(length(freqs), size(Gsvd,1), size(Gsvd,2)); Gsvd_inv = inv(Gsvd); for f_i = 1:length(freqs) RGA_svd(f_i, :, :) = abs(evalfr(Gsvd, j*2*pi*freqs(f_i)).*evalfr(Gsvd_inv, j*2*pi*freqs(f_i))'); end % Relative Gain Array for the decoupled plant using the Jacobian: RGA_x = zeros(length(freqs), size(Gx,1), size(Gx,2)); Gx_inv = inv(Gx); for f_i = 1:length(freqs) RGA_x(f_i, :, :) = abs(evalfr(Gx, j*2*pi*freqs(f_i)).*evalfr(Gx_inv, j*2*pi*freqs(f_i))'); end figure; tiledlayout(1, 2, 'TileSpacing', 'None', 'Padding', 'None'); ax1 = nexttile; hold on; for i_in = 1:6 for i_out = [1:i_in-1, i_in+1:6] plot(freqs, RGA_svd(:, i_out, i_in), '--', 'color', [0 0 0 0.2], ... 'HandleVisibility', 'off'); end end plot(freqs, RGA_svd(:, 1, 2), '--', 'color', [0 0 0 0.2], ... 'DisplayName', '$RGA_{SVD}(i,j),\ i \neq j$'); plot(freqs, RGA_svd(:, 1, 1), 'k-', ... 'DisplayName', '$RGA_{SVD}(i,i)$'); for ch_i = 1:6 plot(freqs, RGA_svd(:, ch_i, ch_i), 'k-', ... 'HandleVisibility', 'off'); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Magnitude'); xlabel('Frequency [Hz]'); legend('location', 'southwest'); ax2 = nexttile; hold on; for i_in = 1:6 for i_out = [1:i_in-1, i_in+1:6] plot(freqs, RGA_x(:, i_out, i_in), '--', 'color', [0 0 0 0.2], ... 'HandleVisibility', 'off'); end end plot(freqs, RGA_x(:, 1, 2), '--', 'color', [0 0 0 0.2], ... 'DisplayName', '$RGA_{X}(i,j),\ i \neq j$'); plot(freqs, RGA_x(:, 1, 1), 'k-', ... 'DisplayName', '$RGA_{X}(i,i)$'); for ch_i = 1:6 plot(freqs, RGA_x(:, ch_i, ch_i), 'k-', ... 'HandleVisibility', 'off'); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); xlabel('Frequency [Hz]'); set(gca, 'YTickLabel',[]); legend('location', 'southwest'); linkaxes([ax1,ax2],'y'); ylim([1e-5, 1e1]); % Obtained Decoupled Plants % <> % The bode plot of the diagonal and off-diagonal elements of $G_{SVD}$ are shown in Figure [[fig:simscape_model_decoupled_plant_svd]]. figure; tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); % Magnitude ax1 = nexttile([2, 1]); hold on; for i_in = 1:6 for i_out = [1:i_in-1, i_in+1:6] plot(freqs, abs(squeeze(freqresp(Gsvd(i_out, i_in), freqs, 'Hz'))), 'color', [0,0,0,0.2], ... 'HandleVisibility', 'off'); end end plot(freqs, abs(squeeze(freqresp(Gsvd(1, 2), freqs, 'Hz'))), 'color', [0,0,0,0.5], ... 'DisplayName', '$G_{SVD}(i,j),\ i \neq j$'); set(gca,'ColorOrderIndex',1) for ch_i = 1:6 plot(freqs, abs(squeeze(freqresp(Gsvd(ch_i, ch_i), freqs, 'Hz'))), ... 'DisplayName', sprintf('$G_{SVD}(%i,%i)$', ch_i, ch_i)); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Magnitude'); set(gca, 'XTickLabel',[]); legend('location', 'northwest'); ylim([1e-1, 1e5]) % Phase ax2 = nexttile; hold on; for ch_i = 1:6 plot(freqs, 180/pi*angle(squeeze(freqresp(Gsvd(ch_i, ch_i), freqs, 'Hz')))); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); ylabel('Phase [deg]'); xlabel('Frequency [Hz]'); ylim([-180, 180]); yticks([-180:90:360]); linkaxes([ax1,ax2],'x'); % #+name: fig:simscape_model_decoupled_plant_svd % #+caption: Decoupled Plant using SVD % #+RESULTS: % [[file:figs/simscape_model_decoupled_plant_svd.png]] % Similarly, the bode plots of the diagonal elements and off-diagonal elements of the decoupled plant $G_x(s)$ using the Jacobian are shown in Figure [[fig:simscape_model_decoupled_plant_jacobian]]. figure; tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); % Magnitude ax1 = nexttile([2, 1]); hold on; for i_in = 1:6 for i_out = [1:i_in-1, i_in+1:6] plot(freqs, abs(squeeze(freqresp(Gx(i_out, i_in), freqs, 'Hz'))), 'color', [0,0,0,0.2], ... 'HandleVisibility', 'off'); end end plot(freqs, abs(squeeze(freqresp(Gx(1, 2), freqs, 'Hz'))), 'color', [0,0,0,0.5], ... 'DisplayName', '$G_x(i,j),\ i \neq j$'); set(gca,'ColorOrderIndex',1) plot(freqs, abs(squeeze(freqresp(Gx('Ax', 'Fx'), freqs, 'Hz'))), 'DisplayName', '$G_x(1,1) = A_x/F_x$'); plot(freqs, abs(squeeze(freqresp(Gx('Ay', 'Fy'), freqs, 'Hz'))), 'DisplayName', '$G_x(2,2) = A_y/F_y$'); plot(freqs, abs(squeeze(freqresp(Gx('Az', 'Fz'), freqs, 'Hz'))), 'DisplayName', '$G_x(3,3) = A_z/F_z$'); plot(freqs, abs(squeeze(freqresp(Gx('Arx', 'Mx'), freqs, 'Hz'))), 'DisplayName', '$G_x(4,4) = A_{R_x}/M_x$'); plot(freqs, abs(squeeze(freqresp(Gx('Ary', 'My'), freqs, 'Hz'))), 'DisplayName', '$G_x(5,5) = A_{R_y}/M_y$'); plot(freqs, abs(squeeze(freqresp(Gx('Arz', 'Mz'), freqs, 'Hz'))), 'DisplayName', '$G_x(6,6) = A_{R_z}/M_z$'); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Magnitude'); set(gca, 'XTickLabel',[]); legend('location', 'northwest'); ylim([1e-2, 2e6]) % Phase ax2 = nexttile; hold on; plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Ax', 'Fx'), freqs, 'Hz')))); plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Ay', 'Fy'), freqs, 'Hz')))); plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Az', 'Fz'), freqs, 'Hz')))); plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Arx', 'Mx'), freqs, 'Hz')))); plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Ary', 'My'), freqs, 'Hz')))); plot(freqs, 180/pi*angle(squeeze(freqresp(Gx('Arz', 'Mz'), freqs, 'Hz')))); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); ylabel('Phase [deg]'); xlabel('Frequency [Hz]'); ylim([0, 180]); yticks([0:45:360]); linkaxes([ax1,ax2],'x'); % #+name: fig:svd_control % #+caption: Control Diagram for the SVD control % #+RESULTS: % [[file:figs/svd_control.png]] % We choose the controller to be a low pass filter: % \[ K_c(s) = \frac{G_0}{1 + \frac{s}{\omega_0}} \] % $G_0$ is tuned such that the crossover frequency corresponding to the diagonal terms of the loop gain is equal to $\omega_c$ wc = 2*pi*80; % Crossover Frequency [rad/s] w0 = 2*pi*0.1; % Controller Pole [rad/s] K_cen = diag(1./diag(abs(evalfr(Gx, j*wc))))*(1/abs(evalfr(1/(1 + s/w0), j*wc)))/(1 + s/w0); L_cen = K_cen*Gx; G_cen = feedback(G, pinv(J')*K_cen, [7:12], [1:6]); K_svd = diag(1./diag(abs(evalfr(Gsvd, j*wc))))*(1/abs(evalfr(1/(1 + s/w0), j*wc)))/(1 + s/w0); L_svd = K_svd*Gsvd; G_svd = feedback(G, inv(V')*K_svd*inv(U), [7:12], [1:6]); % The obtained diagonal elements of the loop gains are shown in Figure [[fig:stewart_comp_loop_gain_diagonal]]. figure; tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); % Magnitude ax1 = nexttile([2, 1]); hold on; plot(freqs, abs(squeeze(freqresp(L_svd(1, 1), freqs, 'Hz'))), 'DisplayName', '$L_{SVD}(i,i)$'); for i_in_out = 2:6 set(gca,'ColorOrderIndex',1) plot(freqs, abs(squeeze(freqresp(L_svd(i_in_out, i_in_out), freqs, 'Hz'))), 'HandleVisibility', 'off'); end set(gca,'ColorOrderIndex',2) plot(freqs, abs(squeeze(freqresp(L_cen(1, 1), freqs, 'Hz'))), ... 'DisplayName', '$L_{J}(i,i)$'); for i_in_out = 2:6 set(gca,'ColorOrderIndex',2) plot(freqs, abs(squeeze(freqresp(L_cen(i_in_out, i_in_out), freqs, 'Hz'))), 'HandleVisibility', 'off'); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Magnitude'); set(gca, 'XTickLabel',[]); legend('location', 'northwest'); ylim([5e-2, 2e3]) % Phase ax2 = nexttile; hold on; for i_in_out = 1:6 set(gca,'ColorOrderIndex',1) plot(freqs, 180/pi*angle(squeeze(freqresp(L_svd(i_in_out, i_in_out), freqs, 'Hz')))); end set(gca,'ColorOrderIndex',2) for i_in_out = 1:6 set(gca,'ColorOrderIndex',2) plot(freqs, 180/pi*angle(squeeze(freqresp(L_cen(i_in_out, i_in_out), freqs, 'Hz')))); end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); ylabel('Phase [deg]'); xlabel('Frequency [Hz]'); ylim([-180, 180]); yticks([-180:90:360]); linkaxes([ax1,ax2],'x'); % Closed-Loop system Performances % <> % Let's first verify the stability of the closed-loop systems: isstable(G_cen) % #+RESULTS: % : ans = % : logical % : 1 isstable(G_svd) % #+RESULTS: % : ans = % : logical % : 1 % The obtained transmissibility in Open-loop, for the centralized control as well as for the SVD control are shown in Figure [[fig:stewart_platform_simscape_cl_transmissibility]]. figure; tiledlayout(2, 2, 'TileSpacing', 'None', 'Padding', 'None'); ax1 = nexttile; hold on; plot(freqs, abs(squeeze(freqresp(G( 'Ax', 'Dwx')/s^2, freqs, 'Hz'))), 'DisplayName', 'Open-Loop'); plot(freqs, abs(squeeze(freqresp(G_cen('Ax', 'Dwx')/s^2, freqs, 'Hz'))), 'DisplayName', 'Centralized'); plot(freqs, abs(squeeze(freqresp(G_svd('Ax', 'Dwx')/s^2, freqs, 'Hz'))), '--', 'DisplayName', 'SVD'); set(gca,'ColorOrderIndex',1) plot(freqs, abs(squeeze(freqresp(G( 'Ay', 'Dwy')/s^2, freqs, 'Hz'))), 'HandleVisibility', 'off'); plot(freqs, abs(squeeze(freqresp(G_cen('Ay', 'Dwy')/s^2, freqs, 'Hz'))), 'HandleVisibility', 'off'); plot(freqs, abs(squeeze(freqresp(G_svd('Ay', 'Dwy')/s^2, freqs, 'Hz'))), '--', 'HandleVisibility', 'off'); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('$D_x/D_{w,x}$, $D_y/D_{w, y}$'); set(gca, 'XTickLabel',[]); legend('location', 'southwest'); ax2 = nexttile; hold on; plot(freqs, abs(squeeze(freqresp(G( 'Az', 'Dwz')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_cen('Az', 'Dwz')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_svd('Az', 'Dwz')/s^2, freqs, 'Hz'))), '--'); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('$D_z/D_{w,z}$'); set(gca, 'XTickLabel',[]); ax3 = nexttile; hold on; plot(freqs, abs(squeeze(freqresp(G( 'Arx', 'Rwx')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_cen('Arx', 'Rwx')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_svd('Arx', 'Rwx')/s^2, freqs, 'Hz'))), '--'); set(gca,'ColorOrderIndex',1) plot(freqs, abs(squeeze(freqresp(G( 'Ary', 'Rwy')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_cen('Ary', 'Rwy')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_svd('Ary', 'Rwy')/s^2, freqs, 'Hz'))), '--'); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('$R_x/R_{w,x}$, $R_y/R_{w,y}$'); xlabel('Frequency [Hz]'); ax4 = nexttile; hold on; plot(freqs, abs(squeeze(freqresp(G( 'Arz', 'Rwz')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_cen('Arz', 'Rwz')/s^2, freqs, 'Hz')))); plot(freqs, abs(squeeze(freqresp(G_svd('Arz', 'Rwz')/s^2, freqs, 'Hz'))), '--'); hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('$R_z/R_{w,z}$'); xlabel('Frequency [Hz]'); linkaxes([ax1,ax2,ax3,ax4],'xy'); xlim([freqs(1), freqs(end)]); ylim([1e-3, 1e2]);