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    %% Plotting System Responses
% This example shows how to plot the time and frequency responses
% of SISO and MIMO linear systems.

%   Copyright 1986-2012 The MathWorks, Inc.

%% Time Responses
% For illustration purposes, create the following third-order transfer function:
sys = tf([8 18 32],[1 6 14 24])

%%
% You can plot the step and impulse responses of this system using the |step|
% and |impulse| commands:
subplot(2,1,1)
step(sys)
subplot(2,1,2)
impulse(sys)

%% 
% You can also simulate the response to an arbitrary signal, for example, a sine
% wave, using the |lsim| command. The input signal appears in gray and the
% system's response in blue.
clf
t = 0:0.01:4;
u = sin(10*t);
lsim(sys,u,t)   % u,t define the input signal

%%
% You can use the plotting commands with continuous or discrete TF, SS, or ZPK models. For
% state-space models, you can also plot the unforced response from some
% given initial state, for example:
A = [-0.8 3.6 -2.1;-3 -1.2 4.8;3 -4.3 -1.1];
B = [0; -1.1; -0.2];
C = [1.2 0 0.6];
D = -0.6;
G = ss(A,B,C,D);
x0 = [-1;0;2];  % initial state
initial(G,x0)
grid

%% Frequency Responses
% Frequency-domain analysis is key to understanding stability and
% performance properties of control systems. Bode plots, Nyquist plots, 
% and Nichols chart are three standard ways to plot and analyze the
% frequency response of a linear system. You can create these plots using
% the |bode|, |nichols|, and |nyquist| commands. For example:
sys = tf([8 18 32],[1 6 14 24])

%%
bode(sys)
grid

%%
nyquist(sys)
grid

%%
nichols(sys)
grid

%% Pole/Zero Maps and Root Locus
% The poles and zeros of a system contain valuable information about its
% dynamics, stability, and limits of performance. For example, consider the
% feedback loop in Figure 1 where 
%
% $$ G = { - (2 s + 1) \over s^2 + 3 s + 2 } $$
%
% <<../response_01.png>>

%%
% *Figure 1*: SISO Feedback Loop.

%%
% For the gain value |k = 0.7|, you can plot the closed-loop poles and zeros using
% |pzmap|:
s = tf('s');
G = -(2*s+1)/(s^2+3*s+2);
k = 0.7;
T = feedback(G*k,1);
pzmap(T)
grid, axis([-2 0 -1 1])

%%
% The closed-loop poles (marked by blue x's) lie in the left half-plane so the 
% feedback loop is stable for this choice of gain |k|.
% You can read the damping ratio of the closed-loop poles from this chart
% (see labels on the radial lines). Here the damping ratio is about 0.7,
% suggesting a well-damped closed-loop response as confirmed by:
clf
step(T)

%% 
% To further understand how the loop gain |k| affects closed-loop
% stability, you can plot the locus of the closed-loop poles as a function
% of |k|:
rlocus(G)
grid

%% 
% Clicking where the locus intersects the y axis reveals that the
% closed-loop poles become unstable for |k = 1.51|. So the loop gain should
% remain smaller than 1.5 for closed-loop stability.
%
% <<../response_02.png>>


%% Response Characteristics
% Right-clicking on response plots gives access to a variety of options and
% annotations. In particular, the *Characteristics* menu lets you display
% standard metrics such as rise time and settling time for step responses,
% or peak gain and stability margins for frequency response plots.
%
% Using the example from the previous section, plot the closed-loop step
% response:
step(T)

%%
% Now, right-click on the plot to display the Peak Response and Settling Time 
% Characteristics, and click on the blue dots to read the corresponding 
% overshoot and settling time values:
%
% <<../response_03.png>>

%% Analyzing MIMO Systems
% All commands mentioned so far fully support multi-input multi-output
% (MIMO) systems. In the MIMO case, these commands produce arrays of plots.
% For example, the step response of the two-input, two-output system
sys = rss(3,2,2);
sys.A = [-0.5 -0.3 -0.2 ; 0 -1.3  -1.7; 0.4 1.7 -1.3];

%% 
% is a 2-by-2 array of plots where each column shows the step response of 
% a particular input channel: 
step(sys)

%%
% If desired, you can group all four responses on a single plot by
% right-clicking on the plot and selecting the *I/O Grouping -> All*
% submenu. The resulting plot is shown below.
%
% <<../response_04.png>>


%%
% The following additional plots are useful for analyzing MIMO systems:
%
% * Singular value plot (|sigma|), which shows the principal gains of the frequency
% response
% * Pole/zero map for each I/O pair (|iopzplot|)
%
% For example, plot the peak gain of |sys| as a function of frequency:
sigma(sys)
grid

%% Comparing Systems
% You can plot multiple systems at once using any of the response plot
% commands. You can assign a specific color, marker, or line style to each
% system for easy comparison. Using the feedback example above, plot the
% closed-loop step response for three values of the loop gain |k| in 
% three different colors:
k1 = 0.4;
T1 = feedback(G*k1,1);
k2 = 1;
T2 = feedback(G*k2,1);
step(T,'b',T1,'r',T2,'g')
legend('k = 0.7','k = 0.4','k = 1')