function [y,u,t,y_e,t_e,e_e] = ppp_lin_run (Name,Simulate,ControlType,w,x_0,p_c,p_o) ## usage: [y,u,t,y_e,t_e,e_e] = ppp_lin_run (Name,Simulate,ControlType,w,x_0,p_c,p_o); ## ## ## Linear closed-loop PPP of lego system (and simulation) ## ## Name: Name of system (in mtt terms) ## Simulate = 0: real thing ## Simulate = 1: simulate ## Control = 0: step test ## Control = 1: PPP open-loop ## Control = 2: PPP closed-loop ## w is the (constant) setpoint ## par_control and par_observer are structures containing parameters ## for the observer and controller ##Defaults if nargin<1 # Default name to dir name names = split(pwd,"/"); [n_name,m_name] = size(names); Name = deblank(names(n_name,:)); endif ## System sys = mtt2sys(Name); # Create system [A,B,C,D] = sys2ss(sys); # SS form [n_x, n_u, n_y] = abcddim(A,B,C,D); # Dimensions if nargin<2 Simulate = 1; endif if nargin<3 ControlType = 2; endif if nargin<4 w = ones(n_y,1);; endif if nargin<5 x_0 = zeros(n_x,1); endif if nargin<6 p_c.N = 10; endif if nargin<7 p_o.sigma = 1e-1; endif if !struct_contains(p_c,"delta_ol") p_c.delta_ol = 1.0; # OL sample interval endif if !struct_contains(p_c,"T") p_c.T = 10.0; # Last time point. endif if !struct_contains(p_c,"Method") p_c.Method = "lq"; endif if struct_contains(p_c,"Method") if strcmp(p_c.Method,"lq") p_c.Q = eye(n_y); p_c.R = (0.5^2)*eye(n_u); p_c.n_U = n_x; elseif strcmp(p_c.Method,"original"); if !struct_contains(p_c,"A_w") p_c.A_w = 0; endif if !struct_contains(p_c,"A_u") p_c.n_U = n_x; a_u = 1.0; p_c.A_u = laguerre_matrix(p_c.n_U,a_u) endif else error(sprintf("Method %s not recognised", p_c.Method)); endif endif if !struct_contains(p_o,"x_0") p_o.x_0 = zeros(n_x,1); endif if !struct_contains(p_o,"method") p_o.method = "continuous"; ## p_o.method = "intermittent"; endif ## Check w. [n_w,m_w] = size(w); if ( (n_w<>n_y) || (m_w<>1) ) error(sprintf("ppp_lin_run: w must a column vector with %i elements",n_y)); endif ## Initialise x_est = p_o.x_0; ## Initilise simulation state x = x_0; if ControlType==0 # Step input I = 1; # 1 large sample p_c.delta_ol = p_c.T # I K_w = zeros(p_c.n_U,n_y); K_w(1,1) = 1; K_w(2,1) = -1; K_x = zeros(p_c.n_U,n_x); U = K_w*w; # Initial control U else I = ceil(p_c.T/p_c.delta_ol) # Number of large samples if strcmp(p_c.Method, "original") tau = [10:0.1:11]*(2/a_u); # Time horizons [k_x,k_w,K_x,K_w] = ppp_lin(A,B,C,D,p_c.A_u,p_c.A_w,tau); # Design elseif strcmp(p_c.Method, "lq") # LQ design tau = [0:0.001:1.0]*5; # Time horizons [k_x,k_w,K_x,K_w,Us0,J_uu,J_ux,J_uw,J_xx,J_xw,J_ww,y_u,p_c.A_u] \ = ppp_lin_quad (A,B,C,D,tau,p_c.Q,p_c.R); else error(sprintf("Control method %s not recognised", p_c.Method)); endif ##Sanity check A_u [p_c.n_U,M_u] = size(p_c.A_u); if (p_c.n_U<>M_u) error("A_u must be square"); endif U = K_w*w; # Initial control U ## Checks [ol_zeros, ol_poles] = sys2zp(sys) cl_poles = eig(A - B*k_x) endif ## Short sample interval dt = p_c.delta_ol/p_c.N; ## Observer design G = eye(n_x); # State noise gain sigma_x = eye(n_x); # State noise variance Sigma = p_o.sigma*eye(n_y); # Measurement noise variance if strcmp(p_o.method, "intermittent") Ad = expm(A*p_c.delta_ol); # Discrete-time transition matrix if (ControlType==2) # [L, M, P, obs_poles] = dlqe(Ad,G,C,sigma_x,Sigma); else L = zeros(n_x,n_y); obs_poles = eig(Ad); endif elseif strcmp(p_o.method, "continuous") Ad = expm(A*dt); # Discrete-time transition matrix A_ud = expm(p_c.A_u*dt); # Discrete-time input transition if (ControlType==2) # [L, M, P, obs_poles] = dlqe(Ad,G,C,sigma_x,Sigma); else L = zeros(n_x,n_y); obs_poles = eig(Ad); endif else error(sprintf("Observer method ""%s"" unknown", p_o.method)); endif ## Display the poles obs_poles ## Write the include file for the real-time function ## Use double length to allow for overuns disp("Writing Ustar.h"); overrun = 2; ppp_ustar2h(ppp_ustar (p_c.A_u, n_u, [0:dt:overrun*p_c.delta_ol], 0,0)); ## Control loop y = []; u = []; t = []; y_e = []; t_e = []; e_e = []; tick = time; for i=1:I i tim=time; # Timing if Simulate # Exact simulation t_sim = [0:p_c.N]*dt; # Simulation time points [yi,ui,xsi] = ppp_ystar(A,B,C,D,x,p_c.A_u,U,t_sim); # Simulate x = xsi(:,p_c.N+1); # Current state (for next time) y_now = yi(:,p_c.N+1); # Current output else # The real thing to_rt(U'); # Send U data = from_rt(p_c.N); # Receive data [yi,ui] = convert_data(data); # And convert from integer format y_now = yi(:,p_c.N); # Current output endif ## Observer if strcmp(p_o.method, "intermittent") [x_est y_est e_est] = ppp_int_obs \ (x_est,y_now,U,A,B,C,D,p_c.A_u,p_c.delta_ol,L); elseif strcmp(p_o.method, "continuous") Ui = U; # U at sub intervals for k = 1:p_c.N [x_est y_est e_est] = ppp_int_obs \ (x_est,yi(:,k+1),Ui,A,B,C,D,p_c.A_u,dt,L); Ui = A_ud*Ui; y_e = [y_e; y_est']; e_e = [e_e; e_est]; endfor endif ##Control ##U = K_w*w - K_x*x_est; U = expm(p_c.A_u*(p_c.delta_ol))*U ## Save data ti = [(i-1)*p_c.N:i*p_c.N-1]*dt; t = [t;ti']; y = [y;yi(:,1:p_c.N)']; u = [u;ui(:,1:p_c.N)']; sample_time = (time-tim)/p_c.N if strcmp(p_o.method, "intermittent") y_e = [y_e; y_est']; e_e = [e_e; e_est]; t_e = [t_e; (i*p_c.N)*dt]; endif dt endfor # Main loop if strcmp(p_o.method, "continuous") t_e = t; endif sample_interval = (time-tick)/(I*p_c.N) ## Put data on file (so can use for identification) filename = sprintf("%s_ident_data.dat",Name); eval(sprintf("save -ascii %s t y u",filename)); ## Plot gset nokey title(""); boxed=0; monochrome=1; grid; xlabel("t"); ylabel("y"); figure(1);plot(t,y, t_e,y_e,"+"); ylabel("u"); figure(2);plot(t,u); ylabel("e"); figure(3);plot(t_e,e_e); endfunction