Difference between revisions of "Bioreactor (ACADO)"

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(Created page with "This is the implementation of the ACADO bioreactor example with the matlab interface and the code generation of ACADO. % implements the bioreactor example of ACADO for the m...")
 
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This is the implementation of the ACADO bioreactor example with the matlab interface and the code generation of ACADO.
 
This is the implementation of the ACADO bioreactor example with the matlab interface and the code generation of ACADO.
  
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<source lang="Matlab">
 
  % implements the bioreactor example of ACADO for the matlab interface and
 
  % implements the bioreactor example of ACADO for the matlab interface and
 
  % the code generation
 
  % the code generation
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  ylabel('Sf')
 
  ylabel('Sf')
 
  xlabel('Time')
 
  xlabel('Time')
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</source>
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[[Category: ACADO]]

Revision as of 18:27, 31 January 2016

This is the implementation of the ACADO bioreactor example with the matlab interface and the code generation of ACADO.


 % implements the bioreactor example of ACADO for the matlab interface and
 % the code generation
 
 clc;
 clear all;
 close all;
 
 Ts = 0.1;
 EXPORT = 1;
 
 %% Variables
 DifferentialState X S P;
 Control Sf;
 
 n_XD = length(diffStates);
 n_U = length(controls);
 
 %% Constants
 D       = 0.15;
 Ki      = 22.0;
 Km      = 1.2 ; 
 Pm      = 50.0;
 Yxs     = 0.4 ;
 alpha   = 2.2 ;
 beta    = 0.2 ;
 mum     = 0.48;
 Sfmin   = 28.7;
 Sfmax   = 40.0;
 t_start =  0.0;
 t_end   = 48.0;
 N = 20;
 
 %% Differential Equation
 mu = mum*(1-P/Pm)*S/(Km+S+S^2/Ki);
 
 f = dot([X;S;P]) == [-D*X+mu*X;...
                       D*(Sf-S)-(mu/Yxs)*X;...
 		             -D*P+(alpha*mu+beta)*X];
 
 % output
 h = P-Sf;
 hN = P;
 
 %% MPCexport
 acadoSet('problemname', 'mpc');
 
 ocp = acado.OCP( t_start, t_end, N );
 
 W_mat = D;
 WN_mat = D;
 W = acado.BMatrix(W_mat);
 WN = acado.BMatrix(WN_mat);
 
 ocp.minimizeLSQ( W, h );
 ocp.minimizeLSQEndTerm( WN, hN );
 
 ocp.subjectTo( Sfmin <= Sf <= Sfmax );
 ocp.setModel(f);
 
 mpc = acado.OCPexport( ocp );
 mpc.set( 'HESSIAN_APPROXIMATION',       'GAUSS_NEWTON'      );
 mpc.set( 'DISCRETIZATION_TYPE',         'MULTIPLE_SHOOTING' );
 mpc.set( 'SPARSE_QP_SOLUTION',          'FULL_CONDENSING_N2');
 mpc.set( 'INTEGRATOR_TYPE',             'INT_IRK_GL4'       );
 mpc.set( 'NUM_INTEGRATOR_STEPS',        10*N                 );
 mpc.set( 'QP_SOLVER',                   'QP_QPOASES'    	);
 mpc.set( 'HOTSTART_QP',                 'NO'             	);
 mpc.set( 'LEVENBERG_MARQUARDT', 		 1e-10				);
 
 if EXPORT
     mpc.exportCode( 'export_MPC' );
     copyfile('../../../../../../external_packages/qpoases', 'export_MPC/qpoases')
 
     cd export_MPC
     make_acado_solver('../acado_MPCstep')
     cd ..
 end
 
 %% CONSTANTS FOR OPTIMIZATION
 X0 = [6.5 12.0 22.0];
 input.x0=X0';
 Xref = [0 0 0];
 input.x = repmat(Xref,N+1,1);
 Xref = repmat(Xref,N,1);
 input.od = [];
 
 Uref = zeros(N,n_U);
 input.u = Uref;
 
 input.y = 0*ones(N,1);
 input.yN = 0;
 
 input.W = D;
 input.WN = D;
 
 %% SOLVER LOOP (SQP - Gauss newton)
 display('------------------------------------------------------------------')
 display('               SOLVER Loop'                                    )
 display('------------------------------------------------------------------')
 
 
 
 for i=1:20
     tic
     % Solve NMPC OCP
     output = acado_MPCstep(input);
 
     input.x=output.x;
     input.u=output.u;
 
     disp([' (RTI step: ' num2str(output.info.cpuTime*1e6) ' µs)'])
 
 end
 
 %% PLOT RESULTS
 
 % States
 figure(1)
 plot([t_start:t_end/N:t_end],output.x)
 ylabel('States')
 xlabel('Time')
 legend('X','S','P')
 
 % Control
 figure(2)
 plot([t_start:t_end/N:t_end-t_end/N],output.u)
 ylabel('Control (Sf)')
 xlabel('Time')
 
 % one figure for all
 figure(3)
 subplot(2,2,1)
 plot([t_start:t_end/N:t_end],output.x(:,1))
 ylabel('X')
 xlabel('Time')
 subplot(2,2,2)
 plot([t_start:t_end/N:t_end],output.x(:,2))
 ylabel('S')
 xlabel('Time')
 subplot(2,2,3)
 plot([t_start:t_end/N:t_end],output.x(:,3))
 ylabel('P')
 xlabel('Time')
 subplot(2,2,4)
 plot([t_start:t_end/N:t_end-t_end/N],output.u)
 ylabel('Sf')
 xlabel('Time')