How to set a constraint to limit rate of change of output in s function

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I have a simulink model where I have used an s-function block and based on the value of Preq and SOC the s-function provides an output based the algorithm shown below. I want the rate of change of output y(1) to be limited to 50. Please let me know how to do it. I am using fmincon optimization to obtain the output. I think a non linear constraint must be used to do this where the difference between the current output value and the previous output value must be 50. but I do not know how to call the current output value and previous output value while using an s function
function [sys,x0,str,ts,simStateCompliance] = trail1(t,x,u,flag)
switch flag
% Initialization %
case 0
[sys,x0,str,ts,simStateCompliance]=mdlInitializeSizes;
% Derivatives %
case 1
sys=mdlDerivatives(t,x,u);
% Update %
case 2
sys=mdlUpdate(t,x,u);
% Outputs %
case 3
sys=mdlOutputs(t,x,u);
% GetTimeOfNextVarHit %
case 4
sys=mdlGetTimeOfNextVarHit(t,x,u);
% Terminate %
case 9
sys=mdlTerminate(t,x,u);
% Unexpected flags %
otherwise
DAStudio.error('Simulink:blocks:unhandledFlag', num2str(flag));
end
% end sfuntmpl
%
%=============================================================================
% mdlInitializeSizes
% Return the sizes, initial conditions, and sample times for the S-function.
%=============================================================================
%
function [sys,x0,str,ts,simStateCompliance]=mdlInitializeSizes
sizes = simsizes;
sizes.NumContStates = 0;
sizes.NumDiscStates = 0;
sizes.NumOutputs = 3; %% the three outputs are the power delivered by fuel cell, battery and the equivalent factor
sizes.NumInputs = 2; %% Inputs are Power required and SOC
sizes.DirFeedthrough = 1; %% because output is a function of SOC
sizes.NumSampleTimes = 1; %% at least one sample time is needed
sys = simsizes(sizes);
%
% initialize the initial conditions
%
x0 = [];
%
% str is always an empty matrix
%
str = [];
%
% initialize the array of sample times
%
ts = [-1 0];
% Specify the block simStateCompliance. The allowed values are:
% 'UnknownSimState', < The default setting; warn and assume DefaultSimState
% 'DefaultSimState', < Same sim state as a built-in block
% 'HasNoSimState', < No sim state
% 'DisallowSimState' < Error out when saving or restoring the model sim state
simStateCompliance = 'UnknownSimState';
% end mdlInitializeSizes
%
%=============================================================================
% mdlDerivatives
% Return the derivatives for the continuous states.
%=============================================================================
%
function sys=mdlDerivatives(t,x,u) %#ok<*INUSD>
sys = [];
% end mdlDerivatives
%
%=============================================================================
% mdlUpdate
% Handle discrete state updates, sample time hits, and major time step
% requirements.
%=============================================================================
%
function sys=mdlUpdate(t,x,u)
sys = [];
% end mdlUpdate
%
%=============================================================================
% mdlOutputs
% Return the block outputs.
%=============================================================================
%
function sys=mdlOutputs(t,x,u)
%constants initialization
Pbatt_char= 7000;
SOC_min=0.4;
SOC_max=0.90;
Pfc_min=5000;
Pfc_max=7000;
Pbatt_max=15000;
%define Matrix Aeq
Aeq=[0 1 0;1 0 1];
%define Matrix beq
mu = 0.6;
beq=[(1-2*mu*((u(2)-0.5*(SOC_max-SOC_min))/(SOC_max-SOC_min))); u(1)];
%define boundary conditions
lb=[Pfc_min, 0, -Pbatt_char];
ub=[Pfc_max, 100, Pbatt_max];
%defining initial conditions
x0 = [7000 0 6000];
options = optimoptions('fmincon','Algorithm','active-set','Display','off','MaxFunctionEvaluations',1000,'MaxIterations',100);
[y,fval] = fmincon('OF_ECMS',x0,[],[],Aeq,beq,lb,ub,[],options); %#ok<*ASGLU>
Pfc=y(1); Pbatt=y(3); alpha=y(2);
sys = [Pfc Pbatt alpha];
% end mdlOutputs
%
%=============================================================================
% mdlGetTimeOfNextVarHit
% Return the time of the next hit for this block. Note that the result is
% absolute time. Note that this function is only used when you specify a
% variable discrete-time sample time [-2 0] in the sample time array in
% mdlInitializeSizes.
%=============================================================================
%
function sys=mdlGetTimeOfNextVarHit(t,x,u)
sampleTime = 1; % Example, set the next hit to be one second later.
sys = t + sampleTime;
% end mdlGetTimeOfNextVarHit
%
%=============================================================================
mdlTerminate
Perform any end of simulation tasks.
% =============================================================================
function sys=mdlTerminate(t,x,u)
sys = [];
% end mdlTerminate
Objective function code is
function f = OF_ECMS(x)
f = (x(1)+x(2)*x(3));
  2 个评论
aditya deepak
aditya deepak 2022-11-7
编辑:aditya deepak 2022-11-7
Thank you for your reply. There is a requirement that the sum of outputs y(1) and y(3) should equal to demand and by using the rate limiter that requirement would not be satisfied. I am using fmincon optimization to obtain the output. I think a non linear constraint must be used to do this where the difference between the current output value and the previous output value must be 50. but I do not know how to call the current output value and previous output value while using an s function.

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回答(1 个)

Stephen Eltinge
Stephen Eltinge 2022-12-7
Hi aditya,
To write an S-Function block that recalls its previous output, please look into adding a discrete state to the S-Function. See the "unit delay" Level-2 MATLAB S-Function example for a simple starting point. You should then be able to use the state's data to provide an additional constraint for your optimization function.
  6 个评论
aditya deepak
aditya deepak 2023-1-10
I converted the level 1 s function to level 2 s function and I am getting the following error
Undefined function 'OutPort' for input arguments of type 'Simulink.MSFcnRunTimeBlock'.
function ECMSsf2(block)
setup(block);
%endfunction
function setup(block)
%% Register number of input and output ports
block.NumInputPorts = 2;
block.NumOutputPorts = 3;
%% Setup functional port properties to dynamically
%% inherited.
block.SetPreCompInpPortInfoToDynamic;
block.SetPreCompOutPortInfoToDynamic;
block.InputPort(1).DirectFeedthrough = false;
%% Set block sample time to inherited
block.SampleTimes = [-1 0];
%% Set the block simStateCompliance to default (i.e., same as a built-in block)
block.SimStateCompliance = 'DefaultSimState';
%% Register methods
block.RegBlockMethod('PostPropagationSetup',@DoPostPropSetup);
block.RegBlockMethod('InitializeConditions',@InitConditions);
block.RegBlockMethod('SetInputPortSamplingMode', @SetInpPortFrameData);
block.RegBlockMethod('Outputs', @Output);
block.RegBlockMethod('Update', @Update);
function DoPostPropSetup(block)
%% Setup Dwork
block.NumDworks = 1;
block.Dwork(1).Name = 'x0';
block.Dwork(1).Dimensions = 1;
block.Dwork(1).DatatypeID = 0;
block.Dwork(1).Complexity = 'Real';
block.Dwork(1).UsedAsDiscState = true;
end
function InitConditions(block)
% Initialize Dwork
block.Dwork(1).Data = 0;
end
function SetInpPortFrameData(block, idx, fd)
block.InputPort(idx).SamplingMode = fd;
block.InputPort(idx).SamplingMode = fd;
block.OutputPort(1).SamplingMode = fd;
block.OutputPort(2).SamplingMode = fd;
block.OutputPort(3).SamplingMode = fd;
end
function Output(block)
%constants initialization
Pbatt_char=5000;
SOC_min=0.2;
SOC_max=0.90;
Pfc_min=1000;
Pfc_max=10000;
Pbatt_max=17000;
%define Matrix Aeq
Aeq=[0 1 0;1 0 1];
%define Matrix beq
mu = 0.6;
beq=[(1-2*mu*((block.InputPort(2).Data-0.5*(SOC_max+SOC_min))/(SOC_max+SOC_min))); block.InputPort(1).Data];
%define boundary conditions
lb=[Pfc_min, 0, -Pbatt_char];
ub=[Pfc_max, 100, Pbatt_max];
%defining initial conditions
x0 = [0 0 0];
options = optimoptions('fmincon','Algorithm','active-set','Display','off','MaxFunctionEvaluations',1000,'MaxIterations',100);
nonlcon=@(y) Nonlinearequations(y,block);
[y,fval] = fmincon(@OF_ECMS,x0,[],[],Aeq,beq,lb,ub,nonlcon,options);
function f = OF_ECMS(y) %<----fix
f = (y(1)+y(2)*y(3));
end
function [c, ceq] = Nonlinearequations(y,block)%<----fix
c = [];
ceq = [];
PFCold = block.Dwork(1).Data;
c(1) = PFCold - y(1) - 20; %<----change to -20
c(2) = y(1) - PFCold - 20;
end
Pfc=y(1); Pbatt=y(3); alpha=y(2);
block.OutPort(1).Data = Pfc;
block.OutPort(2).Data = Pbatt;
block.OutPort(3).Data = alpha;
end
function Update(block)
block.Dwork(1).Data = block.Outport(1).Data;
end
end
end
Stephen Eltinge
Stephen Eltinge 2023-1-10
Hi aditya,
Please try replacing "OutPort" with "OutputPort" in its four occurrences near the end of your code.

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