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pwa_bounds_single.m
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pwa_bounds_single.m
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function PWABounds = pwa_bounds_single(nlfun, Option)
% Nonlinear function: nlfun.Handle
% Vertices: nlfun.X
% Domain: nlfun.Domain
% Resolution: nlfun.Resolution
% Parameters: nlfun.Param
% The linearization point: nlfun.xstar
% The linear approximation: nlfun.AbarLin
if nargin == 1,
Option.ObjFun = 'L2';
Option.Type = 'AP'; % 'LB','UB','AP'
Option.SafetyBound = 0.0; %
else
if ~isfield(Option,'ObjFun'),
Option.ObjFun = 'L2';
end
if ~isfield(Option,'Type'),
Option.Type = 'AP'; % 'LB','UB','AP'
end
if ~isfield(Option,'SafetyBound'),
Option.SafetyBound = 0.0;
end
end
f = nlfun.Handle; % Specify the handle of the nonlinear function
a=[];
b=[];
for i=1:length(nlfun.Domain),
a=[a; nlfun.Domain{i}(1)]; % Set start point of the domain
b=[b; nlfun.Domain{i}(end)]; % Set start point of the domain
end
N = nlfun.Resolution; % The resolution of sampling
X = nlfun.X; % Vertices of the partition
if isfield(nlfun,'Param'),
Param = nlfun.Param; % Parameters of the nonlinear function
elseif isfield(nlfun,'Parameters'),
Param = nlfun.Parameters; % Parameters of the nonlinear function
else
Param = [];
end
[m n] = size(X);
if n == 1,
X = sort(X);
end
for i = 1:n,
if a(i) >= b(i), % Check ?
eval(['error(''nlfun.domain(1,' num2str(i) ') should be less than nlfun.domain(2,' num2str(i) ').'');'])
end
end
try
Y = pwa_nlfun(nlfun,a,Param);
catch
error(['The function can not be evaluated.']);
end
% Create fine mesh
W = pwa_grid(a,b,N);
Z = pwa_nlfun(nlfun,W,Param);
p = size(W,1);
q = size(Z,2);
Ver = ver('MATLAB');
if str2num(Ver.Version(1)) == 7,
T = delaunayn(X,{'Qt','Qbb','Qc','Qz'});
else
T = delaunayn(X);
end
numt = size(T,1); % Determine number of triangulations (cells)
constraints = set([]);
for i = 1:numt,
Abar{i} = sdpvar(q,n+1,'full'); % PWA approximation parameters
end
% The approximation is exact at xstar
if isfield(nlfun,'xstar'),
% if n == 2,
% t = tsearch(X(:,1),X(:,2),T,nlfun.xstar(1),nlfun.xstar(2));
% else
t = tsearchn(X,T,nlfun.xstar');
% end
constraints = constraints + set(Abar{t}*[nlfun.xstar;1] == pwa_nlfun(nlfun,nlfun.xstar',Param)',['Abar' num2str(t) '=AbarLin']);
end
% Continuity constraints
if numt > 1,
for i = 1:m,
Ti = find(any((T==i)'));
if length(Ti) > 1,
for j = 1:length(Ti)-1,
k = j+1;
constraints = constraints + set((Abar{Ti(k)}-Abar{Ti(j)})*[X(i,:) 1]'==0,['(Abar' num2str(Ti(k)) '-Abar' num2str(Ti(j)) ')*[X(' num2str(i) ',:) 1]''=0']);
end
end
end
end
% Error
% if n == 2,
% t = tsearch(X(:,1),X(:,2),T,W(:,1),W(:,2));
% else
t = tsearchn(X,T,W);
% end
% Objective
if ~isfield(Option,'ObjFun'),
Option.ObjFun = 'L2';
end
Err=[];
if strcmp(Option.ObjFun,'L2'),
Obj = 0;
for i = 1:p,
if strcmp(Option.Type,'LB'),
if W(i,:)>nlfun.xstar,
constraints = constraints + set(Z(i,:)'-Option.SafetyBound*sat(abs(W(i,:)-nlfun.xstar))>Abar{t(i)}*[W(i,:) 1]','Z>AbarWbar');
elseif W(i,:)<nlfun.xstar,
constraints = constraints + set(Z(i,:)'+Option.SafetyBound*sat(abs(W(i,:)-nlfun.xstar))<Abar{t(i)}*[W(i,:) 1]','Z<AbarWbar');
end
elseif strcmp(Option.Type,'UB'),
if W(i,:)>nlfun.xstar,
constraints = constraints + set(Z(i,:)'+Option.SafetyBound*sat(abs(W(i,:)-nlfun.xstar))<Abar{t(i)}*[W(i,:) 1]','Z<AbarWbar');
elseif W(i,:)<nlfun.xstar,
constraints = constraints + set(Z(i,:)'-Option.SafetyBound*sat(abs(W(i,:)-nlfun.xstar))>Abar{t(i)}*[W(i,:) 1]','Z>AbarWbar');
end
end
Error = Z(i,:)'-Abar{t(i)}*[W(i,:) 1]';
Obj = Obj + sum(sum(Error.*Error));
Err = [Err; Error'];
end
end
% Solve the optimization problem
solvesdp(constraints,Obj,sdpsettings('usex0',1,'shift',1e-7)); %,sdpsettings('solver','SEDUMI'));
%solution = solvesdp(constraints,Obj,sdpsettings('solver','SEDUMI'));
checkset(constraints);
for i = 1:length(Abar),
Abar{i} = double(Abar{i});
end
Obj = double(Obj);
Err = double(Err);
Y = [];
for i = 1:m,
J = find(any((T==i)'));
Y = [Y; (Abar{J(1)}*[X(i,:) 1]')'];
end
PWABounds.Abar = Abar;
PWABounds.Obj = Obj;
PWABounds.X = X;
PWABounds.Y = Y;
PWABounds.W = W;
PWABounds.Z = Z;
PWABounds.T = T;
PWABounds.Err = Err;
function y = sat(x)
if abs(x)<1,
y=x;
else,
y = sign(x);
end