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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright (c) 2023, Amon Lahr, Simon Muntwiler, Antoine Leeman & Fabian Flürenbrock Institute for Dynamic Systems and Control, ETH Zurich.
%
% All rights reserved.
%
% Please see the LICENSE file that has been included as part of this package.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
classdef MPC_TE
properties
yalmip_optimizer
end
methods
function obj = MPC_TE(Q,R,N,params)
% YOUR CODE HERE
opts = sdpsettings('verbose',1,'solver','quadprog');
% Create yalmip variables
U = sdpvar(repmat(params.model.nu,N,1),ones(1,N));
X = sdpvar(repmat(params.model.nx,N+1,1),ones(1,N+1));
% Build cost function and constraints
objective = 0;
constraints = [];
for k=1:N+1
if k <= N
% These constraints are for the index in 1, ..., N
objective = objective + X{k}' * Q * X{k} + U{k}' * R * U{k};
constraints = [constraints, ...
X{k+1} == params.model.A * X{k} + params.model.B * U{k}, ...
params.constraints.InputMatrix * U{k} <= params.constraints.InputRHS, ...
];
end
% These contrains are for 1, ..., N+1
constraints = [constraints, ...
params.constraints.StateMatrix * X{k} <= params.constraints.StateRHS, ...
];
end
% Terminal constraint
constraints = [constraints, X{N+1} == zeros(size(X{N+1}))];
obj.yalmip_optimizer = optimizer(constraints,objective,opts,X{1},{U{1} objective});
end
function [u, ctrl_info] = eval(obj,x)
%% evaluate control action by solving MPC problem, e.g.
tic;
[optimizer_out,errorcode] = obj.yalmip_optimizer(x);
solvetime = toc;
[u, objective] = optimizer_out{:};
feasible = true;
if (errorcode ~= 0)
feasible = false;
end
ctrl_info = struct('ctrl_feas',feasible,'objective',objective,'solvetime',solvetime);
end
end
end
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