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authorYuan Xu <yuanxu@student.ethz.ch>2023-05-07 21:10:45 +0200
committerYuan Xu <yuanxu@student.ethz.ch>2023-05-07 21:10:45 +0200
commitce14ae31fcb13362ff341e54ace5dccc4f94c095 (patch)
treeb082d1e3201b40a73e9dbb4f124708e752941468 /templates/MPC.m
parentADD: progress log (diff)
downloadmpc_pe-ce14ae31fcb13362ff341e54ace5dccc4f94c095.tar.gz
mpc_pe-ce14ae31fcb13362ff341e54ace5dccc4f94c095.zip
update 15,16 and modify generate_constraints.m
Diffstat (limited to 'templates/MPC.m')
-rw-r--r--templates/MPC.m89
1 files changed, 80 insertions, 9 deletions
diff --git a/templates/MPC.m b/templates/MPC.m
index 3e9d2f1..b2d411d 100644
--- a/templates/MPC.m
+++ b/templates/MPC.m
@@ -6,6 +6,44 @@
% Please see the LICENSE file that has been included as part of this package.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% classdef MPC
+% properties
+% yalmip_optimizer
+% end
+%
+% methods
+% function obj = MPC(Q,R,N,params)
+% nu = params.model.nu;
+% nx = params.model.nx;
+%
+% % define optimization variables
+% U = sdpvar(repmat(nu,1,N),ones(1,N),'full');
+% X0 = sdpvar(nx,1,'full');
+%
+% % YOUR CODE HERE
+%
+% opts = sdpsettings('verbose',1,'solver','quadprog');
+% obj.yalmip_optimizer = optimizer(constraints,objective,opts,X0,{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
+
classdef MPC
properties
yalmip_optimizer
@@ -15,31 +53,64 @@ classdef MPC
function obj = MPC(Q,R,N,params)
nu = params.model.nu;
nx = params.model.nx;
-
+ % YOUR CODE HERE
% define optimization variables
+ A=params.model.A;
+ B=params.model.B;
U = sdpvar(repmat(nu,1,N),ones(1,N),'full');
+ X = sdpvar(repmat(nx,1,N+1),ones(1,N+1),'full');
+
+ [K,P,~] = dlqr(A,B,Q,R);
+
+ % define constraints
+% s_max=params.constraints.MaxAbsPositionXZ;
+% y_max=params.constraints.MaxAbsPositionY;
+% u_max = params.constraints.MaxAbsThrust;
+ H_x = params.constraints.StateMatrix;
+ h_x = params.constraints.StateRHS;
+ H_u = params.constraints.InputMatrix;
+ h_u = params.constraints.InputRHS;
X0 = sdpvar(nx,1,'full');
+ objective = 0;
+ constraints = X{1} == X0;
+ for k = 1:N
+ constraints = [ ...
+ constraints, ...
+ X{k+1} == A*X{k} + B*U{k} , ...
+ H_x * X{k} <= h_x, ...
+ H_u * U{k} <= h_u ...
+ ];
- % YOUR CODE HERE
-
+ objective = objective + X{k}'*Q*X{k} + U{k}'*R*U{k};
+ end
+ objective=objective+X{N+1}'*P*X{N+1};
+ % terminal constraint
+% constraints = [ ...
+% constraints, ...
+% X{N+1} == zeros(nx,1)
+% ];
opts = sdpsettings('verbose',1,'solver','quadprog');
obj.yalmip_optimizer = optimizer(constraints,objective,opts,X0,{U{1} objective});
end
function [u, ctrl_info] = eval(obj,x)
- %% evaluate control action by solving MPC problem, e.g.
+ % evaluate control action by solving MPC problem
tic;
- [optimizer_out,errorcode] = obj.yalmip_optimizer(x);
+ [optimizer_out,errorcode,~] = obj.yalmip_optimizer{x};
solvetime = toc;
-
- [u, objective] = optimizer_out{:};
- feasible = true;
+ % extract optimal control action and objective function value
+ u = optimizer_out{1};
+ objective = optimizer_out{2};
+
+ % check feasibility of optimization problem
+ feasible = ~isnan(objective) && ~isinf(objective);
if (errorcode ~= 0)
feasible = false;
end
+ % create control info struct
ctrl_info = struct('ctrl_feas',feasible,'objective',objective,'solvetime',solvetime);
end
end
-end \ No newline at end of file
+end