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authorNao Pross <np@0hm.ch>2023-05-24 16:29:40 +0200
committerNao Pross <np@0hm.ch>2023-05-24 16:32:02 +0200
commit0105f2746c6dd8c3617f93fd3281f7e2708cae76 (patch)
tree5a630201702256df343dec6aca126bdd1bdc3349 /templates/MPC.m
parentTake deliverables for uncontrained optimal control from npross (diff)
downloadmpc_pe-0105f2746c6dd8c3617f93fd3281f7e2708cae76.tar.gz
mpc_pe-0105f2746c6dd8c3617f93fd3281f7e2708cae76.zip
Take deliverables for from LQR to MPC from yuanxu
According to table 7 that is - lqr_maxPI - traj_cost - MPC - MPC/eval (contained in MPC.m)
Diffstat (limited to 'templates/MPC.m')
-rw-r--r--templates/MPC.m44
1 files changed, 35 insertions, 9 deletions
diff --git a/templates/MPC.m b/templates/MPC.m
index 3e9d2f1..355eb81 100644
--- a/templates/MPC.m
+++ b/templates/MPC.m
@@ -15,31 +15,57 @@ classdef MPC
function obj = MPC(Q,R,N,params)
nu = params.model.nu;
nx = params.model.nx;
-
- % define optimization variables
+ % YOUR CODE HERE
+ 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);
+
+% 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;
if (errorcode ~= 0)
feasible = false;
end
-
ctrl_info = struct('ctrl_feas',feasible,'objective',objective,'solvetime',solvetime);
end
end
-end \ No newline at end of file
+end