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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.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [tuning_struct, i_opt] = lqr_tuning(x0,Q,params)
% YOUR CODE HERE
i_opt = nan;
best_J_u = inf;
% Prepare an array of empty structs
tuning_struct = repmat(struct( ...
'InitialCondition', {}, ...
'Qdiag', {}, ...
'MaxAbsPositionXZ', {}, ...
'MaxAbsPositionY', {}, ...
'MaxAbsThrust', {}, ...
'InputCost', {}, ...
'MaxFinalPosDiff', {}, ...
'MaxFinalVelDiff', {}, ...
'TrajFeasible', {} ...
), size(Q,2), 1);
for i=1:size(Q,2)
tuning_struct(i).InitialCondition = x0;
tuning_struct(i).Qdiag = Q(:,i);
ctrl = LQR(diag(Q(:,i)), eye(params.model.nu), params);
[Xt, Ut, ~] = simulate(x0, ctrl, params);
[s_max, y_max, u_max, J_u, df_max, vf_max, traj_feas] = ...
traj_constraints(Xt, Ut, params);
tuning_struct(i).MaxAbsPositionXZ = s_max;
tuning_struct(i).MaxAbsPositionY = y_max;
tuning_struct(i).MaxAbsThrust = u_max;
tuning_struct(i).InputCost = J_u;
tuning_struct(i).MaxFinalPosDiff = df_max;
tuning_struct(i).MaxFinalVelDiff = vf_max;
tuning_struct(i).TrajFeasible = traj_feas;
if traj_feas
if J_u < best_J_u
i_opt = i;
best_J_u = J_u;
end
end
end
% because the test suite wants a column vector
tuning_struct = tuning_struct';
end
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