Take deliverables for soft contraints from yuanxu

Acording to table 9

  - MPC_TS_SC
  - MPC_TS_SC/eval
  - MPC_TS_SC_script (.m and MPC_TS_SC_params.mat output file)

3 files changed, 53 insertions, 3 deletions

diff --git a/templates/MPC_TS_SC.m b/templates/MPC_TS_SC.m
index 0e64767..fb1c720 100644
--- a/templates/MPC_TS_SC.m
+++ b/templates/MPC_TS_SC.m
@@ -14,22 +14,58 @@ classdef MPC_TS_SC
     methods
         function obj = MPC_TS_SC(Q,R,N,H,h,S,v,params)            
             % YOUR CODE HERE
+            % initialize parameters
+            nu = params.model.nu;
+            nx = params.model.nx;
+            A=params.model.A;
+            B=params.model.B;
+            H_x = params.constraints.StateMatrix;
+            h_x = params.constraints.StateRHS;
+            H_u = params.constraints.InputMatrix;
+            h_u = params.constraints.InputRHS;
+            [~,P,~] = dlqr(A,B,Q,R);
+
+            U = sdpvar(repmat(nu,1,N),ones(1,N),'full');
+            X = sdpvar(repmat(nx,1,N+1),ones(1,N+1),'full');
+            sv = sdpvar(repmat(length(S(1,:)),1,N+1),ones(1,N+1),'full');
+
+            X0 = sdpvar(nx,1,'full');
+            objective = 0;
+            constraints = X{1} == X0;      
+            % items for 1 to N
+            for k=1:N
+                objective = objective + X{k}' * Q * X{k} + U{k}' * R * U{k} + sv{k}' * S * sv{k} + v * max(sv{k});
+                constraints = [constraints, ...
+                    X{k+1} == A * X{k} + B * U{k}, ...
+                    H_x * X{k} <= h_x+sv{k}, ...
+                    H_u * U{k} <= h_u, ...
+                    sv{k} >= 0 ...
+                ];
+            end
+            % items for N+1
+                objective = objective + X{N+1}'*P*X{N+1} + sv{N+1}'*S*sv{N+1} + v*max(sv{N+1});
+                constraints = [constraints, ...
+                    sv{N+1} >= 0, ...
+                    H_x * X{N+1} <= h_x + sv{N+1} ...
+                ];
+            % maximum positively invariant set constraint
+            constraints = [constraints, H * X{N+1} <= h];
             opts = sdpsettings('verbose',1,'solver','quadprog','quadprog.TolFun',1e-8);
             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
diff --git a/templates/MPC_TS_SC_params.mat b/templates/MPC_TS_SC_params.mat
new file mode 100644
index 0000000..b8cc020
--- /dev/null
+++ b/templates/MPC_TS_SC_params.mat
diff --git a/templates/MPC_TS_SC_script.m b/templates/MPC_TS_SC_script.m
new file mode 100644
index 0000000..9499cf1
--- /dev/null
+++ b/templates/MPC_TS_SC_script.m
@@ -0,0 +1,14 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% 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.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+S=100000000*eye(6);
+v=100000000;
+matfile=struct("S",S,"v",v);
+save("MPC_TS_SC_params.mat","-struct","matfile")
+
+