@@ -726,7 +726,7 @@ Predict the current `ŷs` and future `Ŷs` stochastic model outputs over `Hp`.
726726
727727See [`init_stochpred`](@ref) for details on `Ŷs` and `Ks` matrices.
728728"""
729- predict_stoch (mpc, estim:: StateEstimator , x̂s, d , _ ) = (estim. Cs* x̂s, mpc. Ks* x̂s)
729+ predict_stoch (mpc, estim:: StateEstimator , x̂s, _ , _ ) = (estim. Cs* x̂s, mpc. Ks* x̂s)
730730
731731"""
732732 predict_stoch(mpc, estim::InternalModel, x̂s, d, ym )
@@ -809,7 +809,7 @@ Optimize the `mpc` quadratic objective function for [`LinMPC`](@ref) type.
809809function optim_objective! (mpc:: LinMPC , b, q̃, p)
810810 optim = mpc. optim
811811 model = mpc. estim. model
812- ΔŨ = optim[:ΔŨ ]
812+ ΔŨ:: Vector{VariableRef} = optim[:ΔŨ ]
813813 lastΔŨ = mpc. info. ΔŨ
814814 set_objective_function (optim, obj_quadprog (ΔŨ, mpc. P̃, q̃))
815815 set_normalized_rhs .(optim[:linconstraint ], b)
@@ -834,9 +834,9 @@ function optim_objective!(mpc::LinMPC, b, q̃, p)
834834 @warn " MPC termination status not OPTIMAL or LOCALLY_SOLVED ($status )"
835835 @debug solution_summary (optim)
836836 end
837- ΔŨ = isfatal (status) ? ΔŨ0 : value .(ΔŨ) # fatal status : use last value
838- J = objective_value (optim) + p # optimal objective value by adding constant p
839- return ΔŨ, J
837+ ΔŨ_val = isfatal (status) ? ΔŨ0 : value .(ΔŨ) # fatal status : use last value
838+ J_val = objective_value (optim) + p # optimal objective value by adding constant p
839+ return ΔŨ_val, J_val
840840end
841841
842842"""
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