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I am using MPC.jl in a module. When running ModelPredictiveControl.plot(res; plotx=true, ploty=true, plotu=true, plotxwithx̂=true) I get the error:
ERROR: MethodError: no method matching plot(::ModelPredictiveControl.SimResult{Float64, ModelPredictiveControl.LinMPC{…}}; plotx::Bool, ploty::Bool, plotu::Bool, plotxwithx̂::Bool)
Closest candidates are:
plot(::Nothing, ::ModelPredictiveControl.SimResult{<:Real, <:ModelPredictiveControl.PredictiveController}) got unsupported keyword arguments "plotx", "ploty", "plotu", "plotxwithx̂"
@ ModelPredictiveControl ~/.julia/packages/ModelPredictiveControl/0rhFm/src/plot_sim.jl:325
plot(::Nothing, ::ModelPredictiveControl.SimResult{<:Real, <:ModelPredictiveControl.StateEstimator}) got unsupported keyword arguments "plotx", "ploty", "plotu", "plotxwithx̂"
@ ModelPredictiveControl ~/.julia/packages/ModelPredictiveControl/0rhFm/src/plot_sim.jl:324
plot(::Nothing, ::ModelPredictiveControl.SimResult{<:Real, <:ModelPredictiveControl.SimModel}) got unsupported keyword arguments "plotx", "ploty", "plotu", "plotxwithx̂"
@ ModelPredictiveControl ~/.julia/packages/ModelPredictiveControl/0rhFm/src/plot_sim.jl:323
Stacktrace:
[1] plot(ci::ControlInterface)
@ KitePredictiveControl ~/Code/KitePredictiveControl.jl/src/KitePredictiveControl.jl:209
[2] top-level scope
@ ./REPL[17]:5
Some type information was truncated. Use `show(err)` to see complete types.I don't know what could cause this. It worked before, but after some code reformatting, it stopped working.
julia> typeof(res)
SimResult{Float64, LinMPC{Float64, KalmanFilter{Float64, LinModel{Float64}}, JuMP.Model}}
julia> res.obj
LinMPC controller with a sample time Ts = 0.05 s, DAQP optimizer, KalmanFilter estimator and:
20 prediction steps Hp
4 control steps Hc
1 slack variable ϵ (control constraints)
3 manipulated inputs u (3 integrating states)
78 estimated states x̂
26 measured outputs ym (23 integrating states)
0 unmeasured outputs yu
0 measured disturbances d
julia> res.X_data
52×800 Matrix{Float64}:
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 12.1372 12.4948 12.1372 12.1184
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.420671 0.398937 0.420671 0.420346
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 26.1225 24.0023 26.1225 26.1313
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12.1372 12.4948 12.1372 12.1184
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.420671 -0.398937 -0.420671 -0.420346
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 26.1225 24.0023 26.1225 26.1313
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.23948 2.17889 2.23948 2.23148
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.14705e-11 0.0 1.76796e-11 1.65288e-11
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25.0963 24.9049 25.0963 25.102
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.14923 0.0 0.14923 0.15375
⋮ ⋮ ⋮ ⋮ ⋱ ⋮ ⋮
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.308326 0.0 0.308326 0.210995
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.338401 0.0 -0.338401 -0.269748
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.05014e-12 0.0 -7.45084e-12 -4.56091e-11
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.307788 0.0 0.307788 0.209391
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 57.611 57.6066 57.611 57.611
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 57.611 57.6066 57.611 57.611
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 50.1319 50.0 50.1319 50.1404
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.00112142 0.0 0.00112142 0.0011503
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.00112142 0.0 0.00112142 0.0011503
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.16879 0.0 0.16879 0.169753Metadata
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