diff --git a/numerical_example.ipynb b/numerical_example.ipynb
index f15f9182ce18419ec55854ccd7d6618d8dfbe6a7..f60d4b4f5cbc97bb9f624aafab0e46b564b43228 100644
--- a/numerical_example.ipynb
+++ b/numerical_example.ipynb
@@ -10,7 +10,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 1,
"id": "cffe7517-257d-4022-a6dc-6a0e34f758f2",
"metadata": {},
"outputs": [
@@ -61,7 +61,7 @@
},
{
"cell_type": "code",
- "execution_count": 67,
+ "execution_count": 2,
"id": "fbf3188d-3b03-4fb9-954a-523dd95027d6",
"metadata": {},
"outputs": [
@@ -71,7 +71,7 @@
"simultanueousStabilization (generic function with 1 method)"
]
},
- "execution_count": 67,
+ "execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@@ -109,17 +109,17 @@
},
{
"cell_type": "code",
- "execution_count": 68,
+ "execution_count": 3,
"id": "289848c2-54ca-4bad-b3c8-75b678de6e46",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "A_avg_diff (generic function with 1 method)"
+ "getKs (generic function with 1 method)"
]
},
- "execution_count": 68,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -140,43 +140,130 @@
" A_diff = (As[i] - Bs[i] * Ks[k] - As[j] + Bs[j] * Ks[k]) / 2\n",
" return A_avg, A_diff\n",
"end\n",
- "\n"
+ "\n",
+ "function getKs(As, Bs, G, Q, R, γ)\n",
+ " \n",
+ " nmodels = length(As)\n",
+ " Ps = Vector{Matrix{Float64}}(undef, nmodels)\n",
+ " Ks = Vector{Matrix{Float64}}(undef, nmodels)\n",
+ " for i = 2:length(As)-1\n",
+ " Ps[i], Ks[i], ts = simultanueousStabilization(As[i-1:i+1], Bs[i-1:i+1], G, Q, R, γ)\n",
+ " @assert ts == MOI.OPTIMAL\n",
+ " end\n",
+ " (Ps[1], Ks[1], ts) = simultanueousStabilization(As[1:2], Bs[1:2], G, Q, R, γ) \n",
+ " @assert ts == MOI.OPTIMAL\n",
+ " (Ps[nmodels], Ks[nmodels], ts) = simultanueousStabilization(As[nmodels - 1:nmodels], Bs[nmodels - 1:nmodels], G, Q, R, γ) \n",
+ " @assert ts == MOI.OPTIMAL\n",
+ " return Ks, Ps\n",
+ "end"
]
},
{
"cell_type": "code",
- "execution_count": 103,
- "id": "bf8fbd2e-c031-44ed-ba9e-342fb64d4f14",
+ "execution_count": 13,
+ "id": "1e9341f8-0052-432d-8110-1ad592ce1ad7",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "synthesizePijs (generic function with 2 methods)"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "(nx, nw, nu) = (1,1,1)\n",
- "As = -2:0.5:2\n",
- "As = [fill(A, 1, 1) for A in As]\n",
- "Bs = ones(length(As))\n",
- "Bs = [fill(B, 1, 1) for B in Bs]\n",
- "G = fill(1.0,1,1)\n",
- "Q = fill(1.0, 1,1)\n",
- "R = fill(1.0,1, 1)\n",
- "Ks = similar(Bs)\n",
- "Ps = similar(As)\n",
- "γ = 15\n",
- "nmodels = length(As)\n",
- "for i = 2:length(As)-1\n",
- " Ps[i], Ks[i], ts = simultanueousStabilization(As[i-1:i+1], Bs[i-1:i+1], G, Q, R, γ)\n",
- " @assert ts == MOI.OPTIMAL\n",
+ "function synthesizePijs(As, Bs, Ks, G, Q, R, γ, transitions)\n",
+ " nx = size(As[1])[1]\n",
+ " nw = size(G)[2]\n",
+ " model = JuMP.Model(Mosek.Optimizer)\n",
+ " Ps = Dict{NTuple{2,Int},Array{VariableRef,2}}()\n",
+ " for i = 1:nmodels\n",
+ " for j = 1:nmodels\n",
+ " Ps[i, j] = @variable(model, [1:nx, 1:nx], PSD, base_name=\"Ps[$i, $j]\")\n",
+ " end\n",
+ " end\n",
+ " \n",
+ " for i = 1:nmodels\n",
+ " for j = 1:nmodels\n",
+ " if i!=j\n",
+ " @constraint(model, Ps[i,j] .== Ps[j,i])\n",
+ " end\n",
+ " for k = 1:nmodels\n",
+ " if((i != j) && (j ==k))\n",
+ " continue\n",
+ " end\n",
+ " for m ∈ transitions[j]\n",
+ " Aavg, Adiff = A_avg_diff(As, Bs, Ks, i, j, k)\n",
+ " ineq20 = switchingLMI(\n",
+ " Ps[m, k], \n",
+ " Ps[i, j], \n",
+ " Ks[k], \n",
+ " Aavg, \n",
+ " Adiff, \n",
+ " R,\n",
+ " γ\n",
+ " )\n",
+ " @constraint(model, ineq20 in PSDCone())\n",
+ " end\n",
+ " end\n",
+ " end\n",
+ " end\n",
+ " \n",
+ " optimize!(model)\n",
+ " \n",
+ " return Ps, model\n",
+ "end"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "5aff3c38-69fa-4c35-bf0c-5d3c54bb4c38",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "simulate_system! (generic function with 2 methods)"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "function simulate_system!(xs, us, rs, Vs, As, Bs, Ks, G, Q, R, γ, transitions, Pijs, Nsteps, ws, inds)\n",
+ " V(x, r) = maximum([x' * value.(Ps[i, j]) * x + (r[i] + r[j])/2 for i in 1:nmodels for j in 1:nmodels])\n",
+ " \n",
+ " \n",
+ " function update(rs, As, Bs, xplus, x, u)\n",
+ " rnew = zeros(nmodels)\n",
+ " for i = 1:nmodels\n",
+ " rnew[i] = maximum(rs[transitions[i]]) - γ^2 * (xplus - As[i] * x - Bs[i] * u)' * (xplus - As[i] * x - Bs[i] * u)\n",
+ " end\n",
+ " return rnew\n",
+ " end \n",
+ " \n",
+ " for t = 1:Nsteps\n",
+ " k = argmax(rs[:, t])\n",
+ " us[:, t] = -Ks[k] * xs[:, t]\n",
+ " xs[:, t + 1] = As[inds[t]] * xs[:, t] + Bs[inds[t]] * us[:, t] + ws[:, t]\n",
+ " rs[:, t + 1] = update(rs[:, t], As, Bs, xs[:, t + 1], xs[:, t], us[:, t])\n",
+ " Vs[t] = V(xs[:, t], rs[:, t])\n",
+ " end\n",
"end\n",
- "(Ps[1], Ks[1], ts) = simultanueousStabilization(As[1:2], Bs[1:2], G, Q, R, γ) \n",
- "@assert ts == MOI.OPTIMAL\n",
- "(Ps[nmodels], Ks[nmodels], ts) = simultanueousStabilization(As[nmodels - 1:nmodels], Bs[nmodels - 1:nmodels], G, Q, R, γ) \n",
- "@assert ts == MOI.OPTIMAL\n",
"\n"
]
},
{
"cell_type": "code",
- "execution_count": 104,
- "id": "4b046f66-a500-4dbd-af63-e2ed8f4de9be",
+ "execution_count": 15,
+ "id": "36dd891e-b3d7-449a-8125-7c76147371a1",
"metadata": {},
"outputs": [
{
@@ -223,1368 +310,1316 @@
"1 1.1e+03 2.9e-01 6.4e-01 -9.98e-01 0.000000000e+00 1.458343177e+00 4.1e-01 0.06 \n",
"2 4.0e+02 1.0e-01 3.8e-01 -9.95e-01 0.000000000e+00 5.697193934e+00 1.5e-01 0.06 \n",
"3 7.7e+01 2.0e-02 1.6e-01 -9.84e-01 0.000000000e+00 3.226058372e+01 2.8e-02 0.07 \n",
- "4 2.1e+01 5.3e-03 7.6e-02 -9.02e-01 0.000000000e+00 9.953882379e+01 7.6e-03 0.07 \n",
+ "4 2.1e+01 5.3e-03 7.6e-02 -9.02e-01 0.000000000e+00 9.953882379e+01 7.6e-03 0.08 \n",
"5 6.9e+00 1.8e-03 3.3e-02 -6.39e-01 0.000000000e+00 1.683966024e+02 2.5e-03 0.08 \n",
- "6 5.3e+00 1.4e-03 2.5e-02 -1.90e-01 0.000000000e+00 1.622963938e+02 2.0e-03 0.08 \n",
+ "6 5.3e+00 1.4e-03 2.5e-02 -1.90e-01 0.000000000e+00 1.622963938e+02 2.0e-03 0.09 \n",
"7 1.7e+00 4.3e-04 6.7e-03 -6.06e-02 0.000000000e+00 1.221930970e+02 6.1e-04 0.09 \n",
- "8 3.3e-01 8.7e-05 7.4e-04 4.94e-01 0.000000000e+00 3.663565619e+01 1.2e-04 0.09 \n",
- "9 2.4e-02 1.2e-05 1.5e-05 8.81e-01 0.000000000e+00 2.892129662e+00 8.9e-06 0.10 \n",
- "10 6.3e-05 1.7e-06 2.0e-09 9.93e-01 0.000000000e+00 7.131566922e-03 2.2e-08 0.10 \n",
- "11 1.5e-08 7.6e-10 6.9e-15 1.00e+00 0.000000000e+00 1.618116788e-06 5.1e-12 0.11 \n",
- "12 1.9e-10 2.5e-16 9.2e-22 1.00e+00 0.000000000e+00 2.186080410e-13 6.9e-19 0.12 \n",
- "Optimizer terminated. Time: 0.13 \n",
+ "8 3.3e-01 8.7e-05 7.4e-04 4.94e-01 0.000000000e+00 3.663565619e+01 1.2e-04 0.10 \n",
+ "9 2.4e-02 1.2e-05 1.5e-05 8.81e-01 0.000000000e+00 2.892129662e+00 8.9e-06 0.11 \n",
+ "10 6.3e-05 1.7e-06 2.0e-09 9.93e-01 0.000000000e+00 7.131566922e-03 2.2e-08 0.11 \n",
+ "11 1.5e-08 7.6e-10 6.9e-15 1.00e+00 0.000000000e+00 1.618116788e-06 5.1e-12 0.12 \n",
+ "12 1.9e-10 2.5e-16 9.2e-22 1.00e+00 0.000000000e+00 2.186080410e-13 6.9e-19 0.13 \n",
+ "Optimizer terminated. Time: 0.14 \n",
"\n"
]
},
{
"data": {
"text/plain": [
- "OPTIMAL::TerminationStatusCode = 1"
+ "-1.1007247751683735"
]
},
- "execution_count": 104,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "model = JuMP.Model(Mosek.Optimizer)\n",
- "Ps = Dict{NTuple{2,Int},Array{VariableRef,2}}()\n",
+ "(nx, nw, nu) = (1,1,1)\n",
+ "As = -2:0.5:2\n",
+ "As = [fill(A, 1, 1) for A in As]\n",
+ "Bs = ones(length(As))\n",
+ "Bs = [fill(B, 1, 1) for B in Bs]\n",
+ "G = fill(1.0,1,1)\n",
+ "Q = fill(1.0, 1,1)\n",
+ "R = fill(1.0,1, 1)\n",
+ "γ = 15.0\n",
+ "nmodels = length(As)\n",
"transitions = [[i-1, i, i+1] for i = 1:nmodels]\n",
"transitions[1] = [1, 2]\n",
"transitions[nmodels] = [nmodels-1, nmodels]\n",
- "for i = 1:nmodels\n",
- " for j = 1:nmodels\n",
- " Ps[i, j] = @variable(model, [1:nx, 1:nx], PSD, base_name=\"Ps[$i, $j]\")\n",
- " end\n",
- "end\n",
- "\n",
- "for i = 1:nmodels\n",
- " for j = 1:nmodels\n",
- " if i!=j\n",
- " @constraint(model, Ps[i,j] .== Ps[j,i])\n",
- " end\n",
- " for k = 1:nmodels\n",
- " if((i != j) && (j ==k))\n",
- " continue\n",
- " end\n",
- " for m ∈ transitions[j]\n",
- " Aavg, Adiff = A_avg_diff(As, Bs, Ks, i, j, k)\n",
- " ineq20 = switchingLMI(\n",
- " Ps[m, k], \n",
- " Ps[i, j], \n",
- " Ks[k], \n",
- " Aavg, \n",
- " Adiff, \n",
- " R,\n",
- " γ\n",
- " )\n",
- " @constraint(model, ineq20 in PSDCone())\n",
- " end\n",
- " end\n",
- " end\n",
- "end\n",
- "\n",
- "optimize!(model)\n",
- "termination_status(model)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 105,
- "id": "5aff3c38-69fa-4c35-bf0c-5d3c54bb4c38",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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- "</svg>\n"
- ]
- },
- "execution_count": 105,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "\n",
- "V(x, r) = maximum([x' * value.(Ps[i, j]) * x + (r[i] + r[j])/2 for i in 1:nmodels for j in 1:nmodels])\n",
- "\n",
"Nsteps = 100\n",
+ "\n",
"xs = zeros(1, Nsteps + 1)\n",
"us = zeros(1, Nsteps)\n",
+ "rs = zeros(nmodels, Nsteps + 1)\n",
+ "Vs = zeros(Nsteps)\n",
"ws = randn(1, Nsteps)\n",
"inds = zeros(Int64, Nsteps)\n",
"inds[1] = rand(1:nmodels)\n",
- "rs = zeros(nmodels, Nsteps + 1)\n",
- "function update(rs, As, Bs, xplus, x, u)\n",
- " rnew = similar(rs)\n",
- " for i = 1:nmodels\n",
- " rnew[i] = maximum(rs[transitions[i]]) - γ^2 * (xplus - As[i] * x - Bs[i] * u)' * (xplus - As[i] * x - Bs[i] * u)\n",
- " end\n",
- " return rnew\n",
- "end\n",
- "Vs = zeros(Nsteps)\n",
"for t = 1:Nsteps - 1\n",
- " inds[t + 1] = rand(transitions[inds[t]])\n",
- "end\n",
- "\n",
- "for t = 1:Nsteps\n",
- " k = argmax(rs[:, t])\n",
- " us[:, t] = -Ks[k] * xs[:, t]\n",
- " xs[:, t + 1] = As[inds[t]] * xs[:, t] + Bs[inds[t]] * us[:, t] + ws[:, t]\n",
- " rs[:, t + 1] = update(rs[:, t], As, Bs, xs[:, t + 1], xs[:, t], us[:, t])\n",
- " Vs[t] = V(xs[:, t], rs[:, t])\n",
+ " inds[t + 1] = rand(transitions[inds[t]])\n",
"end\n",
+ "(Ks, Pis) = getKs(As, Bs, G, Q, R, γ)\n",
+ "(Ps, model) = synthesizePijs(As, Bs, Ks, G, Q, R, γ, transitions)\n",
+ "termination_status(model)\n",
+ "simulate_system!(xs, us, rs, Vs, As, Bs, Ks, G, Q, R, γ, Ps, Nsteps, ws, inds)\n",
"\n",
"plt1 = plot([a[1] for a in As[inds]], linewidth = 4, markershape= :auto, xlabel = \"t\", ylabel = \"a\", legend = false)\n",
"plt2 = plot(Vs, linewidth = 4, xlabel = \"t\", ylabel=\"Vbar\", legend = false)\n",
"plt3 = plot(xs', linewidth = 4, xlabel = \"t\", ylabel = \"x\", legend = false)\n",
"plt4 = plot(us', linewidth = 4, xlabel = \"t\", ylabel = \"u\", legend = false)\n",
- "plt_comp1 = plot(plt1, plt2, layout=(2,1))\n",
- "plt_comp2 = plot(plt3, plt4, layout=(2,1))\n"
+ "maximum(Vs[2:end] - Vs[1:(end-1)])"
]
},
{
"cell_type": "code",
- "execution_count": 106,
- "id": "ff7e0c13-cb1d-48cb-aa6f-018d097333bc",
+ "execution_count": 16,
+ "id": "2157c16c-faa1-4693-a41c-f0e6e55b14cc",
"metadata": {},
"outputs": [
{
"data": {
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",
+ "image/png": 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]
},
- "execution_count": 106,
+ "execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
+ "plt_comp1 = plot(plt1, plt2, layout=(2,1))\n",
+ "savefig(plt_comp1, \"a_and_Vbar.png\")\n",
"plt_comp1"
]
},
{
"cell_type": "code",
- "execution_count": 107,
- "id": "ddbe3849-12b4-49cd-b169-f03985725b48",
+ "execution_count": 17,
+ "id": "a2f43441-7dd2-42cf-b78b-d44c2a29026a",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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+ "</svg>\n"
]
},
- "execution_count": 107,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "plot(Vs[2:end] - Vs[1:end-1], linewidth = 3)"
+ "plt_comp2 = plot(plt3, plt4, layout=(2,1))\n",
+ "savefig(plt_comp2, \"x_and_u.png\")\n",
+ "plt_comp2"
]
},
{
"cell_type": "code",
- "execution_count": 108,
- "id": "760dc386-1074-4dae-afae-dadff9c5810a",
+ "execution_count": 18,
+ "id": "48aab4e6-c94a-4567-83a5-87909c03ac90",
"metadata": {},
"outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Problem\n",
+ " Name : \n",
+ " Objective sense : minimize \n",
+ " Type : CONIC (conic optimization problem)\n",
+ " Constraints : 72 \n",
+ " Affine conic cons. : 1825 (5475 rows)\n",
+ " Disjunctive cons. : 0 \n",
+ " Cones : 0 \n",
+ " Scalar variables : 0 \n",
+ " Matrix variables : 81 (scalarized: 81)\n",
+ " Integer variables : 0 \n",
+ "\n",
+ "Optimizer started.\n",
+ "Presolve started.\n",
+ "Linear dependency checker started.\n",
+ "Linear dependency checker terminated.\n",
+ "Eliminator started.\n",
+ "Freed constraints in eliminator : 0\n",
+ "Eliminator terminated.\n",
+ "Eliminator - tries : 1 time : 0.00 \n",
+ "Lin. dep. - tries : 1 time : 0.00 \n",
+ "Lin. dep. - primal attempts : 1 successes : 1 \n",
+ "Lin. dep. - dual attempts : 0 successes : 0 \n",
+ "Lin. dep. - primal deps. : 0 dual deps. : 0 \n",
+ "Presolve terminated. Time: 0.00 \n",
+ "Optimizer - threads : 4 \n",
+ "Optimizer - solved problem : the primal \n",
+ "Optimizer - Constraints : 5547 \n",
+ "Optimizer - Cones : 1825 \n",
+ "Optimizer - Scalar variables : 5556 conic : 5475 \n",
+ "Optimizer - Semi-definite variables: 0 scalarized : 0 \n",
+ "Factor - setup time : 0.05 \n",
+ "Factor - dense det. time : 0.01 GP order time : 0.00 \n",
+ "Factor - nonzeros before factor : 1.96e+04 after factor : 2.57e+04 \n",
+ "Factor - dense dim. : 75 flops : 6.44e+05 \n",
+ "ITE PFEAS DFEAS GFEAS PRSTATUS POBJ DOBJ MU TIME \n",
+ "0 2.7e+03 7.1e-01 1.0e+00 0.00e+00 0.000000000e+00 0.000000000e+00 1.0e+00 0.06 \n",
+ "1 1.1e+03 2.9e-01 6.4e-01 -9.98e-01 0.000000000e+00 1.458343177e+00 4.1e-01 0.07 \n",
+ "2 4.0e+02 1.0e-01 3.8e-01 -9.95e-01 0.000000000e+00 5.697193934e+00 1.5e-01 0.07 \n",
+ "3 7.7e+01 2.0e-02 1.6e-01 -9.84e-01 0.000000000e+00 3.226058372e+01 2.8e-02 0.08 \n",
+ "4 2.1e+01 5.3e-03 7.6e-02 -9.02e-01 0.000000000e+00 9.953882379e+01 7.6e-03 0.09 \n",
+ "5 6.9e+00 1.8e-03 3.3e-02 -6.39e-01 0.000000000e+00 1.683966024e+02 2.5e-03 0.09 \n",
+ "6 5.3e+00 1.4e-03 2.5e-02 -1.90e-01 0.000000000e+00 1.622963938e+02 2.0e-03 0.10 \n",
+ "7 1.7e+00 4.3e-04 6.7e-03 -6.06e-02 0.000000000e+00 1.221930970e+02 6.1e-04 0.10 \n",
+ "8 3.3e-01 8.7e-05 7.4e-04 4.94e-01 0.000000000e+00 3.663565619e+01 1.2e-04 0.11 \n",
+ "9 2.4e-02 1.2e-05 1.5e-05 8.81e-01 0.000000000e+00 2.892129662e+00 8.9e-06 0.12 \n",
+ "10 6.3e-05 1.7e-06 2.0e-09 9.93e-01 0.000000000e+00 7.131566922e-03 2.2e-08 0.12 \n",
+ "11 1.5e-08 7.6e-10 6.9e-15 1.00e+00 0.000000000e+00 1.618116788e-06 5.1e-12 0.13 \n",
+ "12 1.9e-10 2.5e-16 9.2e-22 1.00e+00 0.000000000e+00 2.186080410e-13 6.9e-19 0.14 \n",
+ "Optimizer terminated. Time: 0.14 \n",
+ "\n",
+ "Starting simulation no: 100\n",
+ "Starting simulation no: 200\n",
+ "Starting simulation no: 300\n",
+ "Starting simulation no: 400\n",
+ "Starting simulation no: 500\n",
+ "Starting simulation no: 600\n",
+ "Starting simulation no: 700\n",
+ "Starting simulation no: 800\n",
+ "Starting simulation no: 900\n",
+ "Starting simulation no: 1000\n"
+ ]
+ },
{
"data": {
"text/plain": [
- "-0.48212242133013206"
+ "-1.1661299595289165e-5"
]
},
- "execution_count": 108,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "maximum(Vs[2:end] - Vs[1:(end-1)])"
+ "(Ks, Pis) = getKs(As, Bs, G, Q, R, γ)\n",
+ "(Ps, model) = synthesizePijs(As, Bs, Ks, G, Q, R, γ, transitions)\n",
+ "function verify_dissipativity(As, Bs, Ks, G, Q, R, γ, transitions,Ps, Nsteps, Nsimulations)\n",
+ " xs = zeros(1, Nsteps + 1)\n",
+ " us = zeros(1, Nsteps)\n",
+ " rs = zeros(nmodels, Nsteps + 1)\n",
+ " Vs = zeros(Nsteps)\n",
+ " ws = randn(1, Nsteps)\n",
+ " ws = randn(1, Nsteps)\n",
+ " inds = zeros(Int64, Nsteps)\n",
+ " VDeltaMax = -Inf\n",
+ " for l = 1:Nsimulations\n",
+ " if l%100 == 0\n",
+ " print(\"Starting simulation no: \", l, \"\\n\")\n",
+ " end\n",
+ " inds[1] = rand(1:nmodels)\n",
+ " for t = 1:Nsteps - 1\n",
+ " inds[t + 1] = rand(transitions[inds[t]])\n",
+ " end\n",
+ " \n",
+ " termination_status(model)\n",
+ " simulate_system!(xs, us, rs, Vs, As, Bs, Ks, G, Q, R, γ, transitions, Ps, Nsteps, ws, inds)\n",
+ " VDeltaMax = max(VDeltaMax, maximum(Vs[2:end] - Vs[1:end-1]))\n",
+ " end\n",
+ " return VDeltaMax\n",
+ "end\n",
+ "Nsimulations = 1000\n",
+ "verify_dissipativity(As, Bs, Ks, G, Q, R, γ, transitions, Ps, Nsteps, Nsimulations)"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fca82e1f-f661-4c9b-b22e-cbb0fdc63bf4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {