Wolfram 语言与系统参考资料中心

SystemModelSimulate

SystemModelSimulate[model]

根据实验设置仿真 model.

SystemModelSimulate[model,t_max]

从 0 到 t_max 进行仿真.

SystemModelSimulate[model,{t_min,t_max}]

从 t_min 到 t_max 进行仿真.

SystemModelSimulate[model,vars,{t_min,t_max}]

只保存变量 vars 的仿真数据.

范例

打开所有单元关闭所有单元

基本范例 (3)

使用来自模型的仿真设置的时间间隔来对模型进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image]]

Wolfram Language code: SystemModelPlot[sim, {"y", "z"}]

在电压偏移量上做一个参数扫描：

Wolfram Language code: sim = SystemModelSimulate[[image], 1, <|"ParameterValues" -> {"sineVoltage1.offset" -> Range[5]}|>];

绘制所有仿真的电压：

Wolfram Language code: SystemModelPlot[sim, {"sineVoltage1.v"}]

用模型的框图表示作为输入：

Wolfram Language code: SystemModel["DocumentationExamples.Simulation.WeakAxis"]

复制并粘贴上述输出：

Wolfram Language code: SystemModelSimulate[\!$\*GraphicsBox[«8»]$]

或使用名称字符串：

Wolfram Language code: SystemModelSimulate["DocumentationExamples.Simulation.WeakAxis"]

范围 (24)

模型 (6)

仿真系统包含的一个热域示例模型：

Wolfram Language code: model = RandomChoice[SystemModelExamples["Models", "Modelica.Thermal.FluidHeatFlow.*"]]

Wolfram Language code: SystemModelSimulate[model]

仿真 NonlinearStateSpaceModel 并绘制仿真结果：

Wolfram Language code:

sim = SystemModelSimulate[NonlinearStateSpaceModel[{{Cos[x] + 4*Sin[x/2]}, 
  {x + Sin[x]}}, {x}, {}, {Automatic}, Automatic, 
 SamplingPeriod -> None]]

Wolfram Language code: SystemModelPlot[sim, All]

用 UnitStep 作为输入，仿真 TransferFunctionModel：

Wolfram Language code:

sim = SystemModelSimulate[TransferFunctionModel[{{{2*(1 - s)}}, 2*(1 + s/2 + s^2)}, 
 s], <|"Inputs" -> {1 -> UnitStep}|>]

Wolfram Language code: SystemModelPlot[sim, All, PlotRange -> All]

对 AffineStateSpaceModel 进行参数扫描：

Wolfram Language code:

sims = SystemModelSimulate[AffineStateSpaceModel[{{Cos[x2], (-a)*x2 + 
    Cos[x1^2]}, {{0}, {1}}, {x2}, {{0}}}, 
 {x1, x2}, Automatic, {Automatic}, Automatic, SamplingPeriod -> None], <|"ParameterValues" -> {a -> {0.1, 0.2}}|>]

Wolfram Language code: SystemModelPlot[sims, {x2}]

仿真 DiscreteInputOutputModel：

Wolfram Language code: diom = DiscreteInputOutputModel[{u[0] + y[-1] + y[-2], u[1] + u[0] + u[-1]}, {{u, {-2, -1, 1}}}, {{y, {-1, -1, -1}}}]

Wolfram Language code: sim = SystemModelSimulate[diom, <|"Inputs" -> {1 -> Range[-20, 20]}|>]

绘制所有仿真结果：

Wolfram Language code: SystemModelPlot[sim, All]

仿真一个 SystemModelSurrogate：

Wolfram Language code:

surrogate = SystemModelSurrogateTrain[\!\(\*GraphicsBox[«8»]\), <|"Outputs" -> "Inertia2.w", "ParameterValues" -> {"Resistor1.R" -> CenteredInterval[0.5, 0.1]}|>]

Wolfram Language code: sim = SystemModelSimulate[surrogate, <|"ParameterValues" -> {"Resistor1.R" -> 0.45}|>]

绘制仿真结果：

Wolfram Language code: SystemModelPlot[sim, "Inertia2.w"]

仿真时间 (4)

用模型的设置进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image]]

Wolfram Language code: sim["SimulationInterval"]

从时间点 0 到 5 进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], 5]

Wolfram Language code: sim["SimulationInterval"]

设置明确的时间间隔，进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], {2, 10}]

Wolfram Language code: sim["SimulationInterval"]

用 Quantity 指定时间间隔：

Wolfram Language code: sim = SystemModelSimulate[[image], {0, Quantity[2500, "Microseconds"]}]

Wolfram Language code: sim["SimulationInterval"]

变量、参数和输入 (8)

可用 "InitialValues" 来设置变量的初值：

Wolfram Language code: sim = SystemModelSimulate[[image], <|"InitialValues" -> {"y" -> 5}|>]

Wolfram Language code: sim[{"y"}, 0]

可用 "ParameterValues" 设置参数的值：

Wolfram Language code: sim = SystemModelSimulate[[image], <|"ParameterValues" -> {"a" -> 5}|>]

Wolfram Language code: sim[{"a"}]

对把两个输入加在一起的模型进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], {0, 10}, <|"Inputs" -> {"u1" -> Sin, "u2" -> Cos}|>];

绘制输入和输出：

Wolfram Language code: SystemModelPlot[sim, {"u1", "u2", "y"}]

仿真变量 x 取不同初值的情况：

Wolfram Language code: sim = SystemModelSimulate[[image], <|"InitialValues" -> {"x" -> Range[5]}|>];

绘制所有仿真中的变量 x：

Wolfram Language code: SystemModelPlot[sim, {"x"}]

用默认参数仿真模型：

Wolfram Language code: sim1 = SystemModelSimulate[[image], 1];

设置仿真的参数：

Wolfram Language code: sim2 = SystemModelSimulate[[image], 1, <|"ParameterValues" -> {"sineVoltage1.offset" -> 5}|>];

比较不同仿真中的变量：

Wolfram Language code: SystemModelPlot[{sim1, sim2}, {"capacitor1.v"'}]

在电压偏移量上做一个参数扫描：

Wolfram Language code: sim = SystemModelSimulate[[image], 1, <|"ParameterValues" -> {"sineVoltage1.offset" -> Range[5]}|>];

绘制所有仿真的电压：

Wolfram Language code: SystemModelPlot[sim, {"sineVoltage1.v"}]

设置两个参数的范围，对范围中的每个点进行一次仿真：

Wolfram Language code: sims = SystemModelSimulate[[image], 1, <|"ParameterValues" -> {"a" -> {1, 2}, "f" -> {3, 4}}|>];

Wolfram Language code: Map[SystemModelPlot[#, {"y"}, PlotLabel -> {"a", "f"} -> #[{"a", "f"}]]&, sims]

将 TimeSeries 作为输入，对模型进行仿真：

定义时间序列对象：

Wolfram Language code: ts = TimeSeries[{2, 2, 1, 6, 5, 7, 4, 4}, {{0, 1, 2, 5, 7, 7.5, 9, 10}}];

对模型进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], 10, <|"Inputs" -> {"u" -> ts}|>];

绘制输入和输出：

Wolfram Language code: SystemModelPlot[sim, {"u", "y"}]

仿真结果 (6)

仿真模型并绘制变量 x1 和 x2：

Wolfram Language code: sim = SystemModelSimulate[[image]];

Wolfram Language code: SystemModelPlot[sim, {"x1", "x2"}]

对模型进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], 10];

获取变量 x 和 x' 的仿真结果：

Wolfram Language code: {xvar, xvarprime} = sim[{"x", "x"'}, t]

用 Plot 函数绘制变量：

Wolfram Language code: Plot[{xvar, xvarprime}, {t, 0, 10}]

对模型进行仿真并找到变量的最大值：

Wolfram Language code: sim = SystemModelSimulate[[image]];

获取变量 angle1v 的值：

Wolfram Language code: angle1v = sim[{"angle1v"}]//First;

找到角度的最大值：

Wolfram Language code: NMaximize[angle1v[t], t]

运行仿真并绘制结果，一次完成：

Wolfram Language code: SystemModelPlot[[image], {"x1", "x4"}]

指定 SystemModelSimulate 的参数：

Wolfram Language code: SystemModelPlot[[image], {"x1", "x4"}, 5]

只保存选择的变量：

Wolfram Language code: sim = SystemModelSimulate[[image], {"x1", "x2", "x3"}]

只有给定的变量被保存起来：

Wolfram Language code: sim["VariableNames"]

只保存选定的变量，并在给定的仿真区间内进行仿真：

Wolfram Language code: sim = SystemModelSimulate[[image], {"x1", "x2", "x3"}, {2, 5}]

绘制仿真结果：

Wolfram Language code: SystemModelPlot[sim, sim["VariableNames"]]

推广和延伸 (1)

调试消息被收集在消息组 "WSMDebug" 中：

Wolfram Language code: Hold["WSMDebug"] /. $MessageGroups

开始发送初始化调试消息：

Wolfram Language code: On[SystemModelSimulate::dinit]

Wolfram Language code: SystemModelSimulate[[image], {0, 1}]

关闭 "WSMDebug" 调试消息：

Wolfram Language code: Off["WSMDebug"]

选项 (10)

InterpolationOrder (1)

对插值阶数为 1 和 3、有 3 个插值点的情况进行仿真：

Wolfram Language code:

{sim1, sim2} = Table[SystemModelSimulate[[image], 5, Method -> {Automatic, "InterpolationPoints" -> 3}, InterpolationOrder -> intOrder], {intOrder, {1, 3}}];

显示 x 变量：

Wolfram Language code: SystemModelPlot[{sim1, sim2}, {"x"}]

Method (8)

使用固定步长求解器：

Wolfram Language code: sim = SystemModelSimulate[[image], 20, Method -> {"Heun", "StepSize" -> 0.1}]

绘制结果：

Wolfram Language code: SystemModelPlot[sim, {"capacitor1.p.v"}]

使用自适应步长求解器：

Wolfram Language code: sim = SystemModelSimulate[[image], 1220, Method -> {"DASSL", "InterpolationPoints" -> 3000}]

在 ParametricPlot 图中显示结果：

Wolfram Language code:

ParametricPlot[Evaluate[sim[{"x", "y"}, t]], {t, 0, 1220}, ColorFunction -> (ColorData[{"SunsetColors", "Reverse"}][#3]&), PlotPoints -> 400]

对于刚性问题，使用自适应步长求解器：

Wolfram Language code:

{adaptive, fixed} = SystemModelSimulate[[image], 3, <|"ParameterValues" -> {"lambda" -> 45}|>, Method -> #]& /@ {{"DASSL"}, {"Euler", "StepSize" -> 0.01}};

Wolfram Language code:

Plot[Evaluate[#[[1]][{"x", "y"}, t]], {t, 1.6, 1.8}, PlotRange -> {-10, 5}, PlotLabel -> #[[2]]]& /@ {{adaptive, "Adaptive step"}, {fixed, "Fixed step"}}

用太少的插值点进行仿真会给出不精确的曲线：

Wolfram Language code: sim1 = SystemModelSimulate[[image], 5, Method -> {"DASSL", "InterpolationPoints" -> 3}];

Wolfram Language code: SystemModelPlot[sim1, {"x"}]

增加点数给出更好的结果：

Wolfram Language code: sim2 = SystemModelSimulate[[image], 5, Method -> {"DASSL", "InterpolationPoints" -> 100}];

Wolfram Language code: SystemModelPlot[sim2, {"x"}]

固定求解器的缺省步长可能比需要的小：

Wolfram Language code: AbsoluteTiming[sim1 = SystemModelSimulate[[image], 50, Method -> "Heun"]]

使用较大的步长以加快计算速度：

Wolfram Language code: AbsoluteTiming[sim2 = SystemModelSimulate[[image], 50, Method -> {"Heun", "StepSize" -> 0.01}]]

结果没有很大差别：

Wolfram Language code: SystemModelPlot[{sim1, sim2}, {"x"}]

让自适应求解器选择步骤：

Wolfram Language code: SystemModelSimulate[[image], {0, 2}, Method -> {"CVODES", "InterpolationPoints" -> "AllSolverSteps"}]

用 NDSolve 仿真模型：

Wolfram Language code: sim = SystemModelSimulate[[image], 2, Method -> "NDSolve"]

结果为含有仿真结果的 SystemModelSimulationData 对象：

Wolfram Language code: sim[{"x", "x"'}]

将选项传递给 NDSolve：

Wolfram Language code:

sim = SystemModelSimulate[[image], 4, Method -> {"NDSolve", MaxStepSize -> 3, StartingStepSize -> 3, AccuracyGoal -> 0.001, PrecisionGoal -> 0.001}]

由于选项的原因精确度降低：

Wolfram Language code: SystemModelPlot[sim, {"x", "x"'}]

ProgressReporting (1)

用 ProgressReporting 控制进度报告：

Wolfram Language code: SystemModelSimulate[[image], ProgressReporting -> False]

应用 (11)

计算水池系统中的高度过冲：

Wolfram Language code: sim = SystemModelSimulate[[image], 150]

Wolfram Language code: height = sim[{"tank.h"}][[1]];

找出最大峰值：

Wolfram Language code: max = FindMaximum[{height[t], 0 < t < 150}, {t, 20}][[1]]

获取每步输送到水池的量：

Wolfram Language code: step = sim[{"tank.qIn"}, 0][[1]];

计算过冲：

Wolfram Language code: overshoot = (max - step) / step

显示过冲：

Wolfram Language code:

Plot[Evaluate@height[t], {t, 0, 150}, GridLines -> {{}, {height[150]}}, PlotRange -> All, Mesh -> {{height[150]}}, MeshShading -> {Automatic, Red}, MeshFunctions -> {#2&}]

计算水池系统中液面上升的时间：

Wolfram Language code: sim = SystemModelSimulate[[image], 150];

Wolfram Language code: height = sim[{"tank.h"}][[1]];

通过查看高度的稳态值获取上升到 10% 和 90% 时的值：

Wolfram Language code: {p10, p90} = height[150]{0.1, 0.9}

计算信号到达这些值的时间：

Wolfram Language code: {t10, t90} = FindMinimum[{t, height[t] > # && t > 0}, t][[1]]& /@ {p10, p90}

计算上升时间：

Wolfram Language code: t90 - t10

绘制终值曲线，并标出信号达到终值的 10％和 90％的时间：

Wolfram Language code:

Plot[Evaluate@height[t], {t, 0, 100}, GridLines -> {{t10, t90}, {height[150]}}, PlotRange -> All, Mesh -> {{t10, t90}}, MeshShading -> {Automatic, Red, Automatic}]

计算水池系统高度的稳定下来的时间：

Wolfram Language code: sim = SystemModelSimulate[[image], {0, 150}];

Wolfram Language code: height = sim[{"tank.h"}][[1]];

计算终值的 5% 界限值：

Wolfram Language code: {p95, p105} = height[150]{0.95, 1.05}

计算信号位于这些值之间的时间：

Wolfram Language code:

ts = Max[First@FindMaximum[{t, height[t] > p105 && 0 ≤ t ≤ 150}, {t, Cases[Range[0, 150, 5], t_ /; height[t] > p105][[-1]]}], 
	First@FindMaximum[{t, height[t] < p95 && 0 ≤ t ≤ 150}, {t, Cases[Range[0, 150, 5], t_ /; height[t] < p95][[-1]]}]]

绘制界限和稳定下来的时间：

Wolfram Language code:

Plot[Evaluate@height[t], {t, 0, 150}, GridLines -> {{ts}, {p95, p105}}, PlotRange -> All, Mesh -> {{ts}}, MeshShading -> {Automatic, Red}]

交互式改变参数值：

Wolfram Language code:

simf[v_] := simf[v] = SystemModelSimulate[[image], 5, <|"ParameterValues" -> {"conduction.G" -> v}|>][{"Tsensor1.T", "Tsensor2.T"}, t];

Wolfram Language code:

Manipulate[
Plot[Evaluate[simf[v]], {t, 0, 5}, PlotRange -> {0, 100}], {v, 6, 10}, SaveDefinitions -> True, SynchronousUpdating -> False]

对沿轮轴有不同启动惯量的滚动的轮子进行仿真：

Wolfram Language code: sims = SystemModelSimulate[[image], 5, <|"ParameterValues" -> {"wheel1.I_axis" -> Range[0.05, 0.08, 0.004]}|>];

获取车轮的轨迹：

Wolfram Language code: vars = #[{"wheel1.x", "wheel1.y"}, t]& /@ sims;

绘制轨迹：

Wolfram Language code: ParametricPlot[Evaluate@vars, {t, 0, 5}, Frame -> True, Axes -> False]

分析改变弹簧常数时的共振峰值：

Wolfram Language code:

sims = SystemModelSimulate[\!\(\*GraphicsBox[«8»]\), 200, <|"Inputs" -> {"u" -> Function[t, UnitStep[t] - UnitStep[t - 2]]}, "ParameterValues" -> {"spring1.c" -> Range[0.1, 1.5, 0.4]}|>];

根据计算：

Wolfram Language code:

idata = Table[Abs@Fourier@Table[UnitStep[t] - UnitStep[t - 2], {t, 0, 200, 0.25}], {sim, sims}];
odata = Table[Abs@Fourier@Table[Evaluate[sim[{"inertia3.w"}, t][[1]]], {t, 0, 200, 0.25}], {sim, sims}];

显示共振峰值：

Wolfram Language code:

ListLogLinearPlot[odata[[All, 1 ;; 200]] / idata[[All, 1 ;; 200]], Joined -> True, DataRange -> {0, 2Pi}, PlotRange -> {{0.1, 5}, {0, 50}}]

通过与测量数据进行比较来校准模型中的参数：

Wolfram Language code: data = Import["ExampleData/inertiaTestData.dat"];

建立模型拟合的标准函数：

Wolfram Language code: model = \!$\*GraphicsBox[«8»]$;

Wolfram Language code:

criteriaFun[pv : {Verbatim[Rule][_ ? StringQ, _ ? NumericQ]..}, var_ ? StringQ] := 
	Module[{f, tmax = 40}, 
	f = SystemModelSimulate[model, tmax, <|"ParameterValues" -> pv|>][{var}][[1]];
	Norm[Table[data[[i, 2]] - f[data[[i, 1]]], {i, Length[data]}]]^2
	]

用测试数据进行参数拟合：

Wolfram Language code:

fittedpars = FindMinimum[criteriaFun[{"Resistor1.R" -> p, "SpringDamper1.d" -> q}, "Inertia2.w"], {{p, 0.1}, {q, 0.25}}, StepMonitor :> PrintTemporary[{p, q}]]

用拟合参数进行仿真：

Wolfram Language code:

sim = SystemModelSimulate[model, {0, 40}, <|"ParameterValues" -> ({"Resistor1.R" -> p, "SpringDamper1.d" -> q} /. fittedpars[[2]])|>];

同时显示测试数据和校准过的模型：

Wolfram Language code: Show[SystemModelPlot[sim, {"Inertia2.w"}, PlotStyle -> Orange], ListPlot[data]]

筛选 Tinker Forge Weather Station 的采样数据：

Wolfram Language code:

tslux = TemporalData[TimeSeries, {{{Quantity[104.7, "Lux"], Quantity[101.30000000000001, "Lux"], 
    Quantity[194.9, "Lux"], Quantity[200.8, "Lux"], Quantity[169., "Lux"], Quantity[158.3, "Lux"], 
    Quantity[174.3, "Lux"], Quantity[169.60000000000002, " ...   3.6042180438464176`17.309385928427066*^9, 3.6042180439474277`17.30938592843924*^9}}}, 1, 
  {"Discrete", 1}, {"Discrete", 1}, 1, {ValueDimensions -> 1, 
   MetaInformation -> {"Illuminance" -> TemporalData`Self["PathComponent", 1]}}}, True, 10.];

对数据进行时间移位并获取数据的幅值：

Wolfram Language code: ts = TimeSeriesMap[QuantityMagnitude, TimeSeriesShift[tslux, {{0}}]];

用低通滤波器运行时间序列：

Wolfram Language code: filterParameters = {"C1" -> 0.03, "C2" -> 0.115};

Wolfram Language code:

sim = SystemModelSimulate[[image], {0, ts["LastTime"]}, <|"Inputs" -> {"Vi" -> ts}, "ParameterValues" -> filterParameters|>];

Wolfram Language code: SystemModelPlot[sim, {"Vi", "Vo"}]

用声音作为输入对低通滤波器进行仿真：

Wolfram Language code: audioIn = Function[t, (2 + Cos[40t])Sin[2000t]];

用给定声音进行仿真：

Wolfram Language code:

filterParameters = {"C1" -> 0.9, "C2" -> 0.01};
sim = SystemModelSimulate[[image], 2, <|"Inputs" -> {"Vi" -> audioIn}, "ParameterValues" -> filterParameters|>, Method -> {"DASSL", "InterpolationPoints" -> 2 * 44100}]

检索输入和输出的音频：

Wolfram Language code: AudioNormalize /@ sim["Audio", {"Vi", "Vo"}]

仿真牛顿摇篮：

Wolfram Language code: sim = SystemModelSimulate[[image], 20];

从结果中获取轨迹：

Wolfram Language code: traj = Table[sim[{"x" <> ToString[i], "y" <> ToString[i]}, ], {i, 5}];

可视化摇篮：

Wolfram Language code:

Animate[Graphics[Table[{Disk[traj[[i]], 0.5], Line[{{5 - i, 5}, traj[[i]]}]}, {i, 5}] /.  -> t, PlotRange -> {{-5, 9}, {-1, 5}}], {t, 0, 20}, SaveDefinitions -> True, AnimationRunning -> False]

用 WaveletScalogram 可视化仿真数据：

Wolfram Language code: sim = SystemModelSimulate[\!$\*GraphicsBox[«8»]$, {0, 10}];

选取你感兴趣的数据：

Wolfram Language code: data = Table[Evaluate[sim[{"chainLink4.frame_b.r_0[1]"}][[1]][t]], {t, 0, 10, 0.01}];

计算小波转换：

Wolfram Language code: cwd = ContinuousWaveletTransform[data];

绘制小波矢量系数：

Wolfram Language code: WaveletScalogram[cwd]

属性和关系 (3)

SystemModelSimulate 的输出是一个 SystemModelSimulationData 对象：

Wolfram Language code: sim = SystemModelSimulate[[image], 10]

用属性获取变量轨迹：

Wolfram Language code: {x, xp} = sim[{"x", "x"'}]

用 SystemModelSimulateSensitivity 获取对参数的敏感度：

Wolfram Language code: sim = SystemModelSimulateSensitivity[[image], 10, {"sineVoltage1.f"}];

绘制电容上的电压对 "sineVoltage1" 的频率的敏感度：

Wolfram Language code: sim["SensitivityNames"]

Wolfram Language code: SystemModelPlot[sim, {{"capacitor1.v", "sineVoltage1.f"}}]

将 SystemModelParametricSimulate 应用于一个可对不同的值进行计算的函数：

Wolfram Language code: sols = SystemModelParametricSimulate[[image], "capacitor1.v", {"sineVoltage1.f"}]

针对不同的频率参数值计算解：

Wolfram Language code: fns = Table[sols[hz], {hz, 1, 5}]

绘制解随时间变化的情况：

Wolfram Language code: Table[Plot[fn[t], {t, 0, 10}], {fn, fns}]

巧妙范例 (1)

仿真范德波尔模型并用参数化图显示：

Wolfram Language code: sim = SystemModelSimulate[[image], {1.67, 10}, <|"ParameterValues" -> {"lambda" -> Range[0.1, 5, 0.1]}|>];

Wolfram Language code: Show@@(ParametricPlot[Evaluate[#[{"x", "y"}, t]], {t, 1.67, 10}, PlotRange -> All]& /@ sim)

Top

	SystemModel[…]	一般系统模型
	StateSpaceModel[…]	状态-空间模型
	TransferFunctionModel[…]	传递函数模型
	AffineStateSpaceModel[…]	仿射状态-空间模型
	NonlinearStateSpaceModel[…]	非线性状态-空间模型
	DiscreteInputOutputModel[…]	离散输入-输出模型
	SystemModelSurrogate[…]	替代模型

	Automatic	自动选择要保存的变量
	{v₁,v₂,…}	只保存变量 v_i
	All	保存所有变量

"ParameterValues"	{p₁val₁,…}	参数 p_i 取值 val_i
"InitialValues"	{v₁val₁,…}	变量 v_i 取初值 val_i
"Inputs"	{in₁fun₁,…}	输入 in_i 在时间点 t 取值 fun_i[t]

	"InterpolationPoints"	Automatic	插值点的数目
	"Tolerance"	10^-6	自适应步长的容差

	"Euler"	明确的 1 阶欧拉方法
	"Heun"	2 阶 Heun 方法
	"RungeKutta"	明确的 1 阶 Runge–Kutta 方法

更多学习资源

技术支持

数据科学、金融与商业

工程

科学与技术

教育科技

教育举措

开始

提高你的技能

与我们合作

成人教育计划

青少年教育计划

欢迎阅读

SystemModelSimulate

更多信息和选项

范例

基本范例 (3)

范围 (24)

模型 (6)

仿真时间 (4)

变量、参数和输入 (8)

仿真结果 (6)

推广和延伸 (1)

选项 (10)

InterpolationOrder (1)

Method (8)

ProgressReporting (1)

应用 (11)

属性和关系 (3)

巧妙范例 (1)

文本

CMS

APA

BibTeX

BibLaTeX

	"DASSL"	DASSL DAE 求解器
	"CVODES"	CVODES ODE 求解器

SystemModelSimulate

更多信息和选项

范例

基本范例 (3)

范围 (24)

模型 (6)

仿真时间 (4)

变量、参数和输入 (8)

仿真结果 (6)

推广和延伸 (1)

选项 (10)

InterpolationOrder (1)

Method (8)

ProgressReporting (1)

应用 (11)

属性和关系 (3)

巧妙范例 (1)

参见

技术笔记

相关指南

相关链接

历史

文本

CMS

APA

BibTeX

BibLaTeX