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Add new notebook to TOC
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TOC.ipynb

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"* [Discrete control](2_Control/6_Discrete_control_and_analysis/Discrete%20control.ipynb)\n",
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"* [Discrete PI](2_Control/6_Discrete_control_and_analysis/Discrete%20PI.ipynb)\n",
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"* [Dahlin controller](2_Control/6_Discrete_control_and_analysis/Dahlin%20controller.ipynb)\n",
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"* [Simple discrete controller simulation](2_Control/6_Discrete_control_and_analysis/Simple%20discrete%20controller%20simulation.ipynb)\n",
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"* [Noise models](2_Control/6_Discrete_control_and_analysis/Noise%20models.ipynb)"
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]
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},
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"* [Interactive PID simulation](tclab/TCLab%20PID.ipynb)\n",
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"* [Frequency domain](tclab/Frequency%20domain.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# tbcontrol\n",
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"The tbcontrol module contains functions helpful to students learning to solve control problems. It is broken up into submodules."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## symbolic\n",
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"* `linearise` attempt to linearise a symbolic expression\n",
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"* `routh` construct a Routh-Hurwitz array\n",
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"* `pade` pade approximation\n",
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"* `ss2tf` determine the transfer function version of a state space realisation\n",
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"* `sampledvalues` invert the Z transform symbolically\n",
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"* `evaluate_at_times` evaluate a sympy expression at numeric times (useful for plotting responses)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## numeric\n",
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"* `skogestad_half` find an approximation of a high order system by Skogestad's half rule"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## plotting\n",
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"* `cross_axis` create an axis in Matplotlib which has spines going through the origin like a Nyquist diagram would"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## loops\n",
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"* `feedback` calculate the result of having two blocks in a feedback loop"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## responses\n",
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"Step responses of certain systems\n",
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"\n",
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"* `fopdt` first order plus dead time\n",
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"* `sopdt` second order plus dead time"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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"version": "3.7.6"
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}
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},
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"nbformat": 4,

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