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Control System Design

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Introduction

 

Maple has tools for linear control system design in the DynamicSystems package. You can

 

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Work with transfer functions, state space models, or differential equations

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Linearize systems

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Analyze the controllability, observability, phase and gain margin, and more

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Generate control plots, including Bode, root-locus and Nyquist plots

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Work symbolically or numerically


In this example, we will calculate the controllability matrix of a model of a DC motor, and generate a root-locus plot.

DC Motor System

 

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restart: withDynamicSystems:

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eq_sym≔L⋅i.t+R⋅it=vt−K⋅θ.t,J⋅θ..t+b⋅θ.t+Ks⋅θt=K⋅it :

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params≔J=0.1, b=0.1, K=0.01, R=1, L=0.5, Ks = 1:

 

Controllability Matrix and Root-Locus Plot

 

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eq_num≔evaleq_sym,params:

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sys_num ≔ StateSpaceeq_num, inputvariable=vt, outputvariable=thetat,it:

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ControllabilityMatrixsys_num

2−419992500015015−35

(1)
> 

RootLocusPlotsys_num

Symbolic Controllability Matrix

 

You can also work symbolically, and maintain the parameter relationships present in the original equation system. Here, for example, we generate a symbolic controllability matrix.

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sys_sym ≔ StateSpaceeq_sym, inputvariable=vt, outputvariable=thetat,it:

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ControllabilityMatrixsys_sym

1L−RL2R2L3−K2L2⁢J00KJ⁢L0KJ⁢L−K⁢RJ⁢L2−b⁢KJ2⁢L

(2)
> 

Applications

Robot Arm Code Generation

LQR Controller for Inverted Pendulum