Control System Design
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Introduction
Maple has tools for linear control system design in the DynamicSystems package. You can
Work with transfer functions, state space models, or differential equations
Linearize systems
Analyze the controllability, observability, phase and gain margin, and more
Generate control plots, including Bode, root-locus and Nyquist plots
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
restart: withDynamicSystems:
eq_sym≔L⋅i.t+R⋅it=vt−K⋅θ.t,J⋅θ..t+b⋅θ.t+Ks⋅θt=K⋅it :
params≔J=0.1, b=0.1, K=0.01, R=1, L=0.5, Ks = 1:
Controllability Matrix and Root-Locus Plot
eq_num≔evaleq_sym,params:
sys_num ≔ StateSpaceeq_num, inputvariable=vt, outputvariable=thetat,it:
ControllabilityMatrixsys_num
2−419992500015015−35
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.
sys_sym ≔ StateSpaceeq_sym, inputvariable=vt, outputvariable=thetat,it:
ControllabilityMatrixsys_sym
1L−RL2R2L3−K2L2⁢J00KJ⁢L0KJ⁢L−K⁢RJ⁢L2−b⁢KJ2⁢L
Applications
Robot Arm Code Generation
LQR Controller for Inverted Pendulum
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