Designing Linear Control Systems with MATLAB
Written as a companion volume to the author's Solving Control Engineering Problems with MATLAB, this indispensable guide illustrates the power of MATLAB as a tool for synthesizing control systems, emphasizing pole placement, and optimal systems design.
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POLE PLACEMENT AND DESIGN
POLE PLACEMENT AND DESIGN OF
DESIGN OF OPTIMAL CONTROL SYSTEMS
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Ackermann's formula approach arbitrary assume becomes chapter closed-loop poles command computed condition Consider constant control signal control system controllability matrix convert curve Define derive designed system determined discrete-time discuss eigenvalues Enter matrices error example feedback gain matrix Figure following command format given by Eq gives grid Gx(k Hence Hu(k initial input integrator inverted pendulum linear MATLAB Program matrix K measured minimizes minimum-order observer Note Notice observer gain matrix obtain origin output performance index plant plot pole placement poly positive possible present problem pseudoinverse quadratic optimal control rank Referring to Eq result Riccati equation sampling periods scalar servo system shown in Figure shows solution solve stable state-space equations statement steady-state step substituting symmetric matrix transfer function transformation unit-step response values variables vector versus zero
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