Computer-Controlled Systems: Theory and Design, Third EditionCourier Corporation, 2011年1月1日 - 557 頁 Practically all modern control systems are based upon microprocessors and complex microcontrollers that yield high performance and functionality. This volume focuses on the design of computer-controlled systems, featuring computational tools that can be applied directly and are explained with simple paper-and-pencil calculations. The use of computational tools is balanced by a strong emphasis on control system principles and ideas. Extensive pedagogical aids include worked examples, MATLAB macros, and a solutions manual (see inside for details). The initial chapter presents a broad outline of computer-controlled systems, followed by a computer-oriented view based on the behavior of the system at sampling instants. An introduction to the design of control systems leads to a process-related view and coverage of methods of translating analog designs to digital control. Concluding chapters explore implementation issues and advanced design methods. |
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algorithm analog antialiasing filter approximation Assume calculations characteristic polynomial closed-loop poles closed-loop system command signals computer-controlled systems Consider the system continuous-time system control law control signal control system D-A converter delay described Determine difference equation Diophantine equation discrete-time system discussed in Sec double integrator dynamic system eigenvalues error estimate factors feedback feedforward Figure first-order hold follows given gives implemented input signal input-output inside the unit introduce Kalman filter load disturbances loop loss function matrix measurement noise method minimum-variance control Nyquist frequency obtained operator optimal oscillation output parameters pole-placement prediction pulse pulse-transfer function quantization r₁ rad/s reachable response sampled system sampling instants sampling interval sampling period shown in Fig shows simulation solution spectral density stable state-space steady-state stochastic process Theorem theory transfer function transform Tu(k u(kh unit disc values variables variance white noise x(kh z-transform zero-order hold