Course Design for Automatic Control Principles

The course design for Automatic Control Principles typically covers fundamental control system analysis methods and design procedures, including root locus analysis, time-domain analysis, frequency-domain analysis, and system compensation design. Leveraging MATLAB's powerful computational and simulation capabilities, students can visually verify theoretical analysis results and optimize control system performance through practical code implementation.

Root Locus Analysis By plotting the root locus diagram using MATLAB's `rlocus` function, students can visually observe how closed-loop poles vary with parameter changes, thereby analyzing system stability and dynamic performance. The root locus design approach helps determine appropriate gain values or compensation network parameters to ensure system stability requirements are met. Implementation typically involves defining transfer functions using `tf` or `zpk` commands and analyzing stability margins with `margin`.

Time-Domain Analysis Time-domain analysis focuses on evaluating system transient and steady-state response characteristics such as overshoot, settling time, and steady-state error. Through step response (`step` function) or impulse response (`impulse` function) simulations in MATLAB, students can assess dynamic performance and adjust controller parameters accordingly. Key metrics can be extracted using functions like `stepinfo` for quantitative performance evaluation.

Frequency-Domain Analysis Frequency-domain analysis employs Bode plots (`bode` function), Nyquist plots (`nyquist` function), or Nichols charts to examine system frequency response characteristics, evaluating stability margins, bandwidth, and disturbance rejection capabilities. Frequency-domain methods are particularly important for system compensation, suitable for phase-lead, phase-lag, or PID controller design. MATLAB's Control System Toolbox provides comprehensive functions for frequency response analysis and stability assessment.

Control System Design and Compensation Based on system performance specifications, appropriate compensation networks (such as lead compensation, lag compensation, or PID controllers) are designed to optimize both dynamic and steady-state performance. MATLAB offers robust toolboxes (like Control System Toolbox) that facilitate parameter tuning through functions like `pidtune` and simulation verification through `simulink` modeling. The design process often involves iterative optimization using `sisotool` for interactive compensation design.

The ultimate objective of the course design is to integrate theoretical analysis with simulation practice, mastering control system design workflows and enhancing problem-solving capabilities for real-world engineering challenges through hands-on MATLAB programming and simulation exercises.