摘 要
机械电子系统在现代工业中扮演着至关重要的角色，其复杂性和非线性特性给控制策略带来了巨大挑战。为提高系统的动态性能和稳定性，本研究聚焦于机械电子系统中的非线性控制策略，旨在探索适用于复杂工况的先进控制方法。通过引入自适应神经网络与滑模控制相结合的技术，提出了一种新型复合控制算法，该算法能够有效应对系统参数不确定性和外部扰动问题。基于Lyapunov稳定性理论，建立了严格的数学模型，并通过仿真验证了所提算法的有效性。实验结果表明，相较于传统PID控制，新算法在响应速度、稳态精度及抗干扰能力方面均有显著提升。特别是在高速运转和高精度定位场景下，系统表现出更优的动态特性和鲁棒性。本研究不仅丰富了非线性控制理论体系，还为实际工程应用提供了可靠的解决方案，具有重要的理论意义和实用价值。通过对多种典型机械电子系统的测试，进一步证明了该控制策略的普适性和优越性，为相关领域的技术创新和发展奠定了坚实基础。
关键词：非线性控制 自适应神经网络 滑模控制
Abstract
Mechanical electronic systems play a crucial role in modern industry, and their complexity and nonlinear characteristics pose significant challenges to control strategies. To enhance the dynamic performance and stability of these systems, this study focuses on nonlinear control strategies for mechanical electronic systems, aiming to explore advanced control methods suitable for complex operating conditions. By integrating adaptive neural networks with sliding mode control, a novel composite control algorithm is proposed, which effectively addresses issues related to system parameter uncertainties and external disturbances. Based on Lyapunov stability theory, a rigorous mathematical model has been established, and simulations have validated the effectiveness of the proposed algorithm. Experimental results demonstrate that compared to traditional PID control, the new algorithm significantly improves response speed, steady-state accuracy, and disturbance rejection capability. Particularly in high-speed operation and high-precision positioning scenarios, the system exhibits superior dynamic characteristics and robustness. This research not only enriches the theoretical fr amework of nonlinear control but also provides a reliable solution for practical engineering applications, holding important theoretical significance and practical value. Through testing on various typical mechanical electronic systems, the versatility and superiority of this control strategy have been further confirmed, laying a solid foundation for technological innovation and development in relevant fields.
Keyword:Nonlinear Control Adaptive Neural Network Sliding Mode Control
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3本文研究方法 1
2非线性系统建模分析 2
2.1机械电子系统特性 2
2.2建模理论基础 3
2.3模型验证与评估 3
3控制策略设计与优化 4
3.1常见非线性控制方法 4
3.2控制器参数整定 5
3.3系统稳定性分析 5
4实验验证与结果分析 6
4.1实验平台搭建 6
4.2性能测试与评价 7
4.3结果讨论与改进 7
结论 8
参考文献 9
致谢 10
