Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China.
School of Computer Science, Faculty of Science and Engineering, University of Hull, Hull, United Kingdom.
PLoS One. 2024 Mar 22;19(3):e0300305. doi: 10.1371/journal.pone.0300305. eCollection 2024.
This article introduces a cutting-edge H∞ model-based control method for uncertain Multi Input Multi Output (MIMO) systems, specifically focusing on UAVs, through a flexible mixed-optimization framework using the Method of Inequality (MOI). The proposed approach adaptively addresses crucial challenges such as unmodeled dynamics, noise interference, and parameter variations. Central to the design is a two-step controller development process. The first step involves Nonlinear Dynamic Inversion (NDI) and system decoupling for simplification, while the second step integrates H∞ control with MOI for optimal response tuning. This strategy is distinguished by its adaptability and focus on balancing robust stability and performance, effectively managing the intricate cross-coupling dynamics in UAV systems. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB/Simulink environment. Results demonstrated the efficiency of the proposed robust control approach as evidenced by reduced steady-state error, diminished overshoot, and faster system response times, thus significantly outperforming traditional control methods.
本文提出了一种基于 H∞模型的控制方法，用于不确定的多输入多输出（MIMO）系统，特别是针对无人机，通过使用不等式方法（MOI）的灵活混合优化框架。该方法自适应地解决了关键挑战，如未建模动态、噪声干扰和参数变化。设计的核心是两步控制器开发过程。第一步涉及非线性动态反转（NDI）和系统解耦以简化，第二步将 H∞控制与 MOI 集成以进行最佳响应调整。该策略的特点是适应性强，注重平衡鲁棒稳定性和性能，有效地管理无人机系统中复杂的交叉耦合动态。通过在 MATLAB/Simulink 环境中进行的仿真验证了所提出方法的有效性。结果表明，所提出的鲁棒控制方法效率高，稳态误差减小，超调量减小，系统响应时间更快，因此明显优于传统控制方法。
