用约束粒子群优化法调优模糊PID，让水下车辆更稳更快地控深。
Constrained PSO Six-Parameter Fuzzy PID Tuning Method for Balanced Optimization of Depth Tracking Performance in Underwater Vehicles
- 用六参数联合优化方法，同步调整模糊PID的基准参数与增益因子。
- 控制能耗不变的前提下，超调量降为0.01839，响应时间缩短至1.613秒。
- 适合需要精准控深且受执行器限制的水下航行器控制系统设计。
工程应用中，水下车辆的深度控制需兼顾快速跟踪、小超调和执行器约束。传统模糊PID调参多依赖经验，难以在性能提升与控制代价间达成稳定可复现的平衡。本文提出一种约束粒子群优化（Constrained PSO）方法，用于六参数模糊PID控制器的调参。通过同时调整基准PID参数、模糊输入量化因子与输出比例增益，实现模糊PID系统整体调节强度与动态响应特性的协同优化。为确保工程可行性，引入时加权绝对误差积分、调节时间、相对超调、控制能量与饱和占用率作为综合评价指标，并施加控制能量约束，抑制仅靠增大控制输入带来的虚假性能提升。仿真结果表明，在保持控制能量（7980→7935）与饱和水平（0.004→0.003）基本不变的情况下，时加权绝对误差积分由0.2631降至0.1473，调节时间从2.301秒缩短至1.613秒，相对超调从0.1494降至0.01839。验证了该约束式六参数联合调参策略在水下航行器深度控制中的有效性与工程价值。
原文摘要 · Abstract (English)
Depth control of underwater vehicles in engineering applications must simultaneously satisfy requirements for rapid tracking, low overshoot, and actuator constraints. Traditional fuzzy PID tuning often relies on empirical methods, making it difficult to achieve a stable and reproducible equilibrium solution between performance enhancement and control cost. This paper proposes a constrained particle swarm optimization (PSO) method for tuning six-parameter fuzzy PID controllers. By adjusting the benchmark PID parameters alongside the fuzzy controller's input quantization factor and output proportional gain, it achieves synergistic optimization of the overall tuning strength and dynamic response characteristics of the fuzzy PID system. To ensure engineering feasibility of the optimization results, a time-weighted absolute error integral, adjustment time, relative overshoot control energy, and saturation occupancy rate are introduced. Control energy constraints are applied to construct a constraint-driven comprehensive evaluation system, suppressing pseudo-improvements achieved solely by increasing control inputs. Simulation results demonstrate that, while maintaining consistent control energy and saturation levels, the proposed method significantly enhances deep tracking performance: the time-weighted absolute error integral decreases from 0.2631 to 0.1473, the settling time shortens from 2.301 s to 1.613 s, and the relative overshoot reduces from 0.1494 to 0.01839. Control energy varied from 7980 to 7935, satisfying the energy constraint, while saturation occupancy decreased from 0.004 to 0.003. These results validate the effectiveness and engineering significance of the proposed constrained six-parameter joint tuning strategy for depth control in underwater vehicle navigation scenarios.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。