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.

翻译：工程应用中水下航行器的深度控制需同时满足快速跟踪、低超调及执行机构约束等要求。传统模糊PID整定多依赖经验方法，难以在性能提升与控制代价间获得稳定可复现的均衡解。本文提出一种用于六参数模糊PID控制器整定的约束粒子群优化方法，通过同时调整基准PID参数与模糊控制器输入量化因子、输出比例增益，实现模糊PID系统整体整定强度与动态响应特性的协同优化。为确保优化结果的工程可行性，引入时间加权绝对误差积分、调节时间、相对超调量、控制能量及饱和占用率，施加控制能量约束构建约束驱动的综合评价体系，抑制仅通过增大控制输入实现的伪改善。仿真结果表明，在保持控制能量与饱和水平一致的条件下，所提方法显著提升了深度跟踪性能：时间加权绝对误差积分从0.2631降至0.1473，调节时间从2.301 s缩短至1.613 s，相对超调量从0.1494减小至0.01839；控制能量在7980至7935间变化，满足能量约束，饱和占用率从0.004降至0.003。该结果验证了所提约束六参数联合整定策略在水下航行器导航场景深度控制中的有效性与工程意义。