Hierarchical rule-base reduction (HRBR) was used to create a new form of waypoint navigation control for a skid-steer vehicle, which consists of a multiple input-single output nonlinear fuzzy angular velocity controller. HRBR enabled an increase in system complexity by only selecting the rules most influential on state errors. The membership functions of the fuzzy controller employed a trapezoidal structure with a completely symmetric rule-base. The work was motivated by a desire to find the limitations of fuzzy control in terms of accuracy and robustness across environments. To accomplish this, an examination of the proposed controller is completed by employing test courses. The test courses examine the effects of steering disturbance, phase lag, and overshoot. The controller's performance was compared with existing waypoint navigation controllers, pure pursuit, and the Huskić Buck Zell (HBZ) controller. After initial controller development/tuning was completed in the simulation, the controllers were tested outdoors. The HRBR fuzzy was found to outperform the pure pursuit and HBZ in simulation (36.74% and 80.56% improvement in Root Mean Square Error (RMSE) on one course) and on concrete with mixed results on a surface with different dynamics, namely grass (23.13% and 55.64% improvement in RMSE averaging the two on the same course). If a moderate amount of tuning of the fuzzy controller had not been performed in simulation, failure across different environments would be more likely. The present study is important as it illustrates the potential effectiveness of the HRBR for control applications beyond waypoint navigation.

中文翻译：

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差动转向车辆等速路径跟踪的分层规则库简化模糊控制

分层规则库缩减（HRBR）用于为滑移转向车辆创建一种新形式的路点导航控制，该控制由多输入单输出非线性模糊角速度控制器组成。 HRBR 通过仅选择对状态错误影响最大的规则来增加系统复杂性。模糊控制器的隶属函数采用梯形结构，规则库完全对称。这项工作的动机是希望找到模糊控制在跨环境的准确性和鲁棒性方面的局限性。为了实现这一点，通过使用测试课程来完成对所提议的控制器的检查。测试课程检查转向干扰、相位滞后和超调的影响。该控制器的性能与现有的航路点导航控制器、纯粹追踪控制器和 Huskić Buck Zell (HBZ) 控制器进行了比较。在模拟中完成初始控制器开发/调整后，控制器在室外进行测试。研究发现，HRBR 模糊在模拟中优于纯追踪和 HBZ（在一个过程中，均方根误差 (RMSE) 分别提高了 36.74% 和 80.56%），并且在具有不同动态的表面（即草地）上具有混合结果的混凝土上（23.13 % 和 55.64% 的 RMSE 改善（同一课程中两者的平均值）。如果在仿真中没有对模糊控制器进行适度的调整，则更有可能在不同环境下出现故障。本研究很重要，因为它说明了 HRBR 对于航路点导航之外的控制应用的潜在有效性。