This paper proposes an adaptive funnel control (FC) scheme for servo mechanisms with an unknown dead-zone. To improve the transient and steady-state performance, a modified funnel variable, which relaxes the limitation of the original FC (e.g., systems with relative degree 1 or 2), is developed using the tracking error to replace the scaling factor. Then, by applying the error transformation method, the original error is transformed into a new error variable which is used in the controller design. By using an improved funnel function in a dynamic surface control procedure, an adaptive funnel controller is proposed to guarantee that the output error remains within a predefined funnel boundary. A novel command filter technique is introduced by using the Levant differentiator to eliminate the “explosion of complexity” problem in the conventional backstepping procedure. Neural networks are used to approximate the unknown dead-zone and unknown nonlinear functions. Comparative experiments on a turntable servo mechanism confirm the effectiveness of the devised control method.

中文翻译：

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具有未知死区的伺服机构的基于神经网络的自适应漏斗控制

本文提出了一种具有未知死区的伺服机构的自适应漏斗控制（FC）方案。为了提高瞬态和稳态性能，使用跟踪误差代替比例因子，开发了修改后的漏斗变量，该变量可以放松原始FC（例如，相对度为1或2的系统）的限制。然后，通过应用错误转换方法，将原始错误转换为新的错误变量，该变量将在控制器设计中使用。通过在动态表面控制过程中使用改进的漏斗功能，提出了一种自适应漏斗控制器，以确保输出误差保持在预定义的漏斗边界内。通过使用黎凡特微分器引入了一种新颖的命令过滤器技术，以消除常规反推过程中的“复杂性爆炸”问题。使用神经网络来近似未知的死区和未知的非线性函数。转盘伺服机构的比较实验证实了所设计的控制方法的有效性。