Hao J, Vandewalle J, Tan S
ESAT Laboratory, Department of Electrical Engineering, Katholieke Universiteit Leuven, Heverlee, Belgium.
Int J Neural Syst. 1993 Mar;4(1):55-64. doi: 10.1142/s0129065793000079.
This paper tries to demonstrate how a heuristic neural control approach can be used to solve a complex nonlinear control problem. The control task is to swing up a pendulum mounted on a cart from its stable position (vertically down) to the zero state (up right) and keep it there by applying a sequence of two opposing constant forces of equal magnitude to the mass center of the cart. In addition, the displacement of the cart itself is confined to within a preset limit during the swinging up action and it will eventually be brought to the origin of the track. This is truly a nontrivial nonlinear regulation problem and is considerably difficult compared to the pendulum balancing problem (and its variations) widely adopted as a benchmarking test system for neural controllers. Through the solution of this specific control problem, we try to illustrate a heuristic neural control approach with task decomposition, control rule extraction and neural net rule implementation as its basic elements. Specializing to the pendulum problem, the global control task is decomposed into subtasks namely pendulum positioning and cart positioning. Accordingly, three separate neural subcontrollers are designed to cater to the subtasks and their coordination, i.e., pendulum subcontroller (PSC), cart subcontroller (CSC) and the switching subcontroller (SSC). Each of the subcontrollers is designed based on the rules and guidelines obtained from the experiences of a human operator. The simulation result is included to show the actual performance of the controller.
本文试图演示如何使用启发式神经控制方法来解决复杂的非线性控制问题。控制任务是将安装在小车上的摆锤从其稳定位置（垂直向下）摆动到零状态（直立向上），并通过对小车质心施加一系列两个大小相等、方向相反的恒定力将其保持在该位置。此外，在摆动过程中，小车本身的位移被限制在预设范围内，最终将被带到轨道原点。这确实是一个不平凡的非线性调节问题，与广泛用作神经控制器基准测试系统的摆锤平衡问题（及其变体）相比，难度要大得多。通过解决这个特定的控制问题，我们试图说明一种以任务分解、控制规则提取和神经网络规则实现为基本要素的启发式神经控制方法。针对摆锤问题，将全局控制任务分解为摆锤定位和小车定位等子任务。相应地，设计了三个独立的神经子控制器来处理这些子任务及其协调，即摆锤子控制器（PSC）、小车子控制器（CSC）和切换子控制器（SSC）。每个子控制器都是根据从人类操作员经验中获得的规则和指导方针设计的。文中包含了仿真结果以展示控制器的实际性能。
