基于小脑模型关节控制器与PID复合的高速公路交通流密度控制

高速公路交通控制系统是一个复杂的非线性时变系统, 传统的匝道控制方法难以取得满意的控制效果. 为此, 本文提出基于小脑模型关节控制器(CMAC)与PID复合的匝道控制方法. 首先建立了二阶宏观动态交通流模型, 然后研究了CMAC与PID复合控制算法, 结合非线性反馈理论, 设计了基于CMAC与PID复合的高速公路交通流密度控制器, 该密度控制问题是一个输出跟踪和扰动抑制问题, 最后采用两个仿真实例对该方法的有效性进行验证. 结果表明, 复合控制具有优越的密度跟踪性能和抑制噪声干扰的能力; 复合控制方法能够有效地消除交通拥挤, 并使主线车流趋于稳定.

Density control for freeway traffic flow based on the composite of PID controller and cerebella model articulation controller

Freeway traffic control system is a complex nonlinear and time-varying system; for which the results of conventional ramp control methods are not satisfactory. A new method based on the composite of PID controller and cerebella model articulation controller (CMAC) is proposed for ramp control in this paper. First, a second-order macroscopic dynamic traffic flow model is built; and then, the algorithm of the composite control of CMAC and PID is studied. In conjunction with nonlinear feedback theory, a density controller of freeway traffic flow based on the composite of CMAC and PID is designed, and the density control problem is formulated as an output tracking and disturbance rejection problem. Finally, the effectiveness of this new approach is validated by intensive simulations in two different cases. The results show that the composite controller has excellent tracking performance and noise rejection ability, effectively eliminating traffic congestions and stabilizing the traffic flow on freeway mainlines.