scholarly journals A New Approach to the Robust Control Design of Fuzzy Automated Highway Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qingmin Huang ◽  
Zeyu Yang ◽  
Jin Huang ◽  
Hui Yin

In this paper, a new approach to the decentralized control design for vehicle platooning for uncertain automated highway systems is proposed. The uncertainty in the system, which is nonlinear and (possibly) fast time-varying, is bounded. The bound is assumed to be within a prescribed fuzzy set. A creative transformation is made to the system, which converts a local problem to a global problem. Based on the fuzzy description of the uncertainty bound and the transformation, a class of decentralized control is proposed in which each vehicle only needs the knowledge of its preceding vehicle in the platoon. No acceleration feedback or the information of the leading vehicle is required. Both the vehicle platooning system and the control are deterministic, hence not if-then fuzzy rule-based. The performance of the resulting controlled system is twofold. First, the collision avoidance performance is guaranteed under any safe initial conditions regardless of the value of the uncertainty. Second, the minimization of a fuzzy-based performance index is guaranteed based on an optimal choice of a control design parameter. Numerical simulations are conducted to validate the efficiency of the proposed algorithm.

2002 ◽  
Vol 10 (2) ◽  
pp. 97-111
Author(s):  
Paolo Arena ◽  
Holk Cruse ◽  
Mattia Frasca

This article introduces a new approach to locomotion control in six-legged robots. The approach is inspired by the model of decentralized locomotion control in the stick insect introduced by one of the authors and makes use of second-order nonlinear systems to realize the neuron-like dynamics of the sub-units of the whole control system. Each of these sub-units controls the behavior of a leg and is coordinated with the others by means of local influences based on the leg status, revealed by contact sensors. The suitability of the approach has been shown by using cellular nonlinear networks (CNNs) to implement the leg controllers. Simulations of the CNN-based locomotion control demonstrate its robustness with respect to different initial conditions and the property of pattern recovery after the external blocking of a leg.


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