scholarly journals A new approach to decentralized control design for nonlinear multi-unit plants

Author(s):  
Peter L. Lee ◽  
Huaizhong Li ◽  
Ian T. Cameron
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.


2015 ◽  
Vol 44 (3) ◽  
pp. 247-253
Author(s):  
Branislav Rehak

A control design for a large-scale system using LMI optimization is proposed. The control is designed in a way such that the LQ cost in the case of the decentralized control  does not exceed a certain limit. The optimized quantity are the values of the control gain matrices. The methodology is useful even for finding a decomposition of the system, however, some expert knowledge is necessary in this case. The capabilities of the algorithm are illustrated by two examples.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.6464


Automatica ◽  
2005 ◽  
Vol 41 (12) ◽  
pp. 2033-2041 ◽  
Author(s):  
Knut Graichen ◽  
Veit Hagenmeyer ◽  
Michael Zeitz

2008 ◽  
Vol 7 (2) ◽  
pp. 177-181 ◽  
Author(s):  
Yiguang Hong ◽  
Guowu Yang ◽  
Daizhan Cheng ◽  
Sarah Spurgeon

Author(s):  
Ye-Hwa Chen

A new approach to the control design for fuzzy dynamical systems is proposed. For a fuzzy dynamical system, the uncertainty lies within a fuzzy set. The desirable system performance is twofold: one deterministic and one fuzzy. While the deterministic performance assures the bottom line, the fuzzy performance enhances the cost consideration. Under this setting, a class of robust controls is proposed. The control is deterministic and is not if-then rules-based. An optimal design problem associated with the control is then formulated as a constrained optimization problem. We show that the problem can be solved and the solution exists and is unique. The closed-form solution and cost are explicitly shown. The resulting control is able to guarantee the prescribed deterministic performance and minimize the average fuzzy performance.


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