Multi-objective control optimization for semi-active vehicle suspensions

2011 ◽  
Vol 330 (23) ◽  
pp. 5502-5516 ◽  
Author(s):  
John H. Crews ◽  
Michael G. Mattson ◽  
Gregory D. Buckner
2020 ◽  
Vol 93 (1-4) ◽  
pp. 39-44
Author(s):  
Sławomir Grzyb ◽  
Przemysław Orłowski

Effective congestion control is an issue strongly impacting basic features demanded from modern network environment as reliability, high and stable throughput, and low delays. These characteristics define the quality of communication channels. Optimizing network nodes configuration for only one of mentioned features, can exacerbate other parameters. This paper focuses on avoiding and alleviating network congestions using multi-objective optimization for gain setting of used controllers. Unlike in other presented approaches, in this case the non-stationary, discrete, dynamical model is discussed. The significant advantage of this approach is in the better reflection of the real environment conditions, where the transmission delay is floating. As the further development of the control strategy, the controller with the memory of previous steps have been deployed. Such control strategy mitigates the unfavorable impact of extended delays. Both proposed control strategies tune the presented model of communication channel to alleviate the results of sudden, unexpected network state changes. It is obtained by maximization of available bandwidth usage combined with minimization of buffer utilization. This supports avoiding undesirable congestion effects like packet dropping, retransmissions, high delay, and low network throughput.


Sensors ◽  
2011 ◽  
Vol 11 (6) ◽  
pp. 5792-5807 ◽  
Author(s):  
Haigen Hu ◽  
Lihong Xu ◽  
Ruihua Wei ◽  
Bingkun Zhu

2020 ◽  
Vol 53 (2) ◽  
pp. 7927-7932
Author(s):  
Gilberto Reynoso-Meza ◽  
Jesús Carrillo-Ahumada ◽  
Victor Henrique Alves Ribeiro ◽  
Tyene Zoraski Zanella

2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.


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