Intersections are the bottlenecks of the urban road system because an intersection's capacity is only a fraction of the maximum flows that the roads connecting to the intersection can carry. This capacity can be increased if vehicles cross the intersections in platoons rather than one by one as they do today. Platoon formation is enabled by connected vehicle technology. This paper assesses the potential mobility benefits of platooning. It argues that saturation flow rates, and hence intersection capacity, can be doubled or tripled by platooning. The argument is supported by the analysis of three queuing models and by the simulation of a road network with 16 intersections and 73 links. The queuing analysis and the simulations reveal that a signalized network with fixed time control will support an increase in demand by a factor of (say) two or three if all saturation flows are increased by the same factor, with no change in the control. Furthermore, despite the increased demand vehicles will experience the same delay and travel time. The same scaling improvement is achieved when the fixed time control is replaced by the max pressure adaptive control. Part of the capacity increase can alternatively be used to reduce queue lengths and the associated queuing delay by decreasing the cycle time. Impediments to the control of connected vehicles to achieve platooning at intersections appear to be small.

This paper deals with the disturbance rejection problem for discrete-time linear systems having time-varying state delays and control constraints. The study proposes a novel receding horizon H∞ control method utilizing a linear matrix inequality based optimization algorithm which is solved in each step of run-time. The proposed controller attenuates disturbances having bounded energies on controlled output and ensures the closed-loop stability and dissipation while meeting the physical control input constraints. The originality of the work lies on the extension of the idea of the well-known H∞ receding horizon control technique developed for linear discrete-time systems to interval time-delay systems having time-varying delays. The efficiency of the proposed method is illustrated through simulation studies that are carried out on a couple of benchmark problems.

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In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC) is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI) based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.

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Bu çalışmada, ürünlerin dayanım ve performanslarının belirlenmesi için kullanılan hidrolik test sistemlerinin kontrolü için Model Öngörülü Kontrol (Model Predictive Control-MPC) tasarımı yapılmıştır Sistem kısıtlarının optimal kontrol kuralına dahil edilmesiyle test sistemi uygulamalarında karşılaşılan doyum problemleri için performans artımı sağlanması hedeflenmiştir. Bu amaçla, ilk olarak örnek sistem için sistemin doğrusal olmayan dinamik denklemleri oluşturulmuştur. Model çalışma noktası etrafında doğrusallaştırılarak, ivme durum değişkeni olacak şekilde durum uzayı modeli oluşturulmuştur. Elde edilen model, örnek sisteme ait model parametreleri kullanılarak, MPC içerisinde kullanılmak üzere ayrıklaştırılmıştır. MPC kuralı, yığın metodu (batch method) yardımı ile oluşturularak, kısıtlamalı optimal kontrol problemi arama algoritması yardımı ile çözülmüştür. Kontrol performansının tespiti amacı ile LQR ile karşılaştırmalı sayısal benzetim sonuçları sunulmuştur. Ayrıca sayısal benzetim testleri model belirsizliği ve ölçüm gürültüsü koşulları altında tekrarlanmış ve sonuçlar sunulmuştur. Elde edilen sonuçlar yorumlanmıştır ve gelecek çalışmalar için önerilerde bulunulmuştur.In this study, Model Predictive Control (MPC) is designed for the control of hydraulic test systems that are used for determining the strength and performance of the product. It is aimed to increase the performance of the saturation problems faced during the test system applications while including the system constraints in the optimal control rule. For this purpose, the nonlinear dynamic equations are first obtained for the considered test system. The state space model is obtained by linearizing the model around the equilibrium point in a way that the design variable is considered to be acceleration. The obtained model is discretized for employing it in MPC by using the model parameters of the considered system. MPC rule is solved via constituting batch approach method through constrained optimal control problem search algorithm. The simulation result of the comparisons with LQR is presented with the aim of examining the control performance. In addition, numerical simulations are repeated under parametric model uncertainty and measurement noise conditions and results are presented. The obtained results are discussed, and future studies are suggested.Anahtar kelimeler: Hidrolik test sistemi, Model öngörülü kontrol, Kısıtlamalı optimizasyon

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