We consider a congestion control problem in computer networks. The problem is posed as an optimal control problem and reduced to a problem of finding solutions to delay differential equations. Systems involving time delays in the dynamics are actually very difficult to model and therefore very difficult to solve. We consider three approaches in our congestion control problem: an elastic queue approach leading to an optimal control problem with a state–dependent delay differential equation; three approaches in flow models (also leading to systems containing delay differential equations), precisely the dual control approach, the primal–dual control approach and the control approach based on queueing delay. The elastic queue approach is not explored due to the lack of software good enough to solve optimal control problems involving delay differential equations. In flow models, we consider the standard case, that is where the feedback from sources to links is exact and the network behaves perfectly well (without any unexpected event). We also consider some non–standard cases such as the case where this feedback contains errors (for example overestimation, underestimation or noise), and the case where one link breaks in the network. We numerically solve the delay differential equations obtained and use the results we get to determine all the considered dynamics in the network. This is followed by an analysis of the results. We also explore the stability of some simple cases in the dual control approach, with weaker conditions on some network parameters, and discuss some fairness conditions in some simple cases in all the flow model approaches. Non–standard cases are also solved numerically and the results can be compared with those obtained in the standard case.