Because of continuous technical progress over the last decades artificial pancreas (AP) systems have recently become reality for patients with type 1 diabetes (T1D) with first AP devices entering the market. However, all AP systems commercially under development are so-called hybrid closed loop systems, meaning that only the basal insulin is adjusted by the algorithm, whereas the meal boluses still have to be triggered manually by the patient. Fully closed loop systems for T1D that also administer meal boluses autonomously are so far mainly of academic interest. The biggest drawback of fully closed loop systems is that they can only give an insulin bolus as soon as a meal is detected from the recorded data, leading to significant delays in insulin delivery (and therefore more pronounced peaks in postprandial glucose) and/or an increased risk of hypoglycemia (in case of false positive detections). Contrary to almost all publications on the topic, the current paper investigates the feasibility of fully closed loop systems for patients with type 2 diabetes (T2D). Since glycemic variability tends to be significantly lower in T2D and since glucose dynamics are somewhat slower, fully closed loop systems seem in fact more favorable for this patient group than for T1D. The paper investigates the performance of available meal detection algorithms from the literature (developed for T1D patients) and modifies them for application in T2D. Additionally, the paper proposes a simple fully closed loop algorithm for T2D patients including a module for automatic meal bolusing and demonstrates its feasibility and safety.