Volume 3 Issue 1
Authors: Wang Jian-hong
Abstract: To study a direct weight optimization method in nonlinear system identification, linear terms were added in regards to observed input sequences in the former linear affine function to approximate a nonlinear property. Choosing two unknown weights concerning more linear terms, a detailed process for choosing these unknown weights was derived, and their key or auxiliary roles between the unknown weights were analyzed. Then the auxiliary role of the added unknown weights was shown in the process of approximating the nonlinear system.
Keywords: Nonlinear System; Direct Weight Optimization; Weight Selection
Authors: Mohammad Samadi Gharajeh; Sohrab Khanmohammadi
Abstract: Rescue applications perform rescue operations such as medical emergencies, fire fighting, and earthquake responses. Ad hoc networks are composed of mobile wireless nodes which communicate to one another in order to transmit various messages to a desired centre. Integration of these networks and a knowledge-based system (e.g., fuzzy logic) in rescue applications can improve rescue operations. This paper proposes three methods to dispatch rescue teams to events, select members of the proper team, and dispatch the support teams to event locations. Each of the methods uses an individual fuzzy controller, which works based on prior humanistic knowledge. All vehicles in urban environments are equipped with mobile wireless nodes that construct an ad hoc network. Appropriate decisions are determined based on various messages, which are transmitted from vehicles to a main centre (e.g., fire department). The first method, DMRTFL, selects an appropriate path from the centre to the event location to dispatch rescue teams based on path length, path traffic, passage probability through each path, and arrival time. The second method, SMRTFL, selects proper members for the rescue and support teams based on age, experience, event type, and success probability. The third method, DMSTFL, chooses a suitable centre for dispatching the support teams to an event location based on essential parameters including arrival time, event type, amount of equipment, number of forces, and success probability. Simulation results indicate that the proposed methods surpass existing traffic methods in terms of arrival time.
Keywords: Dispatching Method; Rescue Teams; Ad Hoc Networks; Fuzzy Decision Making; Rescue Applications
Authors: V.S.S. Yadavalli; Jeganathan Kathirvel
Abstract: In this paper, a continuous review perishable inventory system with a service facility having two heterogeneous servers (henceforth, referred to as Server 1 and Server 2) was considered in which Server 2 was always available while Server 1 went on vacation when the inventory level was less than or equal to one. The individual customer was issued a demanded item after a random service time, which was distributed as negative exponential. The life time of each commodity was assumed to be exponential. The inventory was replenished according to a (s, Q) control policy and the replenishing times were assumed to be exponentially distributed. At the end of a vacation period, service began if the inventory level was more than one in the system. Otherwise, the server took another vacation immediately and continued in the same method until at least two items were found to be in the system upon returning from a vacation. Any arriving primary customers who found the waiting room full were queued in orbit. The inter-retrial times were exponentially distributed. The joint probability distribution of the number of customers in the waiting room, the number of customers in orbit, the status of the servers, and the inventory level were obtained for the steady state case. Some important system performance measures in the steady state were derived, and the long-run total expected cost rate was also calculated. The results were illustrated numerically.
Keywords: Control Policy; Inventory with Service Time; Perishable; Multiple Vacations; Markov Process; Heterogeneous Servers
Authors: Yazdan Bavafa-Toosi
Abstract: The classical notions of gain margin and phase margin (Gm and Pm) which are among the fundamental topics in undergraduate control education have some confusing subtleties especially for students. These subtleties are in part due to the inherent shortcomings of the traditional definitions, and in part due to false guidelines provided by some classical texts. In this work these problems are discussed and settled. In particular, a new definition of Gm is proposed to better capture the underlying philosophy of being a measure of robustness. The false guidelines and claims are also revisited and rectified. The arguments are supported by several instructive NMP examples which are missing in the classical texts.
Keywords: Control Engineering Education; Gain Margin; Phase Margin; MATLAB