Earticle

This paper deals with high performance speed control approach using direct flux and torque control for the induction motor (IM). The closed loop scheme of the drive utilizes the fuzzy logic controllers both in speed and electromagnetic torque control loops. Due to the drawbacks of the sensors, an algorithm is evolved to reconstruct the IM fluxes and electromagnetic torque. In fact, based on the model of the IM, the observed stator currents and IM fluxes are simultaneously obtained based on full order Luenberger observer. The observed stator currents and IM fluxes are adversely affected by rotor speed feedback signal and stator resistance variations due to temperature and frequency changes. To improve the performance of the overall system, the rotor speed and stator resistance are both estimated in such away to assume the overall stability of the state observer based on Lyaponov criterion. Digital simulation results are presented to show the improvement in performance of the proposed method.

In this paper a design methodology for a novel robust adaptive backstepping controller for the stabilization control of an inverted pendulum on a movable cart, which is a benchmark control problem in the nonlinear control system paradigm, has been presented in a systematic manner. The proposed control law provides a systematic iterative formulation of a Lyapunov energy function for the inverted pendulum system to ensure its stabilization and convergence of the angle tracking error as well as the estimation error of its unknown parameters towards zero. For easier parameter adaptation, the model of the inverted pendulum has been transformed into a motion control model. The effectiveness of the proposed algorithm has been verified in simulation studies. The controller design has been evaluated not only for the tracking performance but also for the parameter convergence rate of the system. It is quite interesting to note that during the simulation it does not require any prior information about the parameters of the mathematical model of the inverted pendulum.

The design of a communication network where the connectivity between nodes must be kept even after failure of some links can be modeled as a Generalized Steiner Problem. It consists of computing the minimal cost subnetwork of a given feasible network where certain pairs of nodes must satisfy a number of disjoint connectivity requirements and is known to be an NP-Complete problem. This paper introduces an heuristic based on the combinatorial optimization metaheuristic “Greedy Randomized Adaptive Search Procedure” (GRASP) to solve the edge-survivable version of the problem, where nodes are perfect but links can fail. The algorithm is tested with a set of heterogeneous network topologies and connectivity requirements obtaining promising results; in all cases with known optimal cost, optimal or near-optimal solutions are found.

The objective of this paper is to develop a framework that integrates two important concepts: Statistical process control (SPC) and engineering process control (EPC). Most of the literature researches on integrated SPC/EPC systems are focused into continuous process mainly with Algorithmic SPC. The integrated SPC/EPC systems in batch process control have not received the same degree of attention. In particular, there is an only Run-to-Run (RTR) control methodology application, which is mostly focused in semiconductor industry. This paper is a first of its kind in integrated SPC/EPC systems that applied in batch process and it based on a data-driven quality improvement tools. The proposed SPC/EPC integration is performed continually in two successive phases: (1) Active SPC for the batch making advance, and (2) RTR control action between batches. Control limits for critical variables are developed using information from the historical reference distribution of past successful batches. EPC application is based on the development of progressive knowledge-based rules. For a validation purpose, the proposed approach is applied to data collected from an industrial batch alkyd polymerization reactor, which evolution is monitored by measuring the overflow water weight, the acidity index and the viscosity of samples withdrawn from the reactor. This industrial process is poorly automated, subject to several disturbances, and the batches have uneven lengths. The synthesis is stopped at the maximum yield allowed by the gelation point of the cold product. Through this case study application, process engineers at the company are now able to use a valuable decision making tool when the production process is affected by certain disruptions, with obvious consequences on product quality, productivity and competitiveness.

Cloud computing is a new computing paradigm that attracted many computer users. Among these are big companies, small and big enterprise, agencies and individual users. Cloud computing brought a lot of advantages especially in ubiquitous services where everybody can access computer services through internet. With cloud computing, there is no need of physical hardware or servers that will support the company’s computer system, internet services and networks. It will basically cut down the expenses of the company allotted for the maintenance of the computer system. Along with the good benefits of Cloud Computing has to offer, there are security problems which make users anxious about the safety, reliability and efficiency of migrating to cloud computing. In this paper, the authors tried to study the threats and attacks that possibly launch in cloud computing and the possible solutions to mitigate these attacks. Aside of having network and application securities being adopted, there must be a security that authenticate the user when accessing the cloud services that is bound to the rules between the cloud computing provider and the client side.

For a large variety of Industrial applications dc motors are being used. The common requirement of the drives in industries is speed control under varying operating conditions. In several research studies, the controllers have been considered without modeling of final control element (FCE). In practical applications, the effect of dynamics and nonlinearity of FCE affects the performance of the system, so it is necessary to consider these for a dependable simulation study of the drive performance. The overall system becomes non-linear due to the dynamics of converter used as FCE. In this study a new approach is being used, first the transfer function of the buck converter is obtained by considering a small linear region near the operating point, then using overall transfer function of buck converter and dc motor, the PID settings are obtained. Now fuzzy logic is used to update these settings on-line corresponding to the changes that may occur in system operating conditions. This configuration of controller is also observed to have robust performance against parameter variations and uncertainties. For more close to actual performance evaluation PWM controlled buck converter, used as FCE has been simulated using sim-power system library of MATLAB. The comparative results are presented with PID and fuzzy adaptive PID control strategies implemented, for both types of control situations i.e. tracking speed control and load disturbance rejection and the strength of approach is demonstrated.

Most of nonlinear controllers need real time mobility operation so one of the most important devices which can be used to solve this challenge is Field Programmable Gate Array (FPGA). FPGA can be used to design a controller in a single chip Integrated Circuit (IC).Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a FPGA-based chattering free mathematical error-based tuning sliding mode controller (MTSMC) for highly nonlinear dynamic robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the switching function in presence of mathematical error-based method instead of switching function method in pure sliding mode controller. The results demonstrate that the FPGA-based sliding mode controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Pure sliding mode controller has difficulty in handling unstructured model uncertainties. To solve this problem applied mathematical model-free tuning method to FPGA-based sliding mode controller for adjusting the sliding surface gain ( ). Since the sliding surface gain ( ) is adjusted by mathematical model free-based tuning method, it is nonlinear and continuous. In this research new is obtained by the previous multiple sliding surface slopes updating factor . FPGA-based Chattering free mathematical error-based tuning sliding mode controller is stable controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in mathematical error-based tuning sliding mode controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12). To have higher implementation speed with good performance TVSC is implemented on Spartan 3E FPGA using Xilinx software (controller computation time=30.2 ns, Max frequency=63.7 MHz and controller action frequency=33 MHZ).

This paper presents a frequency monitoring system for Korean wide-area power protection based on virtual FDR. The virtual FDR is introduced to enhance the simulation capability of frequency monitoring systems and consists of three parts: modeling, estimation, and simulation. Once a power grid model is obtained in the virtual FDR based on EMTP-RV, the frequency is estimated by DFT filtering and gain compensation based on real and imaginary filtering. Various disturbances and conditions are simulated using the data from the power grid model. The proposed FDR allows the monitoring system to display simulated disturbances and data, including voltages, currents, and frequencies. Various simulation results were given to show of the effectiveness of the proposed frequency monitoring system based on the virtual FDR.

One of the benefits of IPv6 protocol is its extensibility of Extension Header. Extension Header is an optional part of IPv6 that is used to support a specific service on the data transmission. CRC Extension Header (CEH) is a new Extension Header proposed to improve IPv6 packets transmission over high speed network. The CEH was introduced to do error detection in Network layer that usually done in Data Link layer. Emulation of CEH showed the enhancement of packet transmission in terms of reduced network latency. However, it caused an overhead in sender as well as in receiver machine. This research aims to decrease the overhead by modifying the algorithm for generation and verification of CEH. The simulation result showed that the network latency reduced was about 34% compared to the former CEH algorithm.