International Journal of Systems, Control and Communications (10 papers in press)
Modeling and Global Predictive Control for Distributed-driven High Speed
by Wei Yongsong, Wu Jing, Li Shaoyuan
Complete Amplitude Scaling and Projective Synchronization of a class of Nonlinear Dynamical systems
by Vicky Garg, Bharat Bhushan Sharma
Abstract: The amplitude control of chaotic systems is important keeping in view different applications of such systems. This paper addresses attaining complete amplitude control by introducing a control function into the nonlinearity of a class of chaotic systems which are having only one nonlinearity. The analytical results presented here show that amplitude of all states of addressed class of chaotic systems can be controlled by introducing control function with the nonlinearity without altering the Lyapunov exponents. Further, the control scheme by applying the Lyapunov stability is presented to realize projective synchronization of the addressed class of systems by considering the fact that the control function can provide the scale factors. The proposed synchronization control function is derived using Lyapunov stability theory with typical feature of amplitude scaling without losing chaotic properties. The approach is illustrated using the Genesio system and cubic Chua system as typical examples. The simulation results show the efficacy of proposed approach in achieving amplitude control of all states and the corresponding projective synchronization under the influence of proposed controller.
Keywords: Lyapunov exponent; Amplitude scaling; Genesio system; cubic Chua system; Projective synchronization.
Quid Pro Quo LEACH protocol
by Abed Al Raoof Bsoul, Ahmad Manasrah, Khalid M.O. Nahar, Moyawiah Al-Shennaq
Abstract: Wireless sensor network (WSN) consists of a large number of sensors to sense different variations in the surroundings from various locations. These sensors communicate with each other to forward the gathered data to the base station (BS). Hence, the energy consumption is one of the main issues that affects the overall performance of the WSN implementation. In this paper, a Quid Pro Quo LEACH (QPQ-LEACH) protocol is introduced. The working mechanism of the Cluster Head (CH) is maintained. However, the CH will not be replaced by new CH until it expends energy due to its continuous working time that is less than a certain threshold value. Moreover, the QPQ-LEACH trades the re-clustering process to save the energy consumed for establishing new clusters every round. The simulation results show that the proposed QPQ-LEACH protocol effectively reduces the energy consumption and prolongs the network lifetime in comparison with other known protocols.
Keywords: Energy-efficient; Routing in WSN; Low energy adaptive clustering hierarchy (LEACH); Enhanced LEACH; wireless sensor networks; cluster head selection; Base station; Energy efficient Clustering; Ad Hoc Communication; WSN lifetime.
Implementation of Electroencephalography (EEG) Controlled Prosthetic Hand
by Syed Tahir Hussain Rizvi, Muhammad Majid Gulzar, Muhammad Yaqoob Javed
Abstract: Use of brain signals for restoring function of impaired body parts using scientific methods is called Brain Machine Interface (BMI). This article presents BMI to control five-fingered prosthetic hand using the Electroencephalography (EEG) signals. The core objective of the system is to develop a control system that will be able to communicate with the brain thoughts. EEG signals captured from the human scalp are used as information carrier for Brain Control Interface (BCI) system. This research article discusses the development of a system to assist disable persons using EEG based signals.
Keywords: Prosthetic Hand; Electroencephalography; Microcontroller; Brain Control Interface; Physical Implementation.
Moth-Flame optimization algorithm based fractional order PID controller with MRAC tuning configuration
by Bachir Bourouba, Samir Ladaci, Abdelhafid Chaabi
Abstract: This paper proposes a new Fractional-order PID controller (FOPID) design based on the adaptive model reference control (MRAC) configuration using a practical numerical search method called Moth-Flame Optimization (MFO) algorithm for the parameters' adjustment. The five parameters of the fractional order PIλDμ controller, namely the coefficients KP, KI and KD and the fractional integral and derivative orders λ and μ are optimized by evaluating an exact quadratic performance index.
Numerical simulation examples illustrate the effectiveness of the proposed tuning method for different plant model structures, and to show relative performance enhancement comparatively to other parameters' tuning strategies.
Keywords: Moth-Flame Optimization algorithm; fractional order PIλDμ controller; MRAC; parameter tuning.
Smart Supply Chain Management using Internet of Things (IoT)
by Sangeetha Manoharan
Abstract: Supply Chain Management (SCM) records the information about the movement of raw materials. Radio Frequency Identification (RFID) is the technology considered as the next promising technology in serving the positioning purpose. This paper proposes an SCM Simulation platform that deals with the tracking of goods or raw materials at both indoor and outdoor environment and also to monitor the goods using IoT anywhere and also at any time. Indoor Tracking of the good is accomplished through RFID Tags and Outdoor Tracking is done through Global Positioning Systems (GPS). XAMPP control panel is the server used here which is used to determine the location of goods and information updates on the server.
Keywords: Arduino; global positioning system; GPS; hypertext preprocessor;
PHP; internet of thing; IoT; radio frequency identification; RFID; tracking.
A Hybrid Bio-Inspired Approach to Solving the Routing Problem in Mobile Ad-Hoc Networks
by Labed Said, Kout Akram, Chikhi Salim, El-Bay Bourennane
Abstract: A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile hosts (nodes) connected by a wireless link.However, the problem of designing routing protocols poses challenges to researchers due to the unpredictable and dynamic nature of ad-hoc networks. Hence, bio-inspired algorithms are widely used to design adaptive routing strategies for MANETs. This paper proposes a routing protocol based on the hybridization of Ant Colony Optimization (ACO) and 2-opt heuristic with the optimization of ACO parameters. Given the vast scope of the parameters, a genetic algorithm is used to minimize the complexity of the problem. The implementation of the method is realized by Matlab. To valid the results in terms of the Quality of Service parameters (i.e.:Normalized Overhead Load, End-to-End Delay and Throughput), a comparison was conducted using the Ad-hoc on-demand distance vector routing protocol.
Keywords: Mobile Ad-hoc Network; Bio-inspired routing; Ant Colony Optimization; Genetic Algorithm; Routing Protocols; QoS.
Fuzzy Autonym MFs to improve complex grid network security by Fuzzy Implication PSO algorithm for dealing of islanding ADCS mode
by Kadapa Harinadha Reddy
Abstract: The network system with bigger number of connectivity computing nodes during the operation is a big challenge and composite job for secure and protective measures. Many issues are arising during the operation like disturbance, disorder and maintenance troubles. Proposed method and technique is seriously involved in these safe measuring issues through identification. Data acquisition from large network has been well defined from the many methods in present scenario of world science and technology. Fuzzy based implication system is elaborately presented with variable weighted random parameter of Particle Swarm Optimization (PSO) in cognitive and social terms. The distance between personal data set and global set data points positions, at two previous instants are taken for modified PSO. Main content this paper is that of Data handling and concentrated in elaborating the modelling to complete this task for Abnormal Disturbance Conditional State (ADCS), operating mode of network. Information from data availability in define zone to be classified accurately and precisely. This paper presents, up to date Fuzzy Memberships (FMFs) are obtained at every sampling interval according to the consequent instants of swam optimization. These FMFs are automatically updated to network state of operation and corresponding dealing of these abnormal issues. Also, control vector from fuzzy system is used to modify PSO algorithm to essential analysis and identification and differentiation of data on user required satisfy level. Data acquired from the grid network in two intervals t, (t-1) and distance dt and dt-1 is considered for proposed FIM-PSO. Results of data at two instants, auto updating of the width of right and left FMFs is done by mathematical approximation. This paper presents auto updating FMFs i.e. Autonym Fuzzy Memberships (AFMFs) and proposed Fuzzy Implication PSO (FIM-PSO) for analysis and hence identification of ADCS mode.
Keywords: Fuzzy implication system; Fuzzy Memberships (FMFs); Particle Swarm Optimization (PSO); Personal Best Data Sets (PBDS); Global Best Data Sets (GBDS) and Abnormal Disturbance Conditional State (ADCS) mode.
Optimality Conditions for Optimal Control under Parametric Representation of Interval Uncertainty
by Mohadeseh Ramezanzaeh, Omid Solaymani Fard
Abstract: The purpose of this paper is to offer a new approach that enables the decision maker to investigate optimal control problems under uncertainty\r\n(undetermined) processes. To this end, using the novel parametric representations of interval quantities as in  the approach is developed to find a candidate for the solution of interval optimal control problem. Furthermore, necessary and sufficient optimality conditions are provided which guarantee the candidate solution to be optimal. Finally, some examples are given to show the main results, more specifically, a discussion on the interval optimal control governed by half-model of a car is also presented.
Keywords: Interval number; Interval-valued function; Interval optimal control problem; Necessary condition; Sufficient condition.
Sensitivity evolution in Quantum Hamiltonian Estimation
by YanJun Zhang, Lu Wang, Jun Zhang
Abstract: In this paper we investigate the sensitivity evolution in estimating the unknown quantum Hamiltonian parameters. We apply Kullback-Liebler (KL) divergence to quantify the difference of quantum measurements between deviated and authentic parameter values. From explicit formula for the Fisher Information Matrix (FIM), we can calculate the second order approximation of the KL divergence. For several quantum mechanical systems, we use this analytical method to investigate the sensitivity evolution of estimating the underlying unknown parameters. We find that in all these examples, the FIM is divergent, which indicates that it is possible to design an unbiased estimator that yields the unknown parameters precisely.
Keywords: Parameter Estimation; Fisher Information Matrix; Sensitivity evolution.