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1
Content available Modified PSO Based Channel Allocation Scheme for Interference Management in 5G Wireless Mesh Networks
Benni Nirmalkumar S., Manvi Sunilkumar S.
Journal of Telecommunications and Information Technology
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2022
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nr 2
1--13
EN
Efficient channel management is a challenge that next-generation wireless networks need to meet in order to satisfy increasing bandwidth demand and transmission rate requirements. Non-orthogonal multiple access (NOMA) is one of such efficient channel allocation methods used in 5G backhaul wireless mesh networks. In this paper, we propose a power demand-based channel allocation method for 5G backhaul wireless mesh networks by employing NOMA and considering traffic demands in small cells, thereby improving channel utility. In this scheme, we work with physical layer transmission. The foremost aim is to mutually optimize the uplink/downlink NOMA channel assignment in order to increase user fairness. The approach concerned may be divided into two steps. First, initial channel allocation is performed by employing the traveling salesman problem (TSP), due to its similarity to many-to-many double-side user-channel allocation. Second, the modified particle swarm optimization (PSO) method is applied for allocation updates, by introducing a decreasing coefficient which may have the form of a standard stochastic estimate algorithm. To enhance exploration capacity of modified the PSO, a random velocity is included to optimize the convergence rate and exploration behavior. The performance of the designed scheme is estimated through simulation, taking into account such parameters as through put, spectral efficiency, sum-rate, outage probability, signal to-interference plus noise ratio (SINR), and fairness. The proposed scheme maximizes network capacity and improves fairness between the individual stations. Experimental results show that the proposed technique performs better than existing solutions.
2
Content available Linear and Planar Array Pattern Nulling via Compressed Sensing
Mohammed Jafar Ramadhan, Thaher Raad H., Abdulqader Ahmed Jameel
Journal of Telecommunications and Information Technology
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2021
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nr 3
50--55
EN
An optimization method based on compressed sensing is proposed for uniformly excited linear or planar antenna arrays to perturb excitation of the minimum number of array elements in such a way that the required number of nulls is obtained. First, the spares theory is relied upon to formulate the problem and then the convex optimization approach is adopted to find the optimum solution. The optimization process is further developed by using iterative re-weighted l1- norm minimization, helping select the least number of the sparse elements and impose the required constraints on the array radiation pattern. Furthermore, the nulls generated are wide enough to cancel a whole specific sidelobe. Simulation results demonstrate the effectiveness of the proposed method and the required nulls are placed with a minimum number of perturbed elements. Thus, in practical implementations of the proposed method, a highly limited number of attenuators and phase shifters is required compared to other, conventional methods.
3
Content available Application-oriented experiment design for model predictive control
Jakowluk W., Świercz M.
Bulletin of the Polish Academy of Sciences. Technical Sciences
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2020
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Vol. 68, nr 4
883--891
EN
The model predictive control (MPC) technique has been widely applied in a large number of industrial plants. Optimal input design should guarantee acceptable model parameter estimates while still providing for low experimental effort. The goal of this work is to investigate an application-oriented identification experiment that satisfies the performance objectives of the implementation of the model. A- and D-optimal input signal design methods for a non-linear liquid two-tank model are presented in this paper. The excitation signal is obtained using a finite impulse response filter (FIR) with respect to the accepted application degradation and the power constraint. The MPC controller is then used to control the liquid levels of the double tank system subject to the reference trajectory. The MPC scheme is built based on the linearized and discretized model of the system to predict the system’s succeeding outputs with reference to the future input signal. The novelty of this model-based method consists in including the experiment cost in input design through the objective function. The proposed framework is illustrated by means of numerical examples, and simulation results are discussed.
4
Content available Robust extremum seeking for a second order uncertain plant using a sliding mode controller
Solis Cesar, Clempner Julio, Poznyak Alexander
International Journal of Applied Mathematics and Computer Science
|
2019
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Vol. 29, no. 4
703--712
EN
This paper suggests a novel continuous-time robust extremum seeking algorithm for an unknown convex function constrained by a dynamical plant with uncertainties. The main idea of the proposed method is to develop a robust closed-loop controller based on sliding modes where the sliding surface takes the trajectory around a zone of the optimal point. We assume that the output of the plant is given by the states and a measure of the function. We show the stability and zone-convergence of the proposed algorithm. In order to validate the proposed method, we present a numerical example.
5
Content available Constraints in allocation of thrusters in a DP simulator
Zalewski P.
Zeszyty Naukowe Akademii Morskiej w Szczecinie
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2017
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nr 52 (124)
45--50
EN
Vessels conducting dynamic positioning (DP) operations are usually equipped with thruster configurations that enable the generation of force and torque. Some thrusters in these configurations are deliberately redundant to minimize consequences of thruster failures, enable overactuated control and increase the safety in operation. On such vessels, a thrust allocation system must be used to distribute the control actions determined by the DP controller among the thrusters. The optimal allocation of the thrusters’ settings in DP systems is a problem that can be solved by convex optimization methods depending on the criteria and constraints used. This paper presents a quadratic programming (QP) method, adopted in a DP control model, which is being developed in Maritime University of Szczecin for ship simulation purposes.
6
Content available Convex optimization of thrust allocation in a dynamic positioning simulation system
Zalewski P.
Zeszyty Naukowe Akademii Morskiej w Szczecinie
|
2016
|
nr 48 (120)
58--62
EN
Vessels conducting dynamic positioning (DP) operations are usually equipped with thruster configurations that enable the generation of resultant force and moment in any direction. These configurations are deliberately redundant in order to reduce the consequences of thruster failures and increase the safety. On such vessels a thrust allocation system must be used to distribute the control actions determined by the DP controller among the thrusters. The optimal allocation of thrusters’ settings in DP systems is a problem that can be solved by several convex optimization methods depending on criteria and constraints used. The paper presents linear programming (LP) and quadratic programming (QP) methods adopted in the DP control model which is being developed at the Maritime University of Szczecin for ship simulation purposes.
7
Content available Methods of thrust allocation in a DP simulation system of Maritime University of Szczecin
Zalewski P.
Annual of Navigation
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2016
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No. 23
209--218
EN
Vessels conducting dynamic positioning (DP) operations are usually equipped with thruster configurations that enable generation of resultant force and moment in any direction. These configurations are deliberately redundant in order to reduce the consequences of thruster failures and increase the safety. On such vessels a thrust allocation system must be used to distribute the control actions determined by the DP controller among the thrusters. The optimal allocation of thrusters’ settings in DP systems is a problem that can be solved by several convex optimization methods depending on criteria and constraints used. The paper presents linear programming (LP) and quadratic programming (QP) methods adopted in DP control model which is being developed in Maritime University of Szczecin for ship simulation purposes.
PL
Statki pozycjonowane dynamicznie (DP) mają konfiguracje pędników umożliwiające wytwarzanie wypadkowej siły i momentu w dowolnym kierunku. Konfiguracje te są zazwyczaj nadmiarowe w celu zmniejszenia skutków awarii pojedynczych pędników, a tym samym zwiększenia poziomu bezpieczeństwa wykonywanej pracy. Na takich jednostkach musi być stosowany system alokacji wyliczający i przydzielający nastawy do poszczególnych pędników. Optymalna alokacja nastaw pędników w systemach DP jest problemem, który można rozwiązać, w zależności od zadanych kryteriów i ograniczeń, kilkoma metodami optymalizacji wypukłej. W artykule przedstawiono metody programowania liniowego (LP) i kwadratowego (QP) zastosowane w modelu sterowania DP w symulatorach nawigacyjno-manewrowych Akademii Morskiej w Szczecinie.
8
Content available Application of descriptor approaches in design of PD observer-based actuator fault estimation
Filasova A., Krokavec D., Serbak V.
Archives of Control Sciences
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2015
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Vol. 25, no. 1
51--64
EN
Stability analysis and design for continuous-time proportional plus derivative state observers is presented in the paper with the goal to establish the system state and actuator fault estimation. Design problem accounts a descriptor principle formulation for non-descriptor systems, guaranteing asymptotic convergence both the state observer error as fault estimate error. Presented in the sense of the second Lyapunov method, an associated structure of linear matrix inequalities is outlined to possess parameter existence of the proposed estimator structure. The obtained design conditions are verified by simulation using a numerical illustrative example.
9
Content available Joint allocation and transportation problem in supply network optimisation
Filcek G.
Management and Production Engineering Review
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2012
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Vol. 3, No. 3
3-10
EN
The paper concerns joint allocation and transportation as an optimization problem in selected supply networks. The network consists of a set of suppliers of the raw material, a set of production units and a set of product receivers. The raw material is treated as fast perishing good like vegetables or fruits. The production units are described by time models. In the optimization process, the time of the production and cost of the transportation is taken into account. The objective function is in general non-convex function of raw material allocation and transportation plans of the raw material and the product. To solve the problem considered, exact and heuristic algorithms have been developed and presented. To solve convex problems, solver Lingo developed by Lindo systems is proposed. The idea of a computer decision supported system integrating all presented algorithms is presented as well as four numerical examples illustrating some properties of the assumed supply network model.
10
Content available Solving Support Vector Machine with Many Examples
Białoń P.
Journal of Telecommunications and Information Technology
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2010
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nr 3
65-70
EN
Various methods of dealing with linear support vector machine (SVM) problems with a large number of examples are presented and compared. The author believes that some interesting conclusions from this critical analysis applies to many new optimization problems and indicates in which direction the science of optimization will branch in the future. This direction is driven by the automatic collection of large data to be analyzed, and is most visible in telecommunications. A stream SVM approach is proposed, in which the data substantially exceeds the available fast random access memory (RAM) due to a large number of examples. Formally, the use of RAM is constant in the number of examples (though usually it depends on the dimensionality of the examples space). It builds an inexact polynomial model of the problem. Another author's approach is exact. It also uses a constant amount of RAM but also auxiliary disk files, that can be long but are smartly accessed. This approach bases on the cutting plane method, similarly as Joachims' method (which, however, relies on early finishing the optimization).
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