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2021 (vol. 31) - Number 3

Vanya R. Barseghyan:

The problem of control of rod heating process with nonseparated conditions at intermediate moments of time

Khadidja Bentata , Ahmed Mohammedi, Tarak Benslimane:

Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition

Jakub Musial, Krzysztof Stebel and Jacek Czeczot:

Self-improving Q-learning based controller for a class of dynamical processes

Ramesh Devarapalli and Vikash Kumar:

Power system oscillation damping controller design: a novel approach of integrated HHO-PSO algorithm

T. Kaczorek:

Poles and zeros assignment by state feedbacks in positive linear systems

Saule Sh. Kazhikenova and Sagyndyk N. Shaltakov, Bekbolat R. Nussupbekov:

Difference melt model

R. Almeida and N. Martins, E. Girejko and A.B. Malinowska, L. Machado:

Evacuation by leader-follower model with bounded confidence and predictive mechanisms

B. Zhao and R. Zhang, Y. Xing:

Evaluation of medical service quality based on a novel multi-criteria decision-making method with unknown weighted information

Stefan Mititelu, Savin Treanta:

Efficiency in vector ratio variational control problems involving geodesic quasiinvex multiple integral functionals

D.K. Dash and P.K. Sadhu, B. Subudhi:

Spider monkey optimization (SMO) – lattice Levenberg–Marquardt recursive least squares based grid synchronization control scheme for a three-phase PV system

Suresh Rasappan and K.A. Niranjan Kumar:

Dynamics, control, stability, diffusion and synchronization of modified chaotic colpitts oscillator

ACS Abstract:

2011 (Volume 21)
Number 3
1. Pairwise control principle in large-scale systems
2. On transformation of STRIPS planning to linear programming
3. Evolutionary computation approaches to tip position controller design for a two-link flexible manipulator
4. Checking of the positivity of descriptor linear systems by the use of the shuffle algorithm
5. Hybrid Mesh Adaptive Direct Search and Genetic Algorithms Techniques for industrial production systems
6. A stabilization method of inhomogeneous ladder networks with nonlinear elements
7. High performance backstepping control of induction motor with adaptive sliding mode observer

Pairwise control principle in large-scale systemsDownload full PDF article
A. Filasova, D. Krokavec
(Technical University of Kosice, Czech Rep.)

The purpose of the paper is present an algorithm of partially decentralized control design for one type of large-scale linear dynamical system. The pairwise autonomous principle is preferred where design conditions are derived in the bounded real lemma form, and global system stability is reproven to formulate potential application principle in fault tolerant control. The validity of the proposed method is demonstrated by the numerical example.

keywords: large-scale systems, decentralized control, state feedback, linear matrix inequality, asymptotic stabilit


On transformation of STRIPS planning to linear programmingDownload full PDF article
A. Galuszka
(Silesian University of Technology, Gliwice, Poland)

STRIPS language is a convenient representation for artificial intelligence planning problems. Planning is a task of coming up with a sequence of actions that will achieve a goal. In this work a heuristic of polynomial transformation of STRIPS planning problem to linear programming problem (LP) is presented. This is done because planning problems are hard computational problems (PSPACE- complete in general case) and LP problems are known to be computational easy. Representation of STRIPS planning as a set of equalities and inequalities based on the transformation is also proposed.  The exemplary simulation shows the computational efficiency of solving planning problem with proposed transformation.

keywords: planning, problem solving, block world, uncertainty, linear programming, computational complexity


Evolutionary computation approaches to tip position controller design for a two-link flexible manipulatorDownload full PDF article
B. Subudhi, S. Ranasingh, A.K. Swain
(National Institute of Technology, Rourkela, India)

Controlling multi-link flexible robots is very difficult compared rigid ones due to interlink coupling, nonlinear dynamics, distributed link flexure and under-actuation. Hence, while designing controllers for such systems the controllers should be equipped with optimal gain parameters. Evolutionary Computing (EC) approaches such as Genetic Algorithm (GA), Bacteria Foraging Optimization (BFO) are popular in achieving global parameter optimizations. In this paper we exploit these EC techniques in achieving optimal PD controller for controlling the tip position of a two-link flexible robot. Performance analysis of the EC tuned PD controllers applied to a two-link flexible robot system has been discussed with number of simulation results.

keywords: flexible manipulator, genetic algorithm, bacteria foraging, fitness function


Checking of the positivity of descriptor linear systems by the use of the shuffle algorithmDownload full PDF article
T. Kaczorek
(Bialystok University of Technology, Poland)

Necessary and sufficient conditions for the positivity of descriptor continuous-time and discrete-time linear systems are established. The shuffle algorithm is applied to transform the state equations of the descriptor systems to their equivalent form for which necessary and sufficient conditions for their positivity have been derived. A procedure for checking the positivity of the descriptor systems is proposed and illustrated by numerical examples.

keywords: descriptor, continuous-time, discrete-time, linear system, positivity, shuffle algorithm


Hybrid Mesh Adaptive Direct Search and Genetic Algorithms Techniques for industrial production systemsDownload full PDF article
P. Vasant
(University Technology Petronas, Malaysia)

In this paper, computational and simulation results are presented for the performance of the fitness function, decision variables and CPU time of the proposed hybridization method of Mesh Adaptive Direct Search (MADS) and Genetic Algorithm (GA). MADS is a class of direct search of algorithms for nonlinear optimization. The MADS algorithm is a modification of the Pattern Search (PS) algorithm. The algorithms differ in how the set of points forming the mesh is computed. The PS algorithm uses fixed direction vectors, whereas the MADS algorithm uses random selection of vectors to define the mesh. A key advantage of MADS over PS is that local exploration of the space of variables is not restricted to a finite number of directions (poll directions). This is the primary drawback of PS algorithms, and therefore the main motivation in using MADS to solve the industrial production planning problem is to overcome this restriction. A thorough investigation on hybrid MADS and GA is performed for the quality of the best fitness function, decision variables and computational CPU time.

keywords: mesh adaptive direct search, genetic algorithms, fitness function, degree of possibility, level of satisfaction


A stabilization method of inhomogeneous ladder networks with nonlinear elementsDownload full PDF article
P. Skruch
(AGH University of Science and Technology, Krakow, Poland)

In the paper, different structures of electric ladder networks are considered: RC, RL, and RLC. Such systems are composed of resistors, inductors and capacitors connected in series. The elements of the network are not identical and have nonlinear characteristics. The network's dynamic behavior can be mathematically described by nonlinear differential equations. A class of robust feedback controls is designed to stabilize the system. The asymptotic stability of the closed-loop system is analyzed and proved by the use of Lyapunov functionals and LaSalle's invariance principle. The results of computer simulations are included to verify theoretical analysis and mathematical formulation.

keywords: electric ladder network, nonlinear circuit, stabilization, feedback control


High performance backstepping control of induction motor with adaptive sliding mode observerDownload full PDF article
I. Bakhti, A. Maakouf
(Batna University, Algeria)
S. Chaouch
(M'sila University, Algeria)

It is well known that modern control of induction motor relies on a good dynamic model of the motor. Extensive research and  activity have been devoted to the problem of induction motor control over the last decade. In this paper we introduce backstepping control with amelioration of performance to guarantee stability of the system. Accurate knowledge of the rotor speed and flux position is the key factor in obtaining a high-performance and high-efficiency induction-motor drive. Thus a sliding mode observer design is presented. Simulation results are included to illustrate good performance of backstepping control of sensorless induction motors with flux observer.

keywords: induction motor, backstepping control, sliding mode, flux observer design, estimation, sensorless control


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