In the calculations presented in the article, an artificial immune system (AIS) was used to plan the routes of the fleet of delivery vehicles supplying food products to customers waiting for the delivery within a specified, short time, in such a manner so as to avoid delays and minimize the number of delivery vehicles. This type of task is classified as an open vehicle routing problem with time windows (OVRPWT). It comes down to the task of a traveling salesman, which belongs to NP-hard problems. The use of the AIS to solve this problem proved effective. The paper compares the results of AIS with two other varieties of artificial intelligence: genetic algorithms (GA) and simulated annealing (SA). The presented methods are controlled by sets of parameters, which were adjusted using the Taguchi method. Finally, the results were compared, which allowed for the evaluation of all these methods. The results obtained using AIS proved to be the best.
This paper presents control method for multiple two-wheeled mobile robots moving in formation. Trajectory tracking algorithm from  is extended by collision avoidance, and is applied to the different type of formation task: each robot in the formation mimics motion of the virtual leader with a certain displacement. Each robot avoids collisions with other robots and circular shaped, static obstacles existing in the environment. Artificial potential functions are used to generate repulsive component of the control. Stability analysis of the closed-loop system is based on Lyapunov-like function. Effectiveness of the proposed algorithm is illustrated by simulation results.
We propose a class of m-crane control systems, that generalizes two- and three-dimensional crane systems. We prove that each representant of the described class is feedback equivalent to the second order chained form with drift. In consequence, we prove that it is differentially flat. Then we investigate its control properties and derive a control law for tracking control problem.
One of the mathematical tools to measure the generation rate of new patterns along a sequence of symbols is the Lempel-Ziv complexity (LZ). Under additional assumptions, LZ is an estimator of entropy in the Shannon sense. Since entropy is considered as a measure of randomness, this means that LZ can be treated also as a randomness indicator. In this paper, we used LZ concept to the analysis of different flow regimes in cold flow combustor models. Experimental data for two combustor’s configurations motivated by efficient mixing need were considered. Extensive computer analysis was applied to develop a complexity approach to the analysis of velocity fluctuations recorded with hot-wire anemometry and PIV technique. A natural encoding method to address these velocity fluctuations was proposed. It turned out, that with this encoding the complexity values of the sequences are well correlated with the values obtained by means of RMS method (larger/smaller complexity larger/smaller RMS). However, our calculations pointed out the interesting result that most complex, this means most random, behavior does not overlap with the “most turbulent” point determined by the RMS method, but it is located in the point with maximal average velocity. It seems that complexity method can be particularly useful to analyze turbulent and unsteady flow regimes. Moreover, the complexity can also be used to establish other flow characteristics like its ergodicity or mixing.
The paper is intented to show a new, state space, discrete, non integer order model of a one-dimensional heat transfer process. The proposed model derives directly from time continuous, state space model and it uses the discrete Grünwald-Letnikov operator to express the fractional order difference with respect to time. Stability and spectrum decomposition for the proposed model are recalled, the accuracy and convergence are analyzed too. The convergence of the proposed model does not depend on parameters of heater and measuring sensors. The dimension of the model assuring stability and predefined rate of convergence and stability is estimated. Analytical results are confirmed by experiments.
Currently, the distribution system has been adapted to include a variety of Distributed Energy Resources (DERs). Maximum benefits can be extracted from the distribution system with high penetration of DERs by transforming it into a sustainable, isolated microgrid. The key aspects to be addressed for this transformation are the determination of the slack bus and assurance of reliable supply to the prioritized loads even during contingency. This paper explores the possibilities of transforming the existing distribution system into a sustainable isolated network by determining the slack bus and the optimal locations and capacity of Distributed Generators (DGs) in the isolated network, taking into account the contingencies due to faults in the network. A combined sensitivity index is formulated to determine the most sensitive buses for DG placement. Further, the reliability based on the loss of load in the isolated system when a fault occurs is evaluated, and the modifications required in for reliability improvement are discussed. The supremacy of the transformed isolated network with distributed generators is comprehended by comparing the results from conventional IEEE 33-bus grid connected test system and modified IEEE 33-bus isolated test system having no interconnection with the main grid.
This paper presents an innovative method of technology mapping of the circuits in ALM appearing in FPGA devices by Intel. The essence of the idea is based on using triangle tables that are connected with different configurations of blocks. The innovation of the proposed method focuses on the possibility of choosing an appropriate configuration of an ALM block, which is connected with choosing an appropriate decomposition path. The effectiveness of the proposed technique of technology mapping is proved by experiments conducted on combinational and sequential circuits.
The article presents an example of the use of functional series for the analysis of nonlinear systems for discrete time signals. The homogeneous operator is defined and it is decomposed into three component operators: the multiplying operator, the convolution operator and the alignment operator. An important case from a practical point of view is considered – a cascade connection of two polynomial systems. A new, binary algorithm for determining the sequence of complex kernels of cascade from two sequences of kernels of component systems is presented. Due to its simplicity, it can be used during iterative processes in the analysis of nonlinear systems (e.g. feedback systems).
This paper presents the improved methodology for the direct calculation of steady-state periodic solutions for electromagnetic devices, as described by nonlinear differential equations, in the time domain. A novel differential operator is developed for periodic functions and the iterative algorithm determining periodic steady-state solutions in a selected set of time instants is identified. Its application to steady-state analysis is verified by an elementary example. The modified algorithm reduces the complexity of steady-state analysis, particularly for electromagnetic devices described by high-dimensional nonlinear differential equations.
This paper proposes a practical tuning of closed loops with model based predictive control. The data assumed to be known from the process is the result of the bump test commonly applied in industry and known in engineering as step response data. A simplified context is assumed such that no prior know-how is required from the plant operator. The relevance of this assumption is very realistic in the context of first time users, both for industrial operators and as educational competence of first hand student training. A first order plus dead time is approximated and the controller parameters immediately follow by heuristic rules. Analysis has been performed in simulation on representative dynamics with guidelines for the various types of processes. Three single-input-single-output experimental setups have been used with no expert users available in different locations – both educational and industrial – these setups are representative for practical cases: a variable time delay dominant system, a non-minimum phase system and an open loop unstable system. Furthermore, in a multivariable control context, a train of separation columns has been tested for control in simulation, followed by experimental tests on a laboratory system with similar dynamics, i.e. a sextuple coupled water tank system. The results indicate the proposed methodology is suitable for hands-on tuning of predictive control loops with some limitations on performance and multivariable process control.
The distortion of air gap magnetic field caused by the rotor eccentricity contributes to the electromechanical coupling vibration of the brushless DC (BLDC) permanent magnet in-wheel motor (PMIWM) in electric vehicles (EV). The comfort of the BLDC in-wheel motor drive (IWMD) EV is seriously affected. To deeply investigate the electromechanical coupling vibration of the PMIWM under air gap eccentricity, the PMIWM, tyre and road excitation are analyzed first. The influence of air gap eccentricity on air gap magnetic density is investigated. The coupling law of the air gap and the unbalanced magnetic force (UMF) is studied. The coupling characteristics of eccentricity rate, air gap magnetic density, UMF, phase current and vibration acceleration are verified on the test bench in the laboratory. The mechanism of the electromechanical coupling vibration of the BLDC PMIWM under air gap static eccentricity (SE), dynamic eccentricity (DE) and hybrid eccentricity (HE) is revealed. DE and HE deteriorate the vibration acceleration amplitude, which contributes the electromechanical coupling vibration of the PMIWM. The research results provide a solid foundation for the vibration and noise suppression of the PMIWM in distributed drive EV.
The paper deals with spectral and lasing characteristics of thulium-doped optical fibers fabricated by means of two doping techniques, i.e. via a conventional solution-doping method and via a nanoparticle-doping method. The difference in fabrication was the application of a suspension of aluminum oxide nanoparticles of defined size instead of a conventional chloride-containing solution. Samples of thulium-doped silica fibers having nearly identical chemical composition and waveguiding properties were fabricated. The sample fabricated by means of the nanoparticle-doping method exhibited longer lifetime, reflecting other observations and the trend already observed with the fibers doped with erbium and aluminum nanoparticles. The fiber fabricated by means of the nanoparticle-doping method exhibited a lower lasing threshold (by ~20%) and higher slope efficiency (by ~5% rel.). All these observed differences are not extensive and deserve more in-depth research; they may imply a positive influence of the nanoparticle approach on properties of rare-earth-doped fibers for fiber lasers.
The article presents issues related to the application of a moving horizon estimator for state variables reconstruction in an advanced control structure of a drive system with an elastic joint. Firstly, a short review of the commonly used methods for state estimation in presented. Then, a description of a state controller structure follows. The design methodology based on the poles-placement method is briefly described. Next, the mathematical algorithm of MHE is presented and some crucial features of MHE are analysed. Then, selected simulation and experimental results are shown and described. The investigation shows, among others, the influence of window length on the quality of state variables estimation.