Initial State Of System Research Articles

Chaos Control in Gear Transmission System using GPC and SMC Controllers

Chaos is a phenomenon that occurs in some non-linear systems. Therefore, the output of the system will be heavily dependent on the initial conditions. Since the main characteristic of the chaos is an abnormal behavior of the system output, it should be considered in designing control systems. In this paper, controlling chaos phenomenon in a time-variant non-linear gear transmission system is investigated. To do this, a non-linear model for the system is introduced considering the effective parameters of the system, and then it is shown that chaos appears in the system by plotting phase plane of state-space variables. It should be noted that there is a great difference between random and chaotic behavior. In random cases, the model or input contains uncertainty, and therefore, the system behavior and output are not predictable. However, in chaotic behavior, there is only a brief uncertainty in the system model, input or initial conditions, and designing controller based on output prediction could be achieved. Therefore, model predictive control (MPC) algorithms are used to control the chaos, using the output prediction concept. In many cases, perturbation term also can be considered as uncertainty, and therefore, a robust controller family can be used for eliminating chaos. Both generalized predictive controller (GPC) and sliding mode controller (SMC) are used for chaos control here. The simulation results show the efficiency of the proposed algorithms.

Particle filter combined with data reconciliation for nonlinear state estimation with unknown initial conditions in nonlinear dynamic process systems

State estimation is very crucial for process control and optimization in dynamic processes. The particle filter (PF) is a novel and suitable technique for state estimation of nonlinear dynamic process systems. Conventional PFs for nonlinear dynamic process systems rely on the known initial conditions for state variables, such as the known probability density function (PDF) of initial states or the known values of initial states, but the initial conditions of a nonlinear dynamical system are usually unknown in actual industrial processes. In this paper, a novel methodology, PF combined with data reconciliation, is proposed and applied to nonlinear dynamic process systems for state estimation with unknown initial conditions. The measurement test criterion and data reconciliation with sequentially increasing data information are proposed to derive reliable initial values of the state variables under sufficient information of measurements. The interactive information between PF and data reconciliation problems can improve the initial values iteratively. Finally, accurate results of state estimation can be achieved. The effectiveness of the methodology is demonstrated through two nonlinear dynamic systems.

PREVENTION AND TREATMENT OF VENOUS THROMBOSIS AND THROMBOEMBOLISM IN SURGICAL TREATMENT PELVIC NEOPLASMS

Summary. Venous thromboembolic complications — a collective concept that combines thrombosis of the saphenous and deep veins, as well as pulmonary thromboembolism. In the clinical practice of a doctor of any specialty, especially surgical, the possibility of timely diagnosis, treatment and preventive measures for deep vein thrombosis and pulmonary embolism are extremely important.
 Purpose. To study the most informative measures for the prevention and treatment of venous thrombosis and thromboembolism in the surgical treatment of pelvic neoplasms.
 Materials and methods. The analysis of the results of the examination and treatment of 112 patients observed for tumors of the pelvic organs and tumors of the retroperitoneal space is presented.
 Results and discussion. When studying the initial state of the hemostasis system in 48 patients, a significant shortening of activated partial thromboplastin time (APTT), a 1.5-fold increase in the concentration of fibrinogen, which indicates activation of the procoagulant link, as well as an increase in platelet aggregation by 20.0 %, were established. Studies of the hemostatic system showed that surgical interventions and injuries contribute to increased hypercoagulation.
 Conclusions. The most informative methods for determining thrombosis in the system of the inferior vena cava and the optimal examination algorithm are: ultrasonic dynamic angioscanning, determination of the amount of D-dimer, computer, magnetic resonance bolus venography and retrograde ileocavagography.
 The use of unfractionated and low molecular weight heparins effectively prevents the development of thrombosis and thromboembolism before and after surgery and does not cause bleeding.
 Nonspecific and specific prophylaxis of venous thrombosis and embolism allowed a 2.8-fold reduction in their number in patients of the main group.

Quantum reversibility in cooperative interaction of the atom system with bi-modal cavity field in Raman conversion

The restoration of the initial state in the Raman interaction of the two atoms with the quantified pump and Stokes (anti-Stokes) cavity modes is analytically obtained. For this the su (2) symmetry representation of the bimodal field and a system of two atoms in scattering interaction is proposed for the simplification of the problem. Using the proprieties of the generators su (2) algebra the exact non-stationary solution of the system of two atoms in interaction with the bimodal field is found, taking into consideration the initial disentangled state between the atomic and field superposition. It is demonstrated that after this collapse and revivals of the inversion of flying atoms in the processes of absorption and emission of the photons from Stokes and pump modes the system atoms and field becomes entangled. The conditions of the restoration of the initial state of the atom-field system were established as a function of the flying time through the resonator possible. A set of discrete flying time intervals for the restoration of the initial disentangled state was found.

Quantum scheme for N-level atom interacting with a two two-level atom: Atomic Fisher information and entropy squeezing

In this work, we introduce a model of a two-atom interacting with a multi-level atom governed by su(2) Lie algebra in the presence of external classical field. The influence of the classical field on the system is discussed in detail for certain values for the classical terms. The atomic density matrix of the proposed system is obtained. The dynamical behavior of the atomic Fisher information as an indicator of the nonlocal correlation between a two-atom and su(2) field is discussed. Moreover, we examine the effect of classical field on the evolution of entropy squeezing and the geometric phase induced between the initial and final state of the proposed system. The results outlined some important phenomena as sudden death and sudden birth of entanglement in presence of the classical terms is observed through the dynamics of atomic Fisher information in the presence of classical field for the large number of levels.

Geometric phase corrected by initial system-environment correlations

We find the geometric phase of a two-level system undergoing pure dephasing via interaction with an arbitrary environment, taking into account the effect of the initial system-environment correlations. We use our formalism to calculate the geometric phase for the two-level system in the presence of both harmonic oscillator and spin environments, and we consider the initial state of the two-level system to be prepared by a projective measurement or a unitary operation. The geometric phase is evaluated for a variety of parameters such as the system-environment coupling strength to show that the initial correlations can affect the geometric phase very significantly even for weak and moderate system-environment coupling strengths. Moreover, the correction to the geometric phase due to the system-environment coupling generally becomes smaller (and can even be zero) if initial system-environment correlations are taken into account, thus implying that the system-environment correlations can increase the robustness of the geometric phase.

Entanglement Control of Two-Level Atoms in Dissipative Cavities

An open quantum bipartite system consisting of two independent two-level atoms interacting nonlinearly with a two-mode electromagnetic cavity field is investigated by proposing a suitable non-Hermitian generalization of the Hamiltonian. The mathematical procedure of obtaining the corresponding wave function of the system is clearly given. Pancharatnam phase is studied to give a precise information about the required initial system state, which is related to artificial phase jumps, to control the degree of entanglement (DEM) and get the highest concurrence. We discuss the effect of time-variation coupling, and dissipation of both atoms and cavity. The effect of the time-variation function appears as frequency modulation (FM) effect in the radio waves. Concurrence rapidly reaches the disentangled state (death of entanglement) by increasing the effect of field decay. On the contrary, the atomic decay has no effect.

Dynamics of non-equilibrium thermal quantum correlation in a two-qubit Heisenberg XYZ model

The non-equilibrium thermal entanglement and quantum discord in a two-qubit Heisenberg XYZ model subjected to two thermal baths with different temperatures are investigated. The dynamical behaviors of entanglement and quantum discord under the influences of the initial states of the two-qubit system, the temperature of the thermal baths and the coupling constant $$J_z$$ are discussed. A special emphasis is devoted to study the effects of the thermal baths on the steady quantum correlation between the two qubits. Our results show that the temperature difference $$\Delta T$$ plays a key role for the appearance of steady quantum correlation, which can be enhanced by coupling constant $$J_z$$, DM interaction and non-uniform magnetic field.

Quantum dynamics of a driven damped harmonic oscillator in Heisenberg picture: exact results and possible generalizations

In the framework of the Heisenberg picture, an alternative derivation of the reduced density matrix of a driven dissipative quantum harmonic oscillator as the prototype of an open quantum system is investigated. The reduced density matrix for different initial states of the combined system is obtained from a general formula, and different limiting cases are studied. Exact expressions for the corresponding characteristic function in quantum thermodynamics and Wigner quasi-distribution function are found. A possible generalization based on the Magnus expansion of the evolution operator is presented.

Using Sliding Mode Controller and Eligibility Traces for Controlling the Blood Glucose in Diabetic Patients at the Presence of Fault

Some people suffering from diabetes use insulin injection pumps to control the blood glucose level. Sometimes, the fault may occur in the sensor or actuator of these pumps. The main objective of this paper is controlling the blood glucose level at the desired level and fault-tolerant control of these injection pumps. To this end, the eligibility traces algorithm is combined with the sliding mode control. The eligibility traces algorithm is one of the newest solving methods of the Reinforcement Learning approach. The major disadvantage of the sliding mode control method is the chattering phenomenon. In this paper, the novel idea is the combination of these methods to remove the chattering phenomena in simulation results. To demonstrate the superiority of the proposed method, it is compared with another combinatory method that is the sliding mode control and Artificial Neural Networks. Simulation results reveal that the combination of the eligibility traces algorithm and the sliding mode control can control the blood glucose level and insulin with a higher speed and bring them to the desired level, even in the case the sensor and actuator faults are present in the system. When the proposed hybrid method is used, the injected dosage of the drug is lower, which will result in reduced side effects. Finally, the noise, as well as the uncertainty in system parameters and initial conditions are applied to the system to investigate the performance of the proposed controller, under the faulty condition.

Predictors of the development of cardiac arrhythmias in women after induction of superovulation in vitro fertilization

The article presents the results of a clinical and instrumental examination of 80 healthy women (average age 32,313,57 years) in order to assess the heart rhythm disturbances after induction of superovulation duringin vitrofertilization. All women were examined twice before and after induction of superovulation during extracorporeal fertilization. Clinical and instrumental examination included: electrocardiography at rest; echocardiography; 24-hour ECG monitoring with heart rate variability analysis; 24-hour blood pressure monitoring. Induction of superovulation is associated with a significant increase in mean daily HR max (р0,01), and consequently with an increase in myocardial oxygen demand. It has been established that induction of superovulation contributes to the development of supraventricular arrhythmias (р0,01) and an increase in episodes of apnea/hypnea (р0,01). Regression analysis revealed predictors of supraventricular arrhythmias after induction of superovulation, including adverse circadian heart rate profile, adverse circadian blood pressure profile, impaired autonomic regulation of heart activity (р0,01). It was shown that the appearance of rhythm disturbances is associated with both the initial functional state of the cardiovascular system and its response to the induction of superovulation. It was established a correlation between the estradiol concentration and the increase of daily average heart rate after induction of superovulation (r=0,30,р0,05), apnea/hypnea index after induction of superovulation (r=0,34,р0,05). Conclusion. Superovulation induction may exacerbate existing chronic cardiovascular diseases. Due to the adverse effect of superovulation induction on the daily heart rate profile, women need to evaluate the functional state of the cardiovascular system duringinvitrofertilization planning. This will prepare the woman for the upcoming procedure and avoid adverse reactions from the cardiovascular system in response to stimulation of superovulationin vitrofertilization.

Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation

Abstract. Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.

Entanglement dynamics for quantum emitters strongly coupled with molybdenum disulfide nanodisks

We study the dynamics of entanglement for a composite two-qubit system, where each qubit is close to a molybdenum disulfide nanodisk, by combining quantum dynamics and classical electromagnetic calculations. We assume that each qubit interacts locally with its own photonic environment and its free-space decay time is in the picosecond regime. We observe non-Markovian entanglement dynamics indicating strong light-matter interaction between the qubits and the photonic reservoirs. We investigate the entanglement dynamics using entanglement of formation as a measure of entanglement by varying the initial state of the composite system, which always remains an extended Werner-like state, the transition frequency and the orientation of the transition dipole moment of each qubit, the radius of the molybdenum disulfide nanodisk, and the distance of a qubit from its corresponding nanodisk. For several values of the above parameters, we observe interesting phenomena during the time evolution of entanglement of formation, such as entanglement sudden death, revival of entanglement and entanglement trapping. • The entanglement dynamics of two initially entangled quantum emitters next to MoS 2 nanodisks is analyzed. • The results are obtained by combining quantum dynamics calculations with electromagnetic calculations. • Non-Markovian entanglement dynamics is obtained. • Entanglement sudden death, revival of entanglement and entanglement trapping are found for different system parameters. • The effects of the electric dipole orientation of the quantum emitter are also analyzed.

Solving systems of linear algebraic equations via unitary transformations on quantum processor of IBM Quantum Experience

We propose a protocol for solving systems of linear algebraic equations via quantum mechanical methods using the minimal number of qubits. We show that $(M+1)$-qubit system is enough to solve a system of $M$ equations for one of the variables leaving other variables unknown provided that the matrix of a linear system satisfies certain conditions. In this case, the vector of input data (the rhs of a linear system) is encoded into the initial state of the quantum system. This protocol is realized on the 5-qubit superconducting quantum processor of IBM Quantum Experience for particular linear systems of three equations. We also show that the solution of a linear algebraic system can be obtained as the result of a natural evolution of an inhomogeneous spin-1/2 chain in an inhomogeneous external magnetic field with the input data encoded into the initial state of this chain. For instance, using such evolution in a 4-spin chain we solve a system of three equations.

Configuring tasks as constraints for coordinated mechanical systems: A Udwadia–Kalaba theory based adaptive robust control

In this paper, we deal with the control problem of coordinated mechanical systems by configuring the control tasks as servo constraints. For the nominal systems, a Udwadia–Kalaba control scheme is implemented. In the presence of system uncertainties and initial condition deviations from the servo constraints, an adaptive robust control scheme is designed and proved to be able to guarantee the deterministic performance: uniform boundedness and uniform ultimate boundedness. The leakage-type and performance-based adaptive law contains two specific terms, with the first term to compensate the uncertainty and the second term to prevent the control magnitude to be too excessive. The developed scheme is able to deal with both holonomic constraints and nonholonomic constraints, which makes it have a wide range of applications. An example of coordinated robotic manipulators with two individual subsystems is given to demonstrate effectiveness of the proposed adaptive robust control methodology.

Structural Decomposition Approach to Design of No-Wait Cyclic Schedules for Repeatedly Operating Transport System Dedicated to Supply Loops

Abstract The paper presents a method allowing to construct no-wait cyclical schedules for repetitive transport systems (e.g. the milk-run) servicing cyclic material supply loops in the production system using selected means of transport (e.g. AGVs). The transport means are following established routes and given arrival times. The routes are composed of sectors linking workstations. Transport trolleys may share specific sectors of the route in mutual exclusion mode and must wait in a given sector to enter the next sector of the route when another trolley occupies it. The job-shop repetitive transportation system is a system of cyclic processes with a fixed structure that are executing sequences of operations (routes) using shared resources (sectors). The work aims to find a no-wait cyclic schedule that guarantees the required delivery dates or establish that such a schedule does not exist. It considers cyclic process systems for which each resource can be used by at most two operations, and the deadlock state cannot occur as a result of waiting processes on shared resources. For specified initial operations of cyclic processes and their start times (the initial system state), the problem of determining no-wait cyclical schedules decomposes into subproblems. Each subproblem consists of the verification of necessary and sufficient conditions for the existence of solutions for each of 2-process subsystems composed of one shared resource and two processes using this resource. The method aims of prototyping various variants of process starting times for which the conditions guaranteeing no-wait property of the system hold simultaneously for each of the 2-process subsystems. It allows designing cyclic schedules for complex systems composed of 2-process subsystems that are structurally deadlock-free. The class of cyclical processes considered in this article is broader than the class of cascade-like (chain-like, sequential) process systems analysed so far in the literature. In this context, the results obtained are an extension of the existing ones.

Operating Reliability Evaluation of Power Systems With Demand-Side Resources Considering Cyber Malfunctions

Demand-side resources (DSRs) have been shown to be valuable for providing reserve capacity and enhancing the reliability of power systems with high wind power penetration. The successful utilization of DSRs relies heavily upon the infrastructure of advanced information and communication technologies (ICTs). Notably, ICT systems may suffer from cyber attacks and communication latency, which could result in the malfunctions of DSRs and consequently bring adverse impacts on the reliability of power systems. In this paper, a novel operating reliability evaluation framework for multi-state power systems with DSRs and wind power considering malfunctions of cyber systems is proposed. For avoiding increasing complexity caused by multiple system states, an analytic method based on Lz transform technique is proposed to achieve dynamic system reliability. The reliability model for a typical hierarchical decentralized control infrastructure in demand side considering cyber attacks and communication latency is first proposed. Then, reserve capacity from DSRs considering stochastic behavior under the cyber infrastructure is modelled. Moreover, multi-state models for power generation systems with stochastic wind power and conventional generation are developed considering cyber malfunctions. Reliability indices based on load curtailment by conducting optimal power flow for various system states are utilized for reliability assessment. A modified IEEE RTS with four cases is adopted to validate the proposed model and method, which denotes that reserve capacity from DSRs can definitely enhance system operating reliability and affected by proportions of DSRs, consideration of cyber malfunctions, actual committed time for DSRs and initial system conditions.

Quasi-Integral-Input-to-State Stability for Switched Nonlinear Systems

Abstract In this paper we introduce and give sufficient conditions for the quasi-iISS property for switched nonlinear systems under dwell-time switching signals. Unlike previous works, our dwell-time bound does not rely on the knowledge of the state but it relies only on the system initial condition and the bound on the input energy. We prove, through a counterexample, that knowledge of the system initial state and bound on input energy is necessary for the estimation of a dwell-time that guarantees quasi-iISS for the switched system. An illustrative example is also included.

Color Image Compression-Encryption Using Fractional-Order Hyperchaotic System and DNA Coding

Recently, many encryption algorithms based on fractional-order chaotic system have been proposed to solve the problem of image encryption. In this paper, we propose a novel color image compression-encryption algorithm based on fractional-order hyperchaotic system and DNA coding. In the data compression stage, the data of R, G, and B channels of the color image are converted to the frequency domain by two-dimensional discrete cosine transform (DCT), and then the amount of encrypted data is reduced by the quantization process. We design a data processing algorithm to ensure that the data after DCT is compatible with DNA coding data format. In the encryption stage, the processes of DNA encoding and decoding, DNA operation, and pixel scrambling are all controlled by the corresponding chaotic sequences, which are generated by the chaotic system. The original image is used to calculate the initial state of the chaotic system, which improves the performance of the algorithm against the chosen-plaintext attack significantly. Experimental results and security analysis illustrate that the proposed algorithm has excellent compression and security performance. It can not only reconstruct the original image well under the condition of low compression ratio, but also provide high security to resist various attacks. Besides, experimental results also indicate that the algorithm proposed can be applied to the fields of color image compression, encryption, and transmission.

Structural Results for Average‐Cost Inventory Models with Markov‐Modulated Demand and Partial Information

We consider a discrete‐time infinite‐horizon inventory system with non‐stationary demand, full backlogging, and deterministic replenishment lead time. Demand arrives according to a probability distribution conditional on the state of the world that undergoes Markovian transitions over time. But the actual state of the world can only be imperfectly estimated based on past demand data. We model the inventory replenishment problem for this system as a Markov decision process (MDP) with an uncountable state space consisting of both the inventory position and the most recent belief, a conditional probability mass function, about the actual state of the world. Assuming that the state of the world evolves as an ergodic Markov chain, using the vanishing discount method along with a coupling argument, we prove the existence of an optimal average cost that is independent of the initial system state. For our linear cost structure, we also establish the average‐cost optimality of a belief‐dependent base‐stock policy. We then discretize the uncountable belief space into a regular grid and observe that the average cost under our discretization converges to the optimal average cost as the number of grid points grows large. Finally, we conduct numerical experiments to evaluate the use of a myopic belief‐dependent base‐stock policy as a heuristic for our MDP with the uncountable state space. On a test bed of 108 instances, the average cost obtained from the myopic policy deviates by no more than a few percent from the best lower bound on the optimal average cost obtained from our discretization.