Steady-state Performance Indices Research Articles

Availability and cost-benefit evaluation for a repairable retrial system with warm standbys and priority

This paper investigates a warm standby repairable retrial system with two types of components and a single repairman, where type 1 components have priority over type 2 in use. Failure and repair times for each type of component are assumed to be exponential distributions. The retrial feature is considered and the retrial time of each failed component is exponentially distributed. By using Markov process theory and matrix-analytic method, the system steady-state probabilities are derived, and the system steady-state availability and some steady-state performance indices are obtained. Using the Bayesian approach, the system parameters can be estimated. The cost-benefit ratio function of the system is constructed based on the failed components and repairman's states. Numerical experiments are given to evaluate the effect of each parameter on the system steady-state availability and optimize the system cost-benefit ratio with repair rate as a decision variable.

Design and Analysis of Zeta Converter for Power Factor Correction Using Cascade PSO-GSA-Tuned PI and Reduced-Order SMC

This paper presents the design and analysis of a single-phase power factor correction (PFC) scheme using a DC–DC Zeta converter operating in continuous conduction mode. The presented DC–DC converter exhibits non-linearity due to switching elements that degrades the performance of the converter. Therefore, this paper proposes a non-linear cascade control of particle swarm optimization-gravitational search algorithm (PSO-GSA) tuned proportional-integral (PI) and sliding mode controller (SMC) in outer and inner loop, respectively, to improve the performance of the converter. The robustness of the controller is analysed by applying the load and line variations to the converter. The simulation results showed that the steady state performance indices such as integral absolute error and integral square error, and transient performance indices like settling time and peak overshoot are significantly enhanced for the proposed cascade control scheme compared to the PSO and root locus method of tuning the outer PI with the inner SMC controller. The proposed control scheme gives better performance in terms of power factor improvement, percentage reduction in total harmonic distortion, and efficient tracking of output voltage for change in reference voltage compared to other techniques presented. Further, the performance of the proposed scheme is tested for battery charging application of the solar photovoltaic system. The demonstrated simulation results are validated by implementing the DC–DC Zeta converter in real-time hardware set-up.

Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization

This paper proposes an improved form of chaotic based atom search optimization (IASO) algorithm by adapting one-dimensional (1D) chaotic map (tent, sine and logistic) to improve the search ability by intensifying the exploration and exploitation phase. The IASO avoids premature convergence and trapping into local optima. Initially, the proposed IASO is validated using a classical benchmark function and its performance is compared with ASO algorithm. Test results indicate that the proposed algorithm outperforms in terms of mean, standard deviation, and best values. Further, the proposed technique is used to design the parameters of fractional-order proportional integral derivative controller for automatic load frequency control (ALFC) of multi-area, multi-source hybrid power system (HPS) by minimizing the integral time absolute error. The results obtained show that the proposed control scheme improves the frequency response of the system by 48 %, 70 %, 15 % and 69 % in terms of settling time, peak undershoot, steady state error value and control effort, respectively compared to ASO. Moreover, the sensitivity analysis is carried out by considering ±25 % variation in HPS parameters and the real-time applicability is tested with Malaysian meteorological data of solar radiation and wind speed variation. These analysis indicates that the transient oscillations are damped out with minimum settling time and the system regains to stable operating conditions. Further, the evaluation of transient and steady-state performance indices shows that the tent map-based IASO is found to be more efficient for obtaining the optimal solution in solving the ALFC problems. In addition, the stability of the system is analysed by approximating the fractional-order transfer function based on the oustaloup filter in frequency domain.

Blind Source Separation Method Based on Neural Network with Bias Term and Maximum Likelihood Estimation Criterion.

Convergence speed and steady-state source separation performance are crucial for enable engineering applications of blind source separation methods. The modification of the loss function of the blind source separation algorithm and optimization of the algorithm to improve its performance from the perspective of neural networks (NNs) is a novel concept. In this paper, a blind source separation method, combining the maximum likelihood estimation criterion and an NN with a bias term, is proposed. The method adds L2 regularization terms for weights and biases to the loss function to improve the steady-state performance and designs a novel optimization algorithm with a dual acceleration strategy to improve the convergence speed of the algorithm. The dual acceleration strategy of the proposed optimization algorithm smooths and speeds up the originally steep, slow gradient descent in the parameter space. Compared with competing algorithms, this strategy improves the convergence speed of the algorithm by four times and the steady-state performance index by 96%. In addition, to verify the source separation performance of the algorithm more comprehensively, the simulation data with prior knowledge and the measured data without prior knowledge are used to verify the separation performance. Both simulation results and validation results based on measured data indicate that the new algorithm not only has better convergence and steady-state performance than conventional algorithms, but it is also more suitable for engineering applications.

Rotor-dynamic performance of porous hydrostatic thrust bearing operating under magnetic field

Purpose The porous bearings are commonly used in slider thrust bearings owing to their self-lubricating properties and cost effectiveness as compared to conventional hydrodynamic bearings. The purpose of this paper is to numerically investigate usefulness of porous layer in hydrostatic thrust bearing operating with magnetic fluid. The effect of magnetic field and permeability has been analysed on steady-state (film pressure, film reaction and lubricant flow rate) and rotor-dynamic (stiffness and damping) parameters of bearing. Design/methodology/approach Finite element approach is used to obtain numerical solution of flow governing equations (Magneto-hydrodynamics Reynolds equation, Darcy law and capillary equation) for computing abovementioned performance indices. Finite element method formulation converts elliptical Reynolds equation into set of algebraic equation that are solved using Gauss–Seidel method. Findings It has been reported that porosity has limited but adverse effects on performance parameters of bearing. The adverse effects of porosity can be minimized by using a circular pocket for achieving better steady-state response and an annular/elliptical pocket, for having better rotor-dynamic response. The use of magnetic fluid is found to be substantially enhancing the fluid film reaction (53%) and damping parameters (55%). Practical implications The present work recommends use of circular pocket for achieving better steady-state performance indices. However, annular and elliptical pockets should be preferred, when design criteria for the bearing are better rotor-dynamic performance. Originality/value This study deals with influence of magnetic fluid, porosity and pocket shape on rotor-dynamic performance of externally pressurized thrust bearing. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0289/

Design of a nonsingular adaptive fuzzy backstepping controller for electrostatically actuated microplates

This paper adopts some alternative strategies to design a nonlinear controller for double electrostatically actuated microplates. The novel design is carried out to solve the singularity problem reported in many articles due to the use of the Taylor expansion to simplify the electrostatic force. The nonlinear governing partial differential equation is converted to the modal equation using the Galerkin method. Then, based on the Lyapunov stability criterion, a fuzzy backstepping controller facilitated by prescribed performance functions is applied to the non-affine system to extend the travel range beyond the pull-in region and capture the structural and nonstructural uncertainties that exist in the practical systems. The present work also aims to bring satisfactory transient and steady-state performance indices to the system. Moreover, unknown time-varying delays as the indispensable part of practical systems are considered in the proposed control scheme to suppress the delays occurring in the measurement of the states by constructing Lyapunov–Krasovskii function. The accuracy of the modal equation in both the static and dynamic analysis is verified through a meshless method as a direct solution of the partial differential equation. The proposed controller guarantees that all the closed-loop signals are semi-globally, uniformly ultimately bounded, and the error evolves within the decaying prescribed bounds. Finally, the proposed controller demonstrates its feasibility to extend the travel range within and beyond the pull-in range despite the unknown uncertainties and time-varying delays which exist in the system.

Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller

This paper proposes a new population-based hybrid particle swarm optimized-gravitational search algorithm (PSO-GSA) for tuning the parameters of the proportional-integral-derivative (PID) controller of a two-area interconnected dynamic power system with the presence of nonlinearities such as generator rate constraints (GRC) and governor dead-band (GDB). The tuning of controller parameters such as Kp, Ki, and Kd are obtained by minimizing the objective function formulated using the steady-state performance indices like Integral absolute error (IAE) of tie-line power and frequency deviation of interconnected system. To test the robustness of the propounded controller, the system is studied with system uncertainties, such as change in load demand, synchronizing power coefficient and inertia constant. The two-area interconnected power system (TAIPS) is modeled and simulated using Matlab/Simulink. The results exhibit that the steady-state and transient performance indices such as IAE, settling time, and control effort are impressively enhanced by an amount of 87.65%, 15.39%, and 91.17% in area-1 and 86.46%, 41.35%, and 91.04% in area-2, respectively, by the proposed method compared to other techniques presented. The minimum control effort of PSO-GSA-tuned PID controller depicts the robust performance of the controller compared to other non-meta-heuristic and meta-heuristic methods presented. The proffered method is also validated using the hardware-in-the-loop (HIL) real-time digital simulation to study the effectiveness of the controller.

Performance Analysis of PI and SMC Controlled Zeta Converter

This paper presents the design and analysis of DC-DC Zeta converter operating in the continuous conduction mode to regulate the output voltage of the converter for automotive battery recharge applications. The state space analysis of the converter is derived to obtain the transfer function of the converter. The presented DC-DC converter exhibits the non-linearity due to the presence of energy storage elements and degrades the performance of the converter. Therefore, this paper proposes a non-linear cascaded Proportional -Integral Sliding Mode Controller (PI-SMC) to improve the performance of the converter. PI-SMC Controller contains PI Controller in the outer loop for voltage regulation and an inner fast acting SMC Controller for current shaping. The PI controller is tuned by Root locus and Routh Hurwitz criterion and the steady state performance parameters are obtained for the PI-SMC Controlled Zeta converter. MATLAB/SIMULINK results are presented for Set point tracking of the controller. The results shows that the steady state performance indices such as Integral Absolute Error (IAE) and Integral Time Absolute Error (ITE) are significantly enhanced for the converter using the proposed cascaded control scheme compared to the conventional PI controller.

Design and analysis of hybrid PSO–GSA tuned PI and SMC controller for DC–DC Cuk converter

In this Letter, a hybrid particle swarm optimisation and gravitational search algorithm (PSO–GSA) to tune the parameters of proportional–integral (PI) controller operating in cascade with sliding mode controller (SMC) is proposed for the design of Cuk converter for low-voltage electric vehicle application. The PI controller in the outer loop regulates the voltage and SMC in the inner loop regulates the current of converter operating in continuous conduction mode. The main objective of Cuk converter with PSO–GSA tuned PI & SMC controller is to track the reference voltage amidst disturbances, and to reduce the performance indices such as integral absolute error (IAE) and integral time absolute error. Initially, PI controller was tuned using Routh Hurwitz and root locus method. Then to improve its steady-state performance index, PSO–GSA technique is applied to tune the proportional and integral gains. To validate the effectiveness of the proposed scheme, the performance indices such as IAE, integral squared error was measured and compared. The results obtained reveal that IAE is reduced to minimal value and the solution converges at a faster rate with the proposed controller than the conventional control methods. Moreover, the stability analysis was carried out using the Lyapunov method of stability.

Steady-State Performance Analysis of Tracking Filter Using LFM Waveforms and Range-Rate Measurement

The steady-state performance of a moving-object tracking filter is theoretically analyzed, assuming the simultaneous measurement of the range and range-rate (RRM system), and the use of linear frequency modulated (LFM) waveforms (RRM-LFM filter). An efficient analytical steady-state performance index, called an RMS index, is derived for the RRM-LFM filter to clarify the steady-state range prediction errors, theoretically. Using the derived RMS index, the optimal performance of the RRM-LFM filter is analyzed. The performance variation due to the use of LFM waveforms is clarified for the RRM tracking system. The theoretical performance analysis verifies that the measured range-rate significantly improves the tracking accuracy, compared to the conventional range-only measuring LFM tracking filter. Furthermore, the quantitative relationships among the measurement accuracy, degree of target maneuvering, and steady-state range prediction errors are clarified to validate the effectiveness of the RRM-LFM filter.

Design of Accurate α-β Tracker based on Steady-State Performance Index

Design of Accurate α-β Tracker based on Steady-State Performance Index

Automatic Parameter Setting Method for an Accurate Kalman Filter Tracker Using an Analytical Steady-State Performance Index

We present an automatic parameter setting method to achieve an accurate second-order Kalman filter tracker based on a steady-state performance index. First, we propose an efficient steady-state performance index that corresponds to the root-mean-square (rms) prediction error in tracking. We then derive an analytical relationship between the proposed performance index and the generalized error covariance matrix of the process noise, for which the automatic determination using the derived relationship is presented. The model calculated by the proposed method achieves better accuracy than the conventional empirical model of process noise. Numerical analysis and simulations demonstrate the effectiveness of the proposed method for targets with accelerating motion. The rms prediction error of the tracker designed by the proposed method is 63.8% of that with the conventional empirically selected model for a target accelerating at 10 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Simulation Research of CVT Variable Fertilization Control System

Using MATLAB to establish emulation model of variable rate fertilization control system, using the Z-N method to setting the system of PID parameters, emulation of the system has without PID controller and PID controller, analysis and evaluation of the system dynamic performance index and steady-state performance index. The emulation results shows that the system with PID controller, the maximum overshoot reduce, adjusting time short, improve the time domain dynamic index; phase margin increase, magnitude increase, improved the performance index of the frequency domain.

Modeling and Parametric Design of Permanent-Magnet AC Machines Using Computationally Efficient Finite-Element Analysis

Computationally efficient finite-element analysis (FEA) (CE-FEA) fully exploits the symmetries of electric and magnetic circuits of sine-wave current-regulated synchronous machines and yields substantial savings of computational efforts. Motor performance is evaluated through Fourier analysis and a minimum number of magnetostatic solutions. The major steady-state performance indices (average torque, ripple and cogging torque, back-electromotive-force waveforms, and core losses) are satisfactorily estimated as compared with the results of detailed time-stepping (transient) FEA. In this paper, the CE-FEA method is presented and applied to a parametric design study for an interior-permanent-magnet machine. Significant reduction of simulation times is achieved (approximately two orders of magnitude), permitting a comprehensive search of large design spaces for optimization purposes. In this case study, the influence of three design variables, namely, stator tooth width, pole arc, and slot opening, on three performance indices, namely, average torque, efficiency, and full-load torque ripple, is examined, and design trends are derived. One hundred candidate designs are simulated in less than 20 minutes on a state-of-the-art workstation.

Colored stochastic Petri nets for modelling and analysis of multiclass retrial systems

Most retrial models assume that customers and servers are homogeneous. However, multiclass (or heterogeneous) retrial systems arise in various practical areas such as telecommunications and cellular mobile networks. Multiclass models are far more difficult for mathematical analysis than single class ones. So, explicit results are available only in few special cases. Actually, so far multiclass retrial systems have been analyzed only by means of queueing theory and almost all studies consider models with several customer’s classes and a service station consisting in one single server or multiple homogeneous (identic) servers and an infinite population size. In this paper, we propose an approach for modelling and analyzing finite-source retrial systems with several customer’s classes and server’s classes using the Colored Generalized Stochastic Petri Nets (CGSPNs). This high-level mathematical model is appropriate for describing and analyzing the performance of systems exhibiting concurrency and synchronization, possibly with heterogeneous components. Using a high-level formalism makes the description of the system easier, while preserving the possibility of obtaining exact performance results. We show how the main steady-state performance indices can be derived and we analyze the behaviour of heterogeneous retrial systems under two service disciplines. The numerical results are graphically displayed to illustrate the effect of system parameters and service discipline on the mean response time.

A Simplified Dynamic Model for Chilled-Water Cooling and Dehumidifying Coils—Part 1: Development (RP-1194)

Dynamic coil models are useful in the development and evaluation of feedback controllers and fault detection and diagnostics algorithms. Existing models in the literature have not been validated fully using experimental data and have not been evaluated in terms of trade-offs between model accuracy and computational requirements. This paper develops a computationally fast, distributed model for the transient behavior of cooling and dehumidifying coils. The model utilizes several steady-state performance indices that simplify dynamic modeling, including fin efficiency, air-side effectiveness, and water-side effectiveness. Predictions from the simplified model were compared with a detailed reference model and with other simplified models from the literature. Comparisons with detailed experimental measurements are given in a companion paper (Zhou and Braun 2007). The model provides very accurate predictions of coil transient performance and executes more than 1000 times faster than real-time on a 1.2 GHz personal computer. As a result, it is very practical for implementation within system simulation programs that execute over long time periods, such as a year.

Fluidic Control of a Hydrostatic Transmission in a Vehicle Propulsion System

A vehicle propulsion system is considered which consists of an engine, hydrostatic transmission, and automatic controller. Control requirements are established for optimum or near optimum operation based on a steady-state performance index. Various controller classes are identified and a systematic method for synthesis of the “best” controller is outlined. A unique fluidic controller is discussed which adjusts the transmission ratio to maintain a specified engine speed-engine load relationship which maximizes overall system efficiency for a wide range of external load conditions.