Proposed Performance Criterion Research Articles

An improved approach to synthesis of Markov jump nonlinear systems with generally uncertain transition rates

AbstractThis paper concentrates on state‐feedback control problem for a kind of Markov jump nonlinear systems with generally uncertain transition rates. The nonlinearity satisfies the sector condition, which is more generic than the ordinary Lipschitz nonlinearity. First, a performance criterion is derived for the closed‐loop systems. Next, based on the proposed performance criterion and a judicious method of using inequalities, a novel controller synthesis method is developed in terms of linear matrix inequalities. Compared with the existing result, the proposed method significantly reduces the conservativeness of the controller synthesis. Finally, a numerical example is provided to show the validity and merit of the developed result.

Integrated assessment of the efficiency of the development of the national of the economic system of the republic of belarus from the position of households

The article proposes a criterion for evaluating the effectiveness of the development of the national economic system of the Republic of Belarus from the perspective of households using a dynamic system of indicators, which allows for an integral assessment of the effectiveness of purposeful activities in dynamics and taking into account the development trends of the country's economy, as well as a reasonable approach to the development of mechanisms for achieving the set goals. development goals in accordance with the proposed performance criterion. The effectiveness of the development of the national economic system of the Republic of Belarus was assessed from the perspective of households for 2016– 2020. On the basis of the proposed efficiency criterion, the directions for achieving the goals of development of subjects of economic relations and the national economic system of the Republic of Belarus are determined.

GENERALIZED CRITERIA FOR LOADING CAPACITY OF INDUSTRIAL ROBOTS

The analysis of the correspondence of the set of functional indicators of industrial robots to the criteria of criteria similarity conditions is carried out. Using the methods of the theory of dimensions, criteria for the similarity of the functional properties of carrying capacity, speed-action and dynamism of industrial robots in terms of rotational and translational degrees of mobility have been determined. The necessary set of criteria has been created and a concept has been proposed for determining the generalized criterion complexes of the load capacity for modules, aggregates and the entire structure of the robot as a whole using the method of defragmentation and averaging the corresponding criteria by degrees of mobility. The proposed performance criterion makes it possible to compare the performance of a group of robots in terms of three kinematic indicators: speed, acceleration and the range of permissible displacements. For robots of light load capacity, the technical evolution of the considered criterion complexes is presented. It is noticed that with an increase in the reach of the robot, the criterion of load-carrying capacity for all robots decreases. The developed criteria make it possible to assess the speed action and loading capacity of a robot of any design and can be used to determine the technical level of robots and identify reserves for increasing it. Key words: degrees of mobility; manipulation system; homogeneous functions; dynamic parameters

Improved Accuracy of Automated Estimation of Cardiac Output Using Circulation Time in Patients with Heart Failure

BackgroundLung-to-finger circulation time of oxygenated blood during nocturnal periodic breathing in heart failure patients measured using polysomnography correlates negatively with cardiac function but possesses limited accuracy for cardiac output (CO) estimation. Methods and ResultsCO was recalculated from lung-to-finger circulation time using a multivariable linear model with information on age and average overnight heart rate in 25 patients who underwent evaluation of heart failure. The multivariable model decreased the percentage error to 22.3% relative to invasive CO measured during cardiac catheterization. ConclusionsThis improved automated noninvasive CO estimation using multiple variables meets a recently proposed performance criterion for clinical acceptability of noninvasive CO estimation, and compares very favorably with other available methods.

A new multiobjective performance criterion used in PID tuning optimization algorithms

In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions.

Comparative analysis and prediction study for effluent gas emissions in a coal-fired thermal power plant using artificial intelligence and statistical tools

Environmental sustainability is a crucial phenomenon for daily human life & planet earth, where various plants influence a massive impact to atmosphere as a drawback of the industrial revolutions. The worldwide regulations imposes various improvements in existing coal-fired thermal power plants by means of implementing emission reduction systems, desulphurization, de-NOx systems, modernization of instrumentation, sensors and automation control systems, co-firing process, efficiency enhancements, etc. which cause high investment impact to the plants. Therefore if relevant variables those affecting emission rates are selected, and the emission measures are predicted and controlled properly, then it will be beneficial to implement emission reduction scheme to the plant accordingly. In this research, effluent gas emissions of a 180 MW coal-fired thermal power plant located in Kocaeli, Turkey is modelled and predicted using Artificial Neural Networks (ANN), Autoregressive Integrated Moving Average (ARIMA) and Multiple Linear Regression (MLR) approaches within proposed process parameters. The data is collected from the consolidated continuous emission monitoring system reports during 1 month of operation, and proposed performance criterion, regression coefficient and root mean squared error, is used for comparison of the model outputs. Prediction results are found satisfactory and encouraging in order to integrate the models to the power plant automation systems as an expert system.

A robust decentralized control method based on dimensionless parameters with practical performance criterion for building structures under seismic excitations

SUMMARY A robust and decentralized control method for reducing vibration in a building, based on the Lyapunov-control function, is proposed and investigated. A new parameter that gives flexibility to the control design is introduced, and the control law is expressed in terms of dimensionless parameters. In addition, an expression adapted for semi-active control of which feedback gain is finite is proposed for a particular case. Analytical proof of the performance is completely derived for a system in which the control distribution matrix is not singular and a practical performance criterion is obtained. The influence of each parameter, along with the validity of the proposed performance criterion and the robustness to the uncertainties in the structural parameters, is extensively discussed with a single-degree-of-freedom numerical example. The performance of a decentralized system and the controller design in the case where the control distribution matrix is singular are discussed with a two-degree-of-freedom numerical application. A shaking table experiment using a small-scale model of a high-rise building with a vibration control device is conducted to verify the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.

비-가우시안 잡음하의 통신을 위한 바이어스된 오차 분포의 유클리드 거리

비-가우시안 잡음 환경의 적응 시스템을 위해, 평행 이동한 오차 분포와 오차 0에 위치한 델타 함수 사이의 유클리드 거리를 새로운 성능기준으로 제안하였다. 또한, 이 성능 기준에 근거하여 적응 알고리듬을 개발하였고, 얕은 바다에서 구한 수중 통신 다경로 채널에 충격성 잡음과 직류 바이어스 잡음이 더해진 환경으로 등화 성능을 시뮬레이션한 결과, 제안한 알고리듬이 기존의 MEDE 알고리듬 보다 5 dB 이상 향상된 MSE 성능을 보이며 오차 분포의 중심 위치가 정확히 0에 위치하였다. In this paper, the Euclidean distance between the probability density functions (PDFs) for biased errors and a Dirac-delta function located at zero on the error axis is proposed as a new performance criterion for adaptive systems in non-Gaussian noise environments. Also, based on the proposed performance criterion, a supervised adaptive algorithm is derived and applied to adaptive equalization in the shallow-water communication channel distorted by severe multipath fading, impulsive and DC-bias noise. The simulation results compared with the performance of the existing MEDE algorithm show that the proposed algorithm yields over 5 dB of MSE enhancement and the capability of relocating the mean of the error PDF to zero on the error axis.

Minimax FIR smoothers for deterministic continuous-time state space models

In order to design a smoother for a deterministic continuous-time state space model, a new performance criterion is proposed, which is given by a ratio of the current estimation error to the weighted energy of the deterministic disturbance applied during the recent finite horizon. Among smoothers with the deadbeat property and finite impulse response (FIR) structure, a minimax FIR smoother (MFS) is obtained to optimize the proposed performance criterion. To begin with, the functional optimization problem is formulated with respect to kernel functions of the MFS and then its solution is explicitly presented. The MFS depends only on inputs and outputs on the finite recent horizon, and is independent of any a priori state information. The MFS is first represented in an integral form for simple representation and then a differential form is introduced for efficient numerical computation. As in H ∞ IIR smoothing and H 2 IIR filtering, it is shown that the proposed MFS for a deterministic system can be interpreted as the minimum variance unbiased FIR smoother for a stochastic system.

A New Approach to Evaluate the Performance of Gravity-Based Coal Washing Equipment

A new method for performance evaluation of gravity-based coal-cleaning unit operations has been proposed in this article. This is done by evaluating the nature and the amount of misplaced particles in the clean coal fraction. The proposed performance parameters “Misplacement 1” and “Misplacement 2” vary from 0 to 1 and therefore, it is easier to compare the performance of various equipment on a simple common scale to process a typical coal. It takes into consideration the ash distribution of the misplaced particles to facilitate direct comparison of various gravity-based equipment as well as identifying their optimum operating conditions. The concept and the methodology to evaluate the proposed performance criterion have been discussed in detail. The advantages of using this new methodology over the conventional distribution curve analysis have been established with some illustrative examples.

1522 舶用推進システムの最適制御に関する考察

A ship propulsion system shows complex dynamic behamic behaviors and consideration of dynamic characteristics is indispensable for development of effective control system. In this paper, the propulsion system is mathematically modeled and an optimal control scheme is formulated in order to transit the system in shorter time under proposed performance criterion. Finally, system simulations are conducted and advantages of the propose control system have been quantitatively evaluated.

A performance criterion for the depth estimation with application to robot visual servo control

AbstractThis article deals with the depth observability problem of a robot visual system with a moving camera. In the visual system, the unknown depth of a feature point is estimated from the input of the camera velocity and the output of the image of the feature point. Although it is well known that the linear velocity of the camera must satisfy some constraints for successful depth estimation, this proposes a criterion to measure the performance of the depth estimation, which is a heuristic extension from an estimation result of a linear system. This performance criterion depends on both the image position and the linear velocity of the camera. Some simulation and experiment examples demonstrate and verify the proposed performance criterion. Furthermore, this criterion is used to develop a new visual servo control scheme that has good performance in both the depth estimation and the visual control. This control scheme is also verified by a simulation example. © 2001 John Wiley & Sons, Inc.

Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data

Abstract A variety of vegetation indices have been used to assess the state and monitor the evolution of the terrestrial biosphere. Early indices were easy to compute but very sensitive to soil and atmospheric effects. Modified indices with a reduced sensitivity to soil brightness changes were then proposed. More recently, new indices have been designed to be less affected by either atmospheric or soil conditions, or both. In this paper, we propose and demonstrate an objective method to evaluate, through model simulation studies, the performance of a representative sample of three such indices (NDVI, SAVI and GEMI) with respect to their capability to retrieve the fractional vegetation cover and the leaf area index from AVHRR optical data. The proposed performance criterion is based on the concept of signal to noise ratio, where the signal is defined to capture the sensitivity of the index to the desired information, and the noise is designed to measure the sensitivity of this index to undesirable perturbations. It is found that no single index is optimal under all conditions, but that improved indices (GEMI and SAVI) are generally much better than the NDVI for assessing the fractional vegetation cover. Reliable estimates of the leaf area index appear very difficult to obtain when this parameter exceeds about two because of the insensitivity of the red reflectance to multiple leaf layers.

Diffusive Monitor Test: Performance Under Transient Conditions

Abstract A performance test is proposed for evaluating passive (pumpless) gas and vapor samplers for use in a time-variable environment. Such a test is necessary because of potentially excessive analyte loss by some passive samplers. Suggested is a measurement of the maximum bias in estimates of the time-weighted average concentration of individual pulses of selected duration and time. This bias is then combined with the bias and random sampling/analytical errors from measurements at constant concentration. Similar to the current NIOSH Standards Completion Program criteria for sampling methods using pumps, the proposed performance criterion is simply a requirement of less than 25 percent overall single-sample inaccuracy at the 95 percent confidence level under both constant and varying conditions. Alternatively, the test given here may be used simply to define a specific sampler performance component.

A mean-square performance criterion for adaptive pattern classification systems

A performance criterion for an adaptive pattern classification system is presented that does not require the probability density function associated with each class to be known. Any decision rule that consists of a discriminant function that is a linear combination of scalar functions of the pattern vector may be chosen on the basis of a priori knowledge about the classes, engineering judgment, and economic considerations. The performance criterion is used to measure the system's performance on a set of "typical patterns" or "training samples." The proposed performance criterion is suitable for the use of multivariable search techniques in order to find the optimum parameters of the discriminant function. It is shown that, as the number of training samples approaches infinity, the resulting discriminant function of the form chosen at the outset approximates the optimum Bayes' discriminant function in the mean-square sense. This short paper extends and solidifies a performance criterion for the adaptive pattern classification system described by Patterson and Womack [11]. The improved criterion gives added assurance that a control loop can adapt the system to the desired operating point. Recursive algorithms as described by Kashyap and Blaydon [12], Pitt and Womack [13], and Nikolic and Fu [14] can accelerate the adapting process. Typical of the possible applications for this criterion is the control of the pass/reject phase of the output of a semiconductor manufacturing process. It is at this point in the process that a decision must be made quickly and efficiently as to whether a device does or does not meet specifications. One conventional test procedure is to make individual measurements on n different parameters which results in a parameter acceptance subregion defined by an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</tex> - dimensional parallelepiped. The discriminant function approach utilized in this short paper is effectively a many-to-one mapping procedure, where the parameter acceptance subregion is defined by an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</tex> -dimensional ellipsoid. This increases the yield of the process and improves the test procedure.

An Adaptive Pattern Classification System

Adaptive pattern classification is the assignment of patterns to classes based on typical patterns or training samples, used by the system to determine the decision procedure. The system is adaptive in the sense that the decision procedure is optimized according to some criterion of the system's performance on the training samples. An adaptive pattern classification system is described that does not require a priori knowledge of the probability density of the pattern vectors for each class, as do the classical statistical techniques. Any decision rule, consisting of a discriminant function, that is a linear combination of arbitrary scalar functions of the pattern vector, may be chosen on the basis of a priori knowledge about the classes, engineering judgment, and economic considerations. The system optimizes itself by adjustment of the decision parameters according to a weighted mean-square-error performance criterion, using a multivariable search technique. The proposed performance criterion is well suited for self-optimizing search procedures. It also has the property that, as the number of training samples approaches infinity, the resulting disciminant function belongs to the class of discriminant functions, chosen at the outset, which approximates the optimum Baye's discriminant function with minimum variance. Some results from simulation studies are presented which include comparison with classical statistical techniques.