Control Performance Criteria Research Articles

Evaluating Use of Hydraulic Modified Sulfur Powder in Concrete Pavements: Laboratory Testing and Field Application

This study comprehensively evaluates the field applicability of hydraulic modified sulfur (HMS) as a concrete additive. We assessed the microstructural characteristics, mechanical properties, and durability performance of HMS at various replacement ratios in a laboratory setting. In addition, a field study was conducted by removing an existing conventional concrete pavement measuring (6000 × 12,000 × 70 mm, W × L × T) and overlaying it with HMS concrete. The experimental results revealed that HMS enhanced the mechanical and durability performance when used as a cement replacement at rates below 9%. These results satisfied the quality control standards and performance criteria specified in the Korean standard specification for cement-concrete pavements. The comparative analysis revealed that HMS concrete outperformed conventional concrete mixtures by 62.6% in sulfuric acid penetration depth, 14.8% in compressive strength retention after sulfuric acid immersion, and 53.1% in chloride-ion penetration resistance. Furthermore, no anomalies were detected during the 3-month follow-up period.

Decentralized and performance-constrained state-estimated fuzzy control for nonlinear differential-algebraic interconnected systems

This paper introduces a decentralized and mixed performance-constrained state-estimated fuzzy control strategy designed for nonlinear differential-algebraic interconnected systems. Initially, the approach employs a Takagi-Sugeno (T-S) fuzzy model to approximate these complex systems. To address potential limitations within the interconnected systems, a Proportional-plus-Derivative (PD) state control method is integrated into the proposed control scheme. Additionally, an observer is constructed to estimate system states, enhancing the feasibility of the control method. System stability analysis is conducted using the free-weighing Lyapunov function approach, allowing designers to customize the weight matrix for desired control performance and facilitate controller design. Subsequently, a fuzzy controller is developed to ensure stability and meet both Passive-H∞ Performance (PHP) and H2 Control Performance (HCP) criteria. Finally, the effectiveness of the proposed design approach is validated through simulation results.

Evaluation of a high-throughput H295R homogenous time resolved fluorescence assay for androgen and estrogen steroidogenesis screening

The H295R test guideline assay evaluates the effect of test substances on synthesis of 17β-estradiol (E2) and testosterone (T). The objective of this study was to leverage commercial immunoassay technology to develop a more efficient H295R assay to measure E2 and T levels in 384-well format. The resulting Homogenous Time Resolved Fluorescence assay platform (H295R-HTRF) was evaluated against a training set of 36 chemicals derived from the OECD inter-laboratory validation study, EPA guideline 890.1200 aromatase assay, and azole fungicides active in the HT-H295R assay. Quality control performance criteria were met for all conditions except E2 synthesis inhibition where low basal hormone synthesis was observed. Five proficiency chemicals were active for both the E2 and T endpoints, consistent with guideline classifications. Of the nine OECD core reference chemicals, 9/9 were concordant with outcomes for E2 and 7/9 for T. Likewise, 9/13 and 11/13 OECD supplemental chemicals were concordant with anticipated effects for E2 and T, respectively. Of the 10 azole fungicides screened, 7/10 for E2 and 8/10 for T exhibited concordant outcomes for inhibition. Generally, all active chemicals in the training set demonstrated equivalent or greater potency in the H295R-HTRF assay, supporting the sensitivity of the platform. The adaptation of HTRF technology to the H295R model provides an efficient way to evaluate E2 and T modulators in accordance with guideline specifications.

Underground mining technologies at the Kekura deposit

Research subject and objective is to work out exploration data details to optimize the processes of filling the stoped-out areas when choosing a underground mining technologies for a gold ore deposit. Methods of research include an analytical survey of information about the deposit to improve the quality of mining by minimizing dilution and loss of valuable ores when backfilling with hardening mixtures. Research results. The paper provides data about a gold deposit with complex geological, geographical and operational conditions. Design solutions for mining technology with minimum dilution and loss and for the enterprise’s production capacity development are analyzed. The priority of the ore-hosting rock mass state control performance criterion is substantiated. The criterion refers to production costs considering the damage from losses and dilution. Factors of ore dilution in the course of underground mining are generalized and systematized. Some options for mining systems are recommended as launching. The options of mining by open-pit and underground methods are assessed and the time to reach full production capacity is given. It is shown that in the course of development, technologies containing backfilling with hardening mixtures will be a priority. Recommendations are given to provide raw materials for hardening mixtures preparation by recycling own waste and waste from allied industries. Conclusions. The most promising technology for ore mining by underground method provides for backfilling with hardening materials made through demetallization and disposed component properties control

Parametric sub-structuring models of large space truss structures for structure/control co-design

Modern and future high precision pointing space missions face increasingly high challenges related to the widespread use of large flexible structures. The development of new modeling tools which are able to account for the multidisciplinary nature of this problem becomes extremely relevant in order to meet both structure and control performance criteria. This paper proposes a novel methodology to analytically model large truss structures in a sub-structuring framework. A three dimensional unit cube element has been designed and validated with a Finite Element commercial software. This model is composed by multiple two-dimensional sub-mechanisms assembled using block-diagram models. This constitutes the building block for constructing complex truss structures by repetitions of the element. The accurate vibration description of the system and its minimal representation, as well as the possibility of accounting for parametric uncertainties in its mechanical parameters, make it an appropriate tool to perform robust Structure/Control co-design. In order to demonstrate the strengths of the proposed approach, a structure/control co-design study case is proposed and solved using structured robust H∞-synthesis. The objective is to optimize the pointing performances of an antenna, minimizing the perturbations coming from the Solar Array Driving Mechanisms (SADM) of two solar panels, performing active control by means of multiple Proof Mass Actuators (PMA), and simultaneously reduce the mass of the truss-structure which connects the antenna to the main spacecraft body.

LQG Control Performance With Low-Bitrate Periodic Coding

Several specific low-bitrate coding strategies are examined through their effect on LQ control performance. By limiting the subject to these methods, we are able to identify principles underlying coding for control; a subject of significant recent interest but few tangible, i.e. implementable, results. In particular, we consider coding the quantized output signal deploying period-two codes of differing delay-versus-accuracy tradeoff. The quantification of coding performance is via the LQ control cost over a long but finite horizon up to a specified average \textit{escape time}. Infinite-horizon stabilization is replaced by a mean-time-before-failure property, which is a new viewpoint but allows contact with uncoded controllers. The feedback control system comprises the coder-decoder in the path between the output and the state estimator, which is followed by linear state-variable feedback, as is optimal in the memoryless case. The static quantizer is treated as the functional composition of an infinitely-long linear staircase function and a saturation. This permits the analysis to subdivide into estimator computations, seemingly independent of the control performance criterion, and

Nature-inspired and hybrid optimization algorithms on interval Type-2 fuzzy controller for servo processes: a comparative performance study

In this paper, performance evaluations of six well-known nature-inspired algorithms have been reported containing genetic algorithm, cuckoo search, particle swarm optimization, differential evolution, bee colony, and combined particle swarm optimization and differential evolution (CPSODE) algorithms. Based on these optimization algorithms, input and output scaling factors of an interval Type-2 fuzzy PID controller (IT2-FLC) are chosen for closed-loop servo tracking. Optimal values of the scaling factors are chosen by minimization of the objective function which is defined based on the closed-loop controller performance criteria. A detailed comparative analysis is reported based on the simulation and experimental results. Performance analysis reveals that improved performance, reliability, robustness, and lesser noise sensitivity are reported by IT2-FLC with the optimal values obtained by the hybrid algorithm CPSODE.

A control strategy for nonconventional column/rectifier configuration for composition control

Energy and cost saving can be accomplished by Nonconventional column/rectifier configuration. The design with a complex arrangement system needs an advance process control such as Model Predictive Control (MPC) to get the best responses control for composition. MPC which the objective function is optimized by Improved Particle Swarm Optimization (IPSO) is required and implemented for composition control. IPSO is used to get the best values of tuning for weighting in MPC. Integral Absolute Error (IAE) is used to indicate the value of control performance criteria. The results show that IPSO-MPC is better than MPC.

Assessment Criteria for the Mechanical Loads of Wind Turbines applied to the example of Active Power Control

Assessment criteria for design of wind turbines controller are discussed since conventional control performance criteria are not sufficient to evaluate the mechanical loads as dependency of the controller type and settings. This will be presented and discussed using the example of the active power control of wind turbines. In contrast to the nominal operation of wind turbines divided into power optimization in the partial and power limitation in the full load region, the power output is guided by an external power reference signal. The reference signal may be delivered either directly by higher-level load frequency controller of the power system or by the wind farm controller. In both cases the external variation of the power to be delivered has an enormous influence on the dynamics and mechanical loads of the wind turbine. To quantify these loads that occur during power tracking operation the Damage Equivalent Load amplitude as appropriated load assessment criteria is described and prepared for control design.

Switching controller design for linear time invariant plant with a single I/O delay

ABSTRACT To deal with the problem of conflicting requirements that cannot be satisfied by only a single LTI controller, this paper focuses on the design of a switching controller, which includes several stabilising linear time-invariant (LTI) controllers designed independently with different control performance criteria, for a specific LTI plant with a single I/O delay. The switching controller design procedure is divided into three steps. First, using simple loop shifting arguments, the design problem is reducible to an equivalent delay-free one. Second, traditional LTI controller synthesis methods could be considered independently for the delay-free plant. Third, based on a quadratically stable state space realisation method, a Youla parameter including a switching strategy with these controllers is designed to guarantee different requirements. Finally, a numerical example is provided to demonstrate the validity and efficiency of the approach.

Fuzzy and Taguchi based Fuzzy Optimization of Performance Criteria of the Process Control Systems

This paper proposes a Taguchi based Fuzzy and Fuzzy PID application using MATLAB ® version 2015a to assess and optimize of process control performance criteria of liquid level and flow rate control system. When the main effect graphs for the liquid level and flow rate control system are evaluated, it was seen that the change in the membership function is the most effective factor on the process control performance. It can be said that the Gaussian membership function provides the lowest mean and standard deviation in the offset value. Improvement rates for “overshoot”, “rise time”, “first peak time”, “%95 setting time, “%99 setting time”, “mean” and “the standard deviation of the offset values” are %50, %50, %55, %77, %64, %5, %63 for flow rate control system; %50, %49, %55, %43, %48, %4, %63 for liquid level control system in order. In comparison with the classical PID method, in the Fuzzy PID method, the improvement is calculated as 54% in the average of the offset value and 99% in the standard deviation.

Switching controller design for linear time-invariant plant with H2 performance criterion

This paper deals with the problem of designing a switching controller, which includes several linear time-invariant (LTI) controllers designed beforehand and independently for a specific LTI plant with corresponding H2 control performance criteria. It is possible to find suitable state space realizations for any given family of controller transfer matrices, which guarantee not only certain H2 performance of the overall closed-loop system under arbitrary switching but also the corresponding H2 performance of local subsystems at each switching point. The effectiveness of the proposed method is demonstrated with a numerical example.

Validation of the 22-day Honey Bee Larval Toxicity, Repeated (Chronic) Exposure Study Design

Assessing the chronic toxicity of a compound to developing honey bees (Apis mellifera L.) has proven to be a challenge since the mid-2000s. Such data are requested by global regulatory authorities so they can evaluate the risk of compounds to larval honey bees when exposure is likely to occur in the environment. Poor test performance has led to frequent study failures and data uncertainty. Here we highlight a recent effort by the Pollinator Research Task Force (PRTF)1 to validate the use of a method for evaluating the chronic toxicity of a compound (e.g., a pesticide) to an immature honey bee for use in a risk assessment. A ring test protocol was selected and based upon the current OECD guidance document No. 2392 with amendments developed at the University of Florida (Schmehl et al. 2016)3. Fifteen independent laboratories on three continents representing government, academia, and industry followed the same testing protocol to: 1) determine if test performance is robust across different geographic regions and different laboratory personnel and 2) identify limitations associated with the methodology. The control performance criteria for a valid test according to OECD GD 239 is ≥ 85% survival at the end of the larval development and ≥ 70% survival through adult emergence. Thirteen trials (81.3%) satisfied the validity criteria and the test design’s performance was determined adequate for regulatory testing. The toxic reference chemical (dimethoate) had a consistent response with a 22-day EC 50 range of 8-22 μg active substance (a.s.)/g diet. An acetone concentration at the maximum concentration allowed by the OECD GD 239 (2% acetone) was observed to be problematic to test performance. In conclusion, the ring test methods based upon the OECD GD 239 demonstrated that the repeat (chronic) exposure of a compound on developing bees can be successfully conducted. A copy of the full study report4 can be accessed here.

Enhancement of the efficiency of the automatic control system to control the thermal load of steam boilers fired with fuels of several types

An automatic control system to control the thermal load (ACS) in a drum-type boiler under random fluctuations in the blast-furnace and coke-oven gas consumption rates and to control action on the natural gas consumption is considered. The system provides for use of a compensator by the basic disturbance, the blast-furnace gas consumption rate. To enhance the performance of the system, it is proposed to use more accurate mathematical second-order delay models of the channels of the object under control in combination with calculation by frequency methods of the controller parameters as well as determination of the structure and parameters of the compensator considering the statistical characteristics of the disturbances and using simulation. The statistical characteristics of the random blast-furnace gas consumption signal based on experimental data are provided. The random signal is presented in the form of the low-frequency (LF) and high-frequency (HF) components. The models of the correlation functions and spectral densities are developed. The article presents the results of calculating the optimal settings of the control loop with the controlled variable in the form of the “heat” signal with the restricted frequency variation index using three variants of the control performance criteria, viz., the linear and quadratic integral indices under step disturbance and the control error variance under random disturbance by the blastfurnace gas consumption rate. It is recommended to select a compensator designed in the form of series connection of two parts, one of which corresponds to the operator inverse to the transfer function of the PI controller, i.e., in the form of a really differentiating element. This facilitates the realization of the second part of the compensator by the invariance condition similar to transmitting the compensating signal to the object input. The results of simulation under random disturbance by the blast-furnace gas consumption are reported. Recommendations are made on the structure and parameters of the shaping filters for modeling the LF and HF components of the random signal. The results of the research may find applications in the systems to control the thermal processes with compensation of basic disturbances, in particular, in boilers for combustion of accompanying gases.

H2−H∞ control of continuous-time nonlinear systems using the state-dependent Riccati equation approach

ABSTRACTThis paper presents a novel state-dependent Riccati equation (SDRE) control approach with the purpose of providing a more effective control design framework for continuous-time nonlinear systems to achieve a mixed nonlinear quadratic regulator and H∞ control performance criteria. By solving the generalized SDRE, the optimal control solution is found to achieve mixed performance objectives guaranteeing nonlinear quadratic optimality with inherent stability property in combination with H∞ type of disturbance reduction. An efficient computational algorithm is given to find the solution to the SDRE. The efficacy of the proposed technique is used to design the control system for inverted pendulum, an under-actuated nonlinear mechanical system.

The Control of The Lorenz Chaotic System Blended With The Noise

In this study, the Lorenz chaotic system behavior is investigated according to the change in the noise of the system and measurement. The noise was emerged as an important impact on the Lorenz chaotic system. The discrete-time LQR ( Linear Quadratic Regulator) control method and discrete-time PI controller method have been used to the noisy system controls. Noise was accepted as a destructor that changes the output behavior of the chaotic system. Noisy system outputs were enforced to move to the equilibrium points by the support of controllers. Optimization of the controller parameters for noiseless system models was performed using a genetic algorithm method. Then, both control system algorithms determined as successful in transporting to the equilibrium point for state variables which are blended with the noise. Changes, associated with the noise conditions are given in the graphics and tables. Besides, the error performance criteria and the control performance criteria were obtained to evaluate the results. This study was performed by MATLAB-Simulink simulation program.

Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory) a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the reference growth trajectory is 5.2 × 106 cells/mL. The controller proves its robustness to keep the process on the desired growth profile.

Objective control skills among students with intellectual disability at special school in Korea

The purpose of this study was to examine the level of objective control skill and performance criteria of students with intellectual disability at special school. Three hundred thirty one students with intellectual disability were participated this study (M: 230, F: 101). Their aged was from 10-18 aged old. We had the test the objective control skill by video, objective control skill consisted of overhand throwing, catching, kicking, hitting, dribbling. Data were analyzed using liner regression and calculated mean, standard error, standard deviation and 95% confidence interval. Total objective control skill mastery was 47%, and hitting skill score was the highest than another subtest, the lowest performance skill was overhand throwing. There were showed that not significant difference object control skill in according to gender. Also not effect object control skill and subtest in according to age except dribbling. It was showed that significant effect objective control skill in according to disability level.

Model-Based Traffic Congestion Control in Urban Road Networks

Traffic congestion is a serious problem for big cities. The model-based optimization control strategy is an effective method for decreasing traffic congestion. A proper control performance criterion is a key factor for effectively addressing different urban road network issues, for example, network mobility and traffic congestion. Therefore, two control performance criteria are proposed—L2-norm and L∞-norm performance indexes—for model-based urban road network controllers. The L2-norm and L∞-norm performance indexes are aimed at keeping road network homogeneity and decreasing road network congestion, respectively. For analysis of these two control performance criteria, case studies were conducted with the microscopic simulation software CORSIM to evaluate the designed model-based controllers with different criteria. The control effects of the model-based road network controllers were compared quantitatively by analyzing the degree of road network congestion and qualitatively by analyzing the macroscopic fundamental diagram of the road network (i.e., a network aggregated characteristic).

An investigation into the use of neural networks for the semi-active control of a magnetorheologically damped vehicle suspension

Neural networks are highly useful for the modelling and control of magnetorheological (MR) dampers. A damper controller based on a recurrent neural network (RNN) of the inverse dynamics of an MR damper potentially offers significant advantages over conventional controllers in terms of reliability and cost through the minimal use of sensors. This paper introduces a neural-network-based MR damper controller for use in conjunction with the system controller of a semi-active vehicle suspension. A mathematical model of a semi-active quarter-vehicle suspension using an MR damper is derived. Control performance criteria are evaluated in the time and frequency domains in order to quantify the suspension effectiveness under bump and random road disturbance. Studies using the modified Bouc—Wen model for the MR damper as well as an actual damper fitted in a hardware-in-the-loop simulation (HILS) both showed that the inverse RNN damper controller potentially offers a significantly superior ride comfort and vehicle stability over a conventional MR damper controller based on continuous-state control. The neural network controller produces a smoother and lower input voltage to the MR damper coil, ensuring extended damper life and lower power requirement respectively. Further studies performed using an RNN model of the forward dynamics of the MR damper showed that it is a reliable substitute for HILS for validating multi-damper control applications.