Adaptive tracking with external force disturbance rejection for uncertain robotic systems

This paper is concerned with the tracking control problem of robotic systems perturbed by time-varying parameters, unmodelled dynamics and external force (and moment) disturbances. The upper bound of system uncertainties and disturbances is not required for controller design. Also, no limitations are assumed on the speed of variation and the magnitude of unknown parameters and perturbations. An adaptive algorithm with simplicity and universality properties is proposed to ensure robust tracking. Presenting the closed loop stability proof analytically, the tracking controller is applied to a two-link robot manipulator and the simulation results are demonstrated to show the effectiveness of the method.     

Stabilization of positive switched systems with time-varying delays under asynchronous switching

This paper investigates the state feedback stabilization problem for a class of positive switched systems with time-varying delays under asynchronous switching in the frameworks of continuous-time and discrete-time dynamics. The so-called asynchronous switching means that the switches between the candidate controllers and system modes are asynchronous. By constructing an appropriate co-positive type Lyapunov-Krasovskii functional and further allowing the functional to increase during the running time of active subsystems, sufficient conditions are provided to guarantee the exponential stability of the resulting closed-loop systems, and the corresponding controller gain matrices and admissible switching signals are presented. Finally, two illustrative examples are given to show the effectiveness of the proposed methods.     

Statistical Product Selectivity Modeling and Optimization for γ-Al2O3-Supported Cobalt Catalysts-Based Fischer–Tropsch Synthesis

The statistical selectivity models were developed for four different Fischer–Tropsch synthesis product range, including methane (CH₄), light olefins (C₂=C₄), light paraffins (C₂–C₄), and long-chain hydrocarbons (C₅₊), based on the experimental data obtained over thirteen γ-Al₂O₃ supported cobalt-based catalysts with different cobalt particle and pore sizes. The input variables consist of cobalt metal particle size and catalyst pore size. The cubic and quadratic polynomial equations were fitted to the experimental data, however, the mathematical models were subjected to model reduction for the enhancement of model adequacy, which was investigated through ANOVA. The multi-objective optimization revealed that the maximum C₅₊?selectivity (84.150%) could be achieved at the cobalt particle size and pore sizes of 14.764 and 23.129 nm, respectively, while keeping the selectivity to other hydrocarbon products minimum.

Graphic Abstract

     

Socially Assistive Robots in Elderly Care: A Mixed-Method Systematic Literature Review

The world’s population is aging, and developed countries are engaged in developing a new aged-care paradigm to reduce spiraling healthcare costs. Assistive technologies like Socially Assistive Robots (SAR) are being considered as enablers to support the process of care giving or keep elderly at home longer. This article reports a mixed-method systematic review of SAR in elderly care and recognizes its impact on elderly well-being, integrating evidence from qualitative and quantitative studies. It follows the principles explained in Cochrane Handbook for Systematic Reviews of Interventions and classifies interventions, measures, and outcomes of field trials of SAR in elderly care. Eighty-six studies in 37 study groups have been included. The findings imply positive effects of SAR on elderly well-being. Ten significant recommendations are made to help avoid the current limitations of existing research and to improve future research and its applicability. This review revealed that SAR can potentially enhance elderly well-being and decrease the workload on caregivers. There is a need for rigorous research methodology, person-centered care, caregiver expectation model, multimodal interaction, multimodal data collection, and modeling of culturally diverse groups to facilitate acceptability of SAR.     

Fault detection for continuous‐time switched systems under asynchronous switching

In this paper, the problem of fault detection for continuous‐time switched systems under asynchronous switching is investigated. The designed fault detection filter is assumed to be asynchronous with the original systems. Attention is focused on designing a fault detection filter such that the estimation error between the residual and the fault is minimized in the sense of H _∞ norm. By employing piecewise Lyapunov function and average dwell time techniques, a sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities. Finally, an example of a switched electrical circuit is provided to illustrate the effectiveness of the proposed approach. Copyright © 2013 John Wiley & Sons, Ltd.     

A model for the adsorption of single metal ion solutes in aqueous solution onto activated carbon produced from pecan shells

Adsorption isotherms for activated carbon made from pecan shells have been obtained at 25 °C and an approximate pH of 3 for a number of metal ion solutes. It was found that the Slips and Freundlich equations were satisfactory for explaining the experimental data. The correlation of metal ion adsorption with the solute parameters of metal ion electronegativity and first stability constant of the metal hydroxide was investigated. In the case of most of the metal ions studied, higher electronegativities and stability constants corresponded to the higher adsorption levels of metal ions onto the activated carbon. A correlation was developed that predicts the constants of the Freundlich equation from the selected parameters of the metal ions, and thus can predict the adsorption isotherms at constant pH. The developed correlation gives results with acceptable deviations from experimental data. A procedure is proposed for obtaining similar correlations for different conditions (temperature, pH, carbon type and dosage). The ratio of equivalent metal ions adsorbed to protons released is calculated for the studied metal ions over a range of concentrations. In most cases, particularly at low concentrations, this ratio is close to one, confirming that ion exchange of one proton with one equivalent metal ion is the dominant reaction mechanism.     

Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

     

A Multi-Criteria Group Decision Making Methodology Using Interval Type-2 Fuzzy Sets: Application to Water Resources Management

In this paper, a new fuzzy group decision-making methodology which determines and incorporates negotiation powers of decision makers is developed. The proposed method is based on a combination of interval type-2 fuzzy sets and a multi-criteria decision making (MCDM) model, namely TOPSIS. To examine the applicability of the proposed methodology, it is used for finding the best scenario of allocating water and reclaimed wastewater to domestic, agricultural, and industrial water sectors and restoring groundwater quantity and quality in the Varamin region located in Tehran metropolitan area in Iran. The results show that the selected scenario leads to an acceptable groundwater conservation level during a long-term planning horizon. Although the capital cost of this scenario is high, which leads to groundwater restoration during the 34-year planning horizon, it is determined as the best allocation scenario. This scenario also entails the second least pumping cost, due to less water allocation from the groundwater. To evaluate the results of the proposed methodology, they are compared with those obtained using some well-known interval type-2 decision-making approaches including arithmetic-based, TOPSIS-based, and likelihood-based comparison methods. The Spearman correlation coefficient shows that the obtained results generally concur with those of the other methods. It is also concluded that the proposed methodology gives more reasonable results by calculating and considering the negotiation powers of decision makers in an extended TOPSIS-based group decision-making model.

     

Selective harmonic elimination method for wide range of modulation indexes in multilevel inverters using ICA

Selective harmonic elimination（SHE） in multilevel inverters is an intricate optimization problem that involves a set of nonlinear transcendental equations which have multiple local minima. A new advanced objective function with proper weighting is proposed and also its efficiency is compared with the objective function which is more similar to the proposed one. To enhance the ability of the SHE in eliminating high number of selected harmonics, at each level of the output voltage, one slot is created. The SHE problem is solved by imperialist competitive algorithm（ICA）. The conventional SHE methods cannot eliminate the selected harmonics and satisfy the fundamental component in some ranges of modulation indexes. So, to surmount the SHE defect, a DC-DC converter is applied. Theoretical results are substantiated by simulations and experimental results for a 9-level multilevel inverter. The obtained results illustrate that the proposed method successfully minimizes a large number of identified harmonics which consequences very low total harmonic distortion of output voltage.     

Thermal antioxidative kinetics of sesamol in triacylglycerols and fatty acid methyl esters of sesame,olive, and canola oils

Oxidation kinetics of the triacylglycerols (TAGs) and fatty acid methyl esters (FAMEs) of sesame, olive, and canola oils were studied in the presence of the different concentrations of sesamol (0.1%–0.16%) at 60, 80, and 100°C. Sesamol increased the temperature coefficient, T_C, and Q₁₀ number of the TAGs more significantly compared to the FAMEs. All the sesamol-added TAG and FAME systems, respectively, of the olive, canola, and sesame oils, respectively, exerted increased values of the Arrhenius (activation energy, E_a, and frequency factor, A) and Eyring (enthalpy, ΔH⁺⁺, and entropy, ΔS⁺⁺) equation parameters. Sesamol improved the Gibbs free energy (ΔG⁺⁺) of the activated complex formation in the canola, sesame, and olive systems, respectively, and the effect was greater in the FAMEs.