Adaptive T–S fuzzy controller using reinforcement learning based on Lyapunov stability

In this paper, an adaptive Takagi–Sugeno (T–S) fuzzy controller based on reinforcement learning for controlling the nonlinear dynamical systems is proposed. The parameters of the T–S fuzzy system are learned using the reinforcement learning based on the actor-critic method. This on-line learning algorithm improves the controller performance over the time, which it learns from its own faults through the reinforcement signal from the external environment and tries to reinforce the T–S fuzzy system parameters to converge. The updating parameters are developed using the Lyapunov stability criterion. The proposed controller is faster in learning than the T–S fuzzy that parameters learned using the gradient descent method under the same conditions. Moreover, it is able to handle the load changes and the system uncertainties. The test is carried out based on two mathematical models. In addition, the proposed controller is applied practically for controlling a direct current (DC) shunt machine. The results indicate that the response of the proposed controller has a good performance compared with other controllers.     

A composite pseudospectral method for solving multi-delay optimal control problems involving piecewise constant delay functions

An adaptive numerical method for solving multi-delay optimal control problems with piecewise constant delay functions is introduced. The proposed method is based on composite pseudospectral method using the well-known Legendre–Gauss–Lobatto points. In this approach, the main problem converts to a mathematical optimization problem whose solution is much more easier than the original one. The necessary conditions of optimality associated to nonlinear piecewise constant delay systems are derived. The method is easy to implement and provides very accurate results.     

Probabilistic fuzzy logic controller for uncertain nonlinear systems

This paper proposes a probabilistic fuzzy proportional - integral (PFPI) controller for controlling uncertain nonlinear systems. Firstly, the probabilistic fuzzy logic system (PFLS) improves the capability of the ordinary fuzzy logic system (FLS) to overcome various uncertainties in the controlled dynamical systems by integrating the probability method into the fuzzy logic system. Moreover, the input/output relationship for the proposed PFPI controller is derived. The resulting structure is equivalent to nonlinear PI controller and the equivalent gains for the proposed PFPI controller are a nonlinear function of input variables. These gains are changed as the input variables changed. The sufficient conditions for the proposed PFPI controller, which achieve the bounded-input bounded-output (BIBO) stability are obtained based on the small gain theorem. Finally, the obtained results indicate that the PFPI controller is able to reduce the effect of the system uncertainties compared with the fuzzy PI (FPI) controller.     

Nonlinear model-predictive control with disturbance rejection property using adaptive neural networks

In this paper, a method is proposed to reject disturbances in the model predictive control (MPC) strategy. In addition, uncertainties in the system parameters (i.e., internal disturbances) are considered as well. To achieve these goals, adaptive neural networks are designed as the predictor model and as the nonlinear disturbance observer, respectively. The disturbances are rejected via the optimization problem of the MPC. Stability of the closed-loop system is studied based on the Input-to-State Stability method. The proposed method is applied to the pH neutralization process and CSTR system and its effectiveness in optimal rejection of the disturbances and satisfying the system constrains is compared with the feed-forward control method.     

The Shaffer–Gee perspective: Can epistemic games serve education?

This paper addresses the issue of how games can reshape education by describing current educational practices. It argues that there are conservative camps that emphasize structure and development of basic literacy and numeracy skills in education as well as liberal camps that emphasize immersion, and notices that both camps fail to train students able to address the crisis of innovation. A post-progressive pedagogy that integrates both structure and immersion to address this innovation crisis is described in the paper. It is also emphasized that epistemic games can serve as excellent tools at the hand of this post-progressive pedagogy.     

Isolation and purification of rat islet cells by flow cytometry

Flow cytometry has been employed as a method to study homogeneity of isolated islet subpopulations. After collagenase digestion of rat pancreas and elutriation of tissue fragments, islets were isolated and dissociated, and cells were analyzed and sorted according to their low forward angle light scattering properties by using automated flow cytometry. A standardized procedure was developed for the preparation of rat islet cell grafts for purification of islet cells. In this process, after collagenase digestion of pancreas, islets were isolated, dissociated, identification by dithizone method and then with enzymatic procedure by DNase and trypsin, the islet cells changed into single cells and beta cells were identified by immunofluorescence method and then assayed by flow cytometry. Methods have been developed for the preparation of suspension of viable rat pancreatic islet cells and their analysis and sorting in the fluorescence activated cell sorter (FACC IV, Becton Dickinson, Sunnyvale, Ca). Flow cytometry of these cells indicated that there were 91% of beta cells in cell suspension. Most of the exocrine particles were lost during digestion. Purified endocrine islet cell grafts were prepared by pure beta-cells, without endocrine non-beta cells. The purified aggregates were devoid of endocrine non-beta cells and damaged cells.     

Chip morphology predictions while machining hardened tool steel using finite element and smoothed particles hydrodynamics methods

Chip morphology predictions in metal cutting have always been challenging because of the complexity of the various multiphysical phenomena that occur across the tool-chip interface. An accurate prediction of chip morphology is a key factor in the assessment of a particular machining operation with regard to both tool performance and workpiece quality. Although finite element (FE) models are being developed over the last two decades, their capabilities in modeling correct material flow around the tool tip with shear localization are very limited. FE models with an arbitrary Lagrangian Eulerian (ALE) approach are able to simulate correct material flow around the tool tip. However, these models are unable to predict any shear localization based on material flow criteria. On the other hand, FE models with a Lagrangian formulation can simulate shear localization in the chip segments; they need to make use of a mesh-based chip separation criterion that significantly affects material flow around the tool tip. In this study a mesh-free method viz. smoothed particles hydrodynamics (SPH) is implemented to simulate shear localization in the chip while machining hardened steel. Unlike other SPH models developed by some researchers, this model is based on a renormalized formulation that can consider frictional stresses along the tool-chip interface giving a realistic chip shape and material flow. SPH models with different cutting parameters are compared with the traditional FE models and it has been found that the SPH models are good for predicting shear localized chips and do not need any geometric or mesh-based chip separation criteria.     

A comparative study of conventional and supercritical fluid extraction methods for the recovery of secondary metabolites from <Emphasis Type="Italic">Syzygium campanulatum</Emphasis> Korth

Syzygium campanulatum Korth is a plant, which is a rich source of secondary metabolites (especially flavanones, chalcone, and triterpenoids). In our present study, three conventional solvent extraction (CSE) techniques and supercritical fluid extraction (SFE) techniques were performed to achieve a maximum recovery of two flavanones, chalcone, and two triterpenoids from S. campanulatum leaves. Furthermore, a Box-Behnken design was constructed for the SFE technique using pressure, temperature, and particle size as independent variables, and yields of crude extract, individual and total secondary metabolites as the dependent variables. In the CSE procedure, twenty extracts were produced using ten different solvents and three techniques (maceration, soxhletion, and reflux). An enriched extract of five secondary metabolites was collected using n-hexane:methanol (1:1) soxhletion. Using food-grade ethanol as a modifier, the SFE methods produced a higher recovery (25.5%?84.9%) of selected secondary metabolites as compared to the CSE techniques (0.92%?66.00%).     

Development and Initial Validation of the Narcissistic Personality Questionnaire for Children: A preliminary investigation using school‐based Asian samples

The Narcissistic Personality Questionnaire for Children (NPQC) is a brief self‐report scale for measuring narcissism in children. In Study 1, a factor analysis on 370 children’s NPQC scores revealed four factors that were labeled superiority, exploitativeness, self‐absorption, and leadership. Study 2 established convergent and discriminant validities of the NPQC. NPQC scores were positively correlated with need for power/dominance, self‐esteem, aggression, and need for achievement, and unrelated to life satisfaction, as expected. Further support for the validity of the NPQC was obtained when findings were consistent with attachment theory’s interpretation of narcissistic children’s self‐perceptions. Study 3 investigated the temporal stability of scores. Results from Studies 1 and 3 show the NPQC to be an internally consistent measure (Cronbach alpha = .81) and to have adequate test–retest reliability (r = .81). Implications for the education of aggressive and narcissistic children are discussed.