Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: stability and moving-horizon approximations

Stability results are given for a class of feedback systems arising from the regulation of time-varying discrete-time systems using optimal infinite-horizon and moving-horizon feedback laws. The class is characterized by joint constraints on the state and the control, a general nonlinear cost function and nonlinear equations of motion possessing two special properties. It is shown that weak conditions on the cost function and the constraints are sufficient to guarantee uniform asymptotic stability of both the optimal infinite-horizon and movinghorizon feedback systems. The infinite-horizon cost associated with the moving-horizon feedback law approaches the optimal infinite-horizon cost as the moving horizon is extended.

Banking psychographics: an Indian empirical study

India has been witnessing an economic boom which fuelling a huge growth in the financial sector especially the banks. The spending power and consumerism has been increasing along with the growth in GDP. The numbers of banks are around 3000 (data according to Reserve Bank of India). With a population base of close to 1.1 billion and a diverse culture that has been dictating the mindset and lifestyle of the population, it has been a challenge for the banks to understand the customer better and hence a the need of the hour is a proper psychographic study of retail banking customers.

Enhanced J-protein interaction and compromised protein stability of mtHsp70 variants lead to mitochondrial dysfunction in Parkinsons disease

Parkinsons disease (PD) is the second most prevalent progressive neurological disorder commonly associated with impaired mitochondrial function in dopaminergic neurons. Although familial PD is multifactorial in nature, a recent genetic screen involving PD patients identified two mitochondrial Hsp70 variants (P509S and R126W) that are suggested in PD pathogenesis. However, molecular mechanisms underlying how mtHsp70 PD variants are centrally involved in PD progression is totally elusive. In this article, we provide mechanistic insights into the mitochondrial dysfunction associated with human mtHsp70 PD variants. Biochemically, the R126W variant showed severely compromised protein stability and was found highly susceptible to aggregation at physiological conditions. Strikingly, on the other hand, the P509S variant exhibits significantly enhanced interaction with J-protein cochaperones involved in folding and import machinery, thus altering the overall regulation of chaperone-mediated folding cycle and protein homeostasis. To assess the impact of mtHsp70 PD mutations at the cellular level, we developed yeast as a model system by making analogous mutations in Ssc1 ortholog. Interestingly, PD mutations in yeast (R103W and P486S) exhibit multiple in vivo phenotypes, which are associated with omitochondrial dysfunction', including compromised growth, impairment in protein translocation, reduced functional mitochondrial mass, mitochondrial DNA loss, respiratory incompetency and increased susceptibility to oxidative stress. In addition to that, R103W protein is prone to aggregate in vivo due to reduced stability, whereas P486S showed enhanced interaction with J-proteins, thus remarkably recapitulating the cellular defects that are observed in human PD variants. Taken together, our findings provide evidence in favor of direct involvement of mtHsp70 as a susceptibility factor in PD.

Dynamics and Regulation of RecA Polymerization and De-Polymerization on Double-Stranded DNA

The RecA filament formed on double-stranded (ds) DNA is proposed to be a functional state analogous to that generated during the process of DNA strand exchange. RecA polymerization and de-polymerization on dsDNA is governed by multiple physiological factors. However, a comprehensive understanding of how these factors regulate the processes of polymerization and de-polymerization of RecA filament on dsDNA is still evolving. Here, we investigate the effects of temperature, pH, tensile force, and DNA ends (in particular ssDNA overhang) on the polymerization and de-polymerization dynamics of the E. coli RecA filament at a single-molecule level. Our results identified the optimal conditions that permitted spontaneous RecA nucleation and polymerization, as well as conditions that could maintain the stability of a preformed RecA filament. Further examination at a nano-meter spatial resolution, by stretching short DNA constructs, revealed a striking dynamic RecA polymerization and de-polymerization induced saw-tooth pattern in DNA extension fluctuation. In addition, we show that RecA does not polymerize on S-DNA, a recently identified novel base-paired elongated DNA structure that was previously proposed to be a possible binding substrate for RecA. Overall, our studies have helped to resolve several previous single-molecule studies that reported contradictory and inconsistent results on RecA nucleation, polymerization and stability. Furthermore, our findings also provide insights into the regulatory mechanisms of RecA filament formation and stability in vivo.

Single network adaptive critic aided dynamic inversion for optimal regulation and command tracking with online adaptation for enhanced robustness

To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a pre-synthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system. Copyright (C) 2013 John Wiley & Sons, Ltd.