Exogenous System Research Articles

Disturbance‐observer‐based‐control and L 2 − L ∞ resilient control for Markovian jump non‐linear systems with multiple disturbances and its application to single robot arm system

In this study, the problem of disturbance-observer-based-control (DOBC) and L 2−L ∞ resilient control for Markovian jump non-linear systems with multiple disturbances is investigated. The disturbances are divided into two parts: one part is produced by an exogenous system and the other part is supposed to lie in the space of L 2[0,∞). A disturbance observer is designed to estimate the first one, and the disturbance estimation is introduced into L 2−L ∞ resilient state feedback control law. Hence, by combining DOBC and L 2−L ∞ control methods, a composite anti-disturbance controller is designed to attenuate and reject two kinds of disturbances. Some sufficient conditions are obtained by using Lyapunov function method and linear matrix inequalities technique. Finally, an application example is given to illustrate the effectiveness of the main algorithm.

Alterations of the immunosuppressive IL4I1 enzyme activity induced by naturally occurring SNP/mutations

The immunosuppressive phenylalanine oxidase interleukin 4-induced gene 1 (IL4I1), primarily produced by antigen-presenting cells, inhibits T-cell proliferation and promotes the generation of Foxp3(+) regulatory T cells in vitro. Highly expressed by tumour-associated macrophages from human cancers, IL4I1 has a potential role in immune evasion from the anti-tumour immune response. We have reviewed single-nucleotide polymorphisms (SNPs) and mutations described for the exon 4 of the IL4I1 isoform 1, which is expressed in lymphoid tissue. Two of them were expressed in an exogenous system to analyse their effect on the enzymatic activity. The N92D SNP leads to a hyperactive enzyme, while the R102G mutation is hypomorphic. Moreover, we show that IL4I1 activity is not only directed against phenylalanine, as initially described, but also at a lower level against arginine. These data pave the way to more extensive analyses of the mutational state of IL4I1 in pathological conditions such as cancer, where its participation in immune system dysfunctions may have therapeutic implications.

Composite anti-disturbance control for a class of uncertain nonlinear systems via a disturbance observer

A new anti-disturbance control scheme is proposed for a class of nonlinear systems subjected to multi-source disturbances. The uncertain multi-source disturbances are classified into two parts; one is the harmonic and constant disturbance with partial known information, which can be formulated by an exogenous system, and the other consists of unknown time-varying disturbances. The nonlinear disturbance observer (NDO) is constructed to estimate the first kind of disturbance. By integrating the NDO with an adaptive backstepping technique, a novel composite anti-disturbance control scheme is proposed for the nonlinear systems. Then the stability analysis of the closed-loop system is presented. The simulation of a numerical example is given to demonstrate the effectiveness of the proposed results.

Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.

The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.

Emergence of the default-mode network from resting-state to activation-state in reciprocal social interaction via eye contact.

The default-mode network has been identified as a resting state BOLD response that is often associated with self-referential or sensory task-passive processes. Many recent studies reveal that this vaguely defined network often plays an essential role in many pervasive mental diseases. By taking advantage of the recent development of dyadic fMRI, this study presents the initial experimental evidence that the default-mode network emerges from resting-state to activation-state in social interaction during live eye contact. Moreover, by comparing the BOLD responses between dyadic fMRI and monadic fMRI, it suggests that live eye contact excites empathy networks in the exogenous system which further activates the default mode network in endogenous system; whereas seeing eyes in face pictures activates completely different brain responses in which the default-mode network remains in resting-state.

Dissipative lag synchronization of chaotic Lur'e systems with unknown disturbances

This paper is concerned with the problem of dissipative lag synchronization (LS) for two identical Lur'e systems with unknown external disturbances. The disturbances are supposed to be generated by the exogenous systems with and without time-delay. Based on the disturbance-observer-based control method, the linear matrix inequality technique and the dissipativity theory, the disturbance observers are developed to ensure the boundedness of the disturbance error dynamics and the dissipativity of the resultant LS error system. By using the sliding-mode control (SMC) approach, an integral-type sliding surface function is constructed and a dissipative SMC law is established to render the disturbance rejection and realize LS between the master and slave systems, and an integral sliding-mode controller is designed to guarantee the reachability of the specified sliding surface. Finally, the Chua's circuit is used as a numerical example to illustrate the effectiveness of the proposed method.

Output Regulation of Nonlinear Systems With Application to Roll-to-Roll Manufacturing Systems

This paper deals with the problem of synthesizing feedforward control to aid the regulation of output of a nonlinear system in the presence of partially known exogenous inputs. The problem appears in many engineering applications including Roll-to-Roll (R2R) manufacturing systems. Currently known methods for this problem either require the solution of a constrained partial differential equation or the preview information of the signal to be tracked. The novelty of this paper lies in synthesizing feedforward control as the solution of a system of differential-algebraic equations, which is considerably less complex and suitable for practical implementation. In this paper, we consider the problem of regulating the output while rejecting the disturbances and apply it to R2R manufacturing systems. The problem of tracking reference signals can also be handled with the suggested technique. We assume that the disturbance signal is the output of a known exogenous system with unknown initial conditions. A parameter identification scheme to estimate the unknown initial conditions is developed. The proposed technique is successfully applied to control of web tension in a large R2R machine which mimics most of the features of industrial R2R machines and contains real-time hardware and software that is used in industrial practice. Extensive experiments were conducted to evaluate the proposed scheme for web tension control under various experimental conditions, including different web speeds and materials. We will present and discuss the representative experimental results with the proposed technique and provide a comparison with an industrial PI control scheme to highlight the benefits of using the proposed scheme.

Dual logic and cerebral coordinates for reciprocal interaction in eye contact.

In order to scientifically study the human brain’s response to face-to-face social interaction, the scientific method itself needs to be reconsidered so that both quantitative observation and symbolic reasoning can be adapted to the situation where the observer is also observed. In light of the recent development of dyadic fMRI which can directly observe dyadic brain interacting in one MRI scanner, this paper aims to establish a new form of logic, dual logic, which provides a theoretical platform for deductive reasoning in a complementary dual system with emergence mechanism. Applying the dual logic in the dfMRI experimental design and data analysis, the exogenous and endogenous dual systems in the BOLD responses can be identified; the non-reciprocal responses in the dual system can be suppressed; a cerebral coordinate for reciprocal interaction can be generated. Elucidated by dual logic deductions, the cerebral coordinate for reciprocal interaction suggests: the exogenous and endogenous systems consist of the empathy network and the mentalization network respectively; the default-mode network emerges from the resting state to activation in the endogenous system during reciprocal interaction; the cingulate plays an essential role in the emergence from the exogenous system to the endogenous system. Overall, the dual logic deductions are supported by the dfMRI experimental results and are consistent with current literature. Both the theoretical framework and experimental method set the stage to formally apply the scientific method in studying complex social interaction.

A Comparative Study of Linear ARX and Nonlinear ANFIS Modeling of an Electro-Hydraulic Actuator System

The existence of a high degree of nonlinearity in Electro-Hydraulic Actuator (EHA) has imposed a challenge in development of a representable model for the system such as that significant control performance can be proposed. In this work, linear Autoregressive with Exogenous (ARX) model and nonlinear Adaptive Neuro-Fuzzy Inference System (ANFIS) model of an EHA system are obtained based on the mathematical model of the system. Linear ARX modeling technique has been widely applied on EHA system and satisfying result has been obtained. On the other hand, ANFIS modeling technique can model nonlinear system at high accuracy. Both models are validated offline using data set obtained and using different stimulus signals when doing online validation. Offline validation test shows that ANFIS model has 99.37% best fitting accuracy, which is more accurate than 93.75% in ARX model. ARX model fails in some online validation tests, while ANFIS model has been consistently accurate in all tests with RMSE lower than 0.25.

Dual Logic and Dual Neural Basis for Reciprocal Social Interaction

Event Abstract Back to Event Dual Logic and Dual Neural Basis for Reciprocal Social Interaction Ray Lee1* 1 Princeton University, Neuroscience Institute, United States Most social interaction studies are limited by both insufficient dyadic test instruments and entwined social and affective cerebral responses. To address these two issues, I not only pioneered the dyadic fMRI (dfMRI) method (1), but also developed a dual logic to deductively untwine the reciprocal social state and non-reciprocal affective state in BOLD responses. A dual neural basis of exogenous-endogenous system (2) is deductively and experimentally derived. In addition, the dual logic symbolically formulated emergence of the endogenous process and predicted the default mode network (DMN). In the dfMRI protocol (1), the task A and B are for dyad opening and closing their eyes either simultaneously or alternately. The rigorous propositional logic deductions suggest that: A-B represents the exogenous reciprocal state; B-A represents the superposition of the endogenous reciprocal and DMN states; the nonreciprocal exogenous and endogenous states are suppressed. The theoretical predictions are verified by the dfMRI experimental data. Total 19 pairs of subjects were enrolled for dfMRI. The data processing was performed by the FSL (Oxford Univ., UK). The paired t-test comparison results show that the exogenous system (A-B) is mostly imitation-empathy networks; the endogenous system mostly consists of mentalization networks. Here the inference threshold for clustering and atlas labeling is Z>2.3 and p<0.05. The lateral asymmetry is clearly evident, where A-B and B-A are right and left dominant respectively, and DMN is embedded in B-A. Dual neural basis for reciprocal social interaction is derived based on dyadic fMRI experiments and propositional dual logic deduction, which is consistent with most of literature. It provides a foundation for further studying multiple parallel processes in social interaction. (1) Lee, RF, et al (2012). Magn Reson Med, v. 68, p. 1087 (2) Lieberman, MD (2007). Annual Rev Psy, v. 58, p. 259 Keywords: Default Mode Network, Dyadic fMRI, dual logic, reciprocal social interaction, dual neural basis Conference: XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014. Presentation Type: Poster Topic: Methods Development Citation: Lee R (2015). Dual Logic and Dual Neural Basis for Reciprocal Social Interaction. Conference Abstract: XII International Conference on Cognitive Neuroscience (ICON-XII). doi: 10.3389/conf.fnhum.2015.217.00278 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Feb 2015; Published Online: 24 Apr 2015. * Correspondence: Dr. Ray Lee, Princeton University, Neuroscience Institute, Princeton, United States, rl2946@columbia.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ray Lee Google Ray Lee Google Scholar Ray Lee PubMed Ray Lee Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Open-loop synchronization: uncoupled oscillators may show synchronized motion

In this paper, synchronous behaviour is induced in a group of identical dynamical oscillators by applying a synchronizing signal, which is generated by an exogenous system. Specifically, a second order dynamical system driven by a pulse train is designed. The output of this system is further applied to a group of identical oscillatory systems, forcing them to synchronize. The novelty in this approach is that the synchronizing signal does not require any information from the dynamics of the systems to synchronize, i.e. the systems are uncoupled and they synchronize not because of an interaction between them but because of the influence of the synchronizing exogenous signal. In the analysis, the proposed synchronizing signal is applied to a set of chaotic systems, to a set of biological systems, and to a set of mechanical oscillators.

Observer-Based Bounded Control for Discrete Time-Delay Uncertain Nonlinear Systems

A bounded controller is proposed for a class of uncertain discrete time-delay systems with nonlinearity and disturbance based on state estimator and disturbance observer technique. A state estimator is developed to estimate the unmeasured system state vector. Suppose that the disturbance is generated by an exogenous system; a disturbance observer is designed to estimate the unknown disturbance. The parameters of the state estimator and the disturbance observer are calculated by solving linear matrix inequalities (LMIs). By applying the outputs of the state estimator and the disturbance observer, the sufficient condition for the existence of the bounded controller is derived based on an appropriate Lyapunov function candidate. Under the developed bounded controller, the stability of the closed-loop system can be guaranteed. Simulation examples are provided to show the effectiveness of the proposed bounded control scheme.

Single molecule study of non-specific binding kinetics of LacI in mammalian cells.

Many key cellular processes are controlled by the association of DNA-binding proteins (DBPs) to specific sites. The kinetics of the search process leading to the binding of DBPs to their target locus are largely determined by transient interactions with non-cognate DNA. Using single-molecule microscopy, we studied the dynamics and non-specific binding to DNA of the Lac repressor (LacI) in the environment of mammalian nuclei. We measured the distribution of the LacI-DNA binding times at non-cognate sites and determined the mean residence time to be τ(1D) = 182 ms. This non-specific interaction time, measured in the context of an exogenous system such as that of human U2OS cells, is remarkably different compared to that reported for the LacI in its native environment in E. coli (<5 ms). Such a striking difference (more than 30 fold) suggests that the genome, its organization, and the nuclear environment of mammalian cells play important roles on the dynamics of DBPs and their non-specific DNA interactions. Furthermore, we found that the distribution of off-target binding times follows a power law, similar to what was reported for TetR in U2OS cells. We argue that a possible molecular origin of such a power law distribution of residence times is the large variability of non-cognate sequences found in the mammalian nucleus by the diffusing DBPs.

Tracking control of overactuated systems with actuator faults

A novel scheme for fault-tolerant control is proposed in this paper. The geometric theory of output regulation is used to solve the total failure of actuators, under the assumption that redundancy is available in the systems. In the case that the reference signals are generated by a finite dimensional exogenous system, it is shown that, under standard assumptions, this problem is solvable if and only if a certain partial differential equation is solvable. Once a solution of this equation is available, a feedback law which solves the problem can easily be constructed. A numerical example is presented to illustrate the effectiveness of proposed approach.

Disturbance‐observer‐based control &amp; ℋ ∞ control for non‐linear Markovian jump singular systems with multiple disturbances

This study addresses the Problem of composite hierarchical anti-disturbance control [disturbance-observer-based controllers (DOBC) and ℋ∞ control] for Markovian jump singular systems with non-linearity and two types of disturbances (the first is generated by an exogenous system and the latter is norm-bounded). The authors’ attention is focused on the design of a disturbance observer to estimate the first disturbance, and then on constructing a composite hierarchical control scheme such that the solution to the composite system is unique and exists, the composite system can be guaranteed to be stochastically admissible, and different types of disturbances can be attenuated and rejected simultaneously. By constructing a proper stochastic Lyapunov–Krasovskii functional, sufficient conditions for the existence of the desired DOBCs are established. Finally, a numerical eEEExample is provided to show the effectiveness of the proposed approaches.

Cytological assays for the evaluation of genotoxicity in plants: A review

Plants model are recognized as excellent genetic models to detect environ-mental mutagens and are frequently used in xenomoitoring studies. Several assays such as chromosomal aberration assay, micronucleus assay and comet assay are used for detecting the mutagenicity, cytotoxicity and genotoxicity of environmental pollutants. It is easily handled and has advantages over other short-term tests that require pervious preparation of tested samples as well as the addition of exogenous metabolic system. Plants model also enables to evaluate different end points such as chromosomal aberration assay (CAA), micronucleus assay (MNA) and comet assay (CA) that have been used to detect genotoxicity of environmental pollutants. In addition, plants model provides important information to evaluate action mechanisms of an agent about its effects on the genetic material (clastogenic and/or aneugenic effects). It has been widely used to assess the impacts caused by xenobiotic, characterizing an important tool for environmental monitoring studies. The present review describes the two important assays using plant models that are appropriate and efficient cytogenetic materials for the detection of geno-toxicity of environmental pollutants.

A robust time delay auto-regressive exogenous fuzzy inference system for real-time estimation of catalyst temperature over engines coldstart operation: a multiobjective implementation scenario

In the current investigation, the authors propose an intelligent real-time system to dynamically simulate the catalyst temperature in automotive engines over the coldstart period. In general, the behavior of an engine during the first few minutes of its operation, namely the coldstart period, is highly transient and nonlinear. However, it is important to the engineers of automotive industry to develop advanced simulation techniques capable of capturing the engine system’s behavior during coldstart periods. The main motivation behind such a fact emanates in the pursuit of making successful strides towards decreasing the amount of unburned hydrocarbon emissions (HCs) of the engine. Catalytic convertors play a pivotal role in reducing the amount of this emitted pollutant. Therefore, here, the authors develop a knowledge based intelligent identification system, based on the integration of a low-level fuzzy identification machine (FIM) identifier and a hyper-level multiobjective optimizer, to monitor the catalyst temperature over the coldstart period for a given automotive engine system. In the current investigation, the authors propose the use of synchronous self-learning Pareto strategy for the multi-objective optimization of the architecture of FIM. To suit the intelligent scheme for online applications, the authors capture the required database using the concept of nonlinear auto-regressive exogenous systems. The developed intelligent approach can be used as a real-time soft sensor to observe the state of the catalytic convertor and send the required data to the coldstart controller. To ensure the efficacy of the resulting time delay FIM framework, it is used for capturing the catalyst temperature in three different experimental conditions. Through a comparative numerical study, it is demonstrated that the proposed soft sensor can be efficiently used for real-time estimations of the catalyst temperature. Besides, the results let us make sure that intelligent approaches have an aptitude to be effectively used as real-time observers instead of expensive commercial sensors. Generally, the results of the current investigation substantiates the authenticity of advanced computational approaches for coping with the considered identification problem, to help resolving one of the challenging issues in the field of automotive engineering, that is, the coldstart HC emission reduction.

Elegant anti-disturbance control for nonlinear systems based on a robust disturbance observer

A new elegant anti-disturbance control and estimation strategy is presented for a class of nonlinear systems subject to multiple disturbances. As a class of strong-coupled nonlinear systems, the models have measurement error, friction, varying load, and unmodelled dynamics, which can be characterized as two types of disturbances in this framework. One is supposed to be generated by an exogenous system with uncertainty, which represents the disturbance with partial known information. The other is a bounded external disturbance in the H2-norm. The nonlinear robust disturbance observer (DO) based on regional pole placement theory is constructed separately from the controller design to estimate and reject the first type of disturbance, and terminal sliding-mode (TSM) control is used to attenuate the second type of disturbance. By integrating the nonlinear robust DO with TSM control, a new elegant anti-disturbance control scheme based on a robust DO is proposed for a kind of nonlinear system, which can further improve the ability of anti-disturbance for nonlinear systems. Simulations are given to demonstrate the effectiveness of the proposed method.

Hybrid model predictive control for flotation plants

Development of control strategies for large-scale processes has led to formulate novel methodologies to consider the global performance of a plant, facilitating the design, validation and evaluation of more complex control strategies. This paper describes a hybrid dynamic simulator for a flotation circuit with one production line composed by one cell and two banks in series, calibrated with industrial data. This simulator allows to represent a real plant behavior, facilitating the process of extracting input–output data. A PieceWise AutoRegresive eXogenous (PWARX) system is obtained from simulated plant by applying identification techniques for different operating conditions. A Hybrid Model Predictive Control (HMPC) methodology based on PWARX models has been developed and evaluated showing a good performance. Simulation results show that the proposed methodology is suitable for modelling the behavior of a flotation process and its control stage by minimizing the tracking error in the final tail grade.

Observer-based optimal fault-tolerant control for offshore platforms

This paper is concerned with an observer-based optimal fault-tolerant control for an offshore steel jacket platform. The dynamic characteristics of the actuator faults under consideration are formulated by an exogenous system. Based on a dynamic fault observer designed, a feedforward and feedback optimal fault-tolerant controller is developed to improve the reliability of the offshore platform. The controller can be obtained by solving an algebraic Riccati equation and Sylvester equations, respectively. It is shown through simulation results that the proposed control scheme is effective to guarantee the reliability of the offshore platform with the actuator faults. The vibration amplitudes of the displacement, the velocity of the offshore platform and the required control force under the proposed fault-tolerant controller can be reduced significantly.