Identification of nonlinear systems using hybrid functions

Most real systems have nonlinear behavior and thus model linearization may not produce an accurate representation of them. This paper presents a method based on hybrid functions to identify the parameters of nonlinear real systems. A hybrid function is a combination of two groups of orthogonal functions: piecewise orthogonal functions (e.g. Block-Pulse) and continuous orthogonal functions (e.g. Legendre polynomials). These functions are completed with an operational matrix of integration and a product matrix. Therefore, it is possible to convert nonlinear differential and integration equations into algebraic equations. After mathematical manipulation, the unknown linear and nonlinear parameters are identified. As an example, a mechanical system with single degree of freedom is simulated using the proposed method and the results are compared against those of an existing approach.<br /

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.<br /

Prognostic significance of endogenous adhesion/growth-regulatory lectins in lung cancer

Objective: To determine the expression of endogenous adhesion/growth-regulatory lectins and their binding sites using labeled tissue lectins as well as the binding profile of hyaluronic acid as an approach to define new prognostic markers. Methods: Sections of paraffin-embedded histological material of 481 lungs from lung tumor patients following radical lung excision processed by a routine immunohistochemical method (avidin-biotin labeling, DAB chromogen). Specific antibodies against galectins-1 and - 3 and the heparin-binding lectin were tested. Staining by labeled galectins and hyaluronic acid was similarly visualized by a routine protocol. After semiquantitative assessment of staining, the results were compared with the pT and pN stages and the histological type. Survival was calculated by univariate and multivariate methods. Results: Binding of galectin-1 and its expression tended to increase, whereas the parameters for galectin-3 decreased in advanced pT and pN stages at a statistically significant level. The number of positive cases was considerably smaller among the cases with small cell lung cancer than in the group with non-small-cell lung cancer, among which adenocarcinomas figured prominently with the exception of galectin-1 expression. Kaplan-Meier computations revealed that the survival rate of patients with galectin-3-binding or galectin-1-expressing tumors was significantly poorer than that of the negative cases. In the multivariate calculations of survival lymph node metastases ( p < 0.0001), histological type ( p = 0.003), galectin-3-binding capacity ( p = 0.01), galectin-3 expression ( p = 0.03) and pT status ( p = 0.003) proved to be independent prognostic factors, not correlated with the pN stage. Conclusion: The expression and the capacity to bind the adhesion/growth regulatory galectin-3 is defined as an unfavorable prognostic factor not correlated with the pTN stage. Copyright (C) 2005 S. Karger AG, Basel

GRAPH THEORETICAL METHODS TO STUDY CONTROLLABILITY AND LEADER SELECTION FOR DEAD-TIME SYSTEMS Communicated by Alireza Abdollahi

Abstract. In this article a graph theoretical approach is employed to study some specifications of dynamic systems with time delay in the inputs and states, such as structural controllability and observability. First, the zero and non-zero parameters of a proposed system have been determined, next the general structure of the system is presented by a graph which is constructed by non-zero parameters. The structural controllability and observability of the system is investigated using the corresponding graph. Our results are expressed for multi-agents systems with dead-time. As an application we find a minimum set of leaders to control a given multi-agent system

Robust Adaptive Actuator Failure Compensation of MIMO Systems with Unknown State Delays

In this paper, a robust adaptive actuator failure compensation control scheme is proposed for a class of multi input multi output linear systems with unknown time-varying state delay and in the presence of unknown actuator failures and external disturbance. The adaptive controller structure is designed based on the SPR-Lyapunov approach to achieve the control objective under the specific assumptions and the SDU factorization method of the high frequency gain matrix is employed to drive the suitable form of the error equation.&nbsp; The two component controller structure with an integral term is used in order to compensate the effect of unknown state delay and external disturbance. Using a suitable Lyapunov-Krasovskii functional, it is shown that despite existing external disturbance and actuator failures, all closed loop signals are bounded and the plant Output asymptotically tracks the output of a stable reference model. Simulation results are provided to demonstrate the effectiveness of the proposed theoretical results

Simultaneous Actuator Fault Estimation and Fault-tolerant Tracking Control for Multi-agent Systems: A Sliding-mode Observer-based Approach

This study is concerned with the design of a distributed simultaneous fault estimation and fault-tolerant control scheme for linear multi-agent systems subject to actuator faults. For each agent, a sliding-mode observer-based estimator/controller module is proposed that uses the available local relative output measurements and the information transmitted from the neighboring agents. By considering the (Formula presented.) performance index and using the linear matrix inequality technique, the parameters of the observers are designed such that the fault estimation is robust against disturbances and at the same time, a robust leader-following mission in the presence of actuator fault is guaranteed. As the fault estimator and fault tolerant controller are integrated in the proposed strategy, there is no need for separate design of these units. Moreover, the proposed method improves the existing fault estimation techniques in terms of both complexity and performance. Two simulation examples are presented to illustrate the effectiveness of the proposed methodology.Scopu

Actuator Fault Estimation for Multi-agent Systems: A Sliding-mode Observer-based Approach

This study is concerned with the design of a distributed fault estimation scheme for linear multi-agent systems subject to actuator faults. For each agent, a sliding-mode observer-based estimator module is proposed that uses the available local relative output measurements and the information transmitted from the neighboring agents. By considering the H? performance index and using the linear matrix inequality technique, the parameters of the observers are designed such that the fault estimation is robust against disturbances. The proposed method improves the existing fault estimation techniques in terms of both complexity and performance. A simulation example is presented to illustrate the effectiveness of the proposed methodology. - 2019 IEEE.Scopu

A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties

In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers

Distributed simultaneous fault detection and leader-following consensus control for multi-agent systems

In this paper, the problem of distributed simultaneous fault detection and leader-following consensus control (SFDLCC) in a multi-agent network is investigated. In the proposed method, instead of designing two separate units for fault detection and control objectives, a single module is used that conducts both tasks. Based on the extended linear matrix inequality (LMI) technique, an SFDLCC module is designed for each agent which utilizes both the data received from the neighboring agents as well as the available local relative measurements. The SFDLCC unit in each agent generates both the control input and the residual signal such that the effect of the unknown inputs including faults, disturbances and noises on the tracking error and the effect of disturbances and noises on the residual signal are attenuated using finite frequency H? performance index. On the other hand, the effect of fault inputs on the residual signals is enhanced using the finite frequency H? performance index. Moreover, in the proposed algorithm, the group can not only isolate the faulty agent but also determine whether the fault is in the sensors or actuators. Finally, to illustrate the effectiveness of the proposed methodology, a simulation study is provided.Scopu