1,256 publications from this institution
In this paper, some small-gain conditions are presented for stochastic network systems which can describe many large-scale systems with interconnections, nonlinear behaviors, uncertainties and random disturbances. One subsystem is selected as monitor with the requirement that the gains to other systems are smooth concave functions. The relations of members under the supervise of the monitor are described as bilateral plus multilateral relations of gains. For the deterministic case, the requirement on the monitor can be removed. To demonstrate the power of this result, the small-gain conditions cover interconnected system with two subsystems as a special case. Compared with the existing results, the main character is that the forward completion of system and ultimate uniform boundedness of input are removed from conditions of small-gain theorems.
This chapter presents several important definitions and lemmas needed in the study of fractional calculus theory and system stability theory, providing essential theoretical support for subsequent research. Fractional calculus extends the concept of integer-order differentiation and integration to noninteger orders, offering a powerful tool for modeling various physical and engineering processes. System stability theory, on the other hand, addresses the behavior of dynamic systems over time, ensuring that they remain within desired bounds and do not exhibit undesirable behavior. By laying down the foundational concepts and theoretical constructs in these areas, this chapter serves as a critical reference point for further exploration and application in advanced research. The definitions and lemmas provided here are crucial for developing a deeper understanding and for solving complex problems in these fields.
This paper investigates finite-time (FT) stability and stabilization problems for a class of switched linear systems with polytopic uncertainties. Both stable and unstable subsystems are considered to coexist in the system, and a new concept of extended FT stability is proposed as the first attempt. A stability criterion is first established, where the admissible maximum switching number is obtained while ensuring extended FT stability of switched linear systems with time-varying delays under a given maximum ratio between the running time of unstable subsystems and the running time of stable subsystems. Sufficient conditions on the existence of desired memory state-feedback controllers are then developed. A numerical example and a class of servomechanism systems are given, respectively, to illustrate the effectiveness and validity of the developed techniques with time-varying delays and without time delay.
Engineering, IITRAM, Ahmedabad and Department of Mechanical Engineering, IIT Bhilai.This conference provides a forum for discussion on issues, concepts, skill development and possible innovations in the mechanical infrastructure sector.ICRAM-2022 aims at bringing the best technical minds working in the field of mechanical engineering on a common platform to share their knowledge of technical expertise, experience and forthcoming challenges in the development of infrastructure of the country.
This paper presents mathematical logarithmic, statistical linear regression, and neural models capable of predicting maximum A-weighed noise level (L A,max) for the Tehran–Karaj express train. The models have been developed upon the basis of the measurements from sampling locations at distances of 25m, 45m, and 65m from the centreline of the track and at a height of 1.5m. In the next step, the predictive capability of the models have been tested on the data associated with the sampling locations, situated, respectively at distances of 35 and 55m from the centreline of the track at a height of 1.5m. The non-parametric tests i.e. two-related samples Wilcoxon, and two-independent samples Kolmogorov–Smirnov, carried out, respectively for training and testing steps, indicate satisfactory results. In the final step the non-parametric k-related samples Friedman test detects no significant differences amongst the absolute testing set error of the models.
The complex dynamics that characterize hydraulic systems make it difficult for the control design to achieve prescribed goals in an efficient manner. In this paper, we present the design and analysis of a robust nonlinear controller for a nonlinear hydraulic-mechanical (NHM) system. The system consists of an electrohydraulic servo valve and two hydraulic cylinders. Specifically, by considering a part of the dynamics of the NHM system as a norm-bounded uncertainty, two adaptive controllers are developed based on the backstepping technique that ensure the tracking error signals asymptotically converge to zero despite the uncertainties in the system according to the Barbalat lemma. The resulting controllers are able to take into account the interval uncertainties in Coulomb friction parameters and in the internal leakage parameters in the cylinders. Two adaptation laws are obtained by using the Lyapunov functional method and inequality techniques. Simulation results demonstrate the performance and feasibility of the proposed method.
Convolutional neural networks (CNNs) are considered black boxes due to their robust nonlinear fitting capability. In the context of fault diagnosis for rotating machinery, it may happen that a standard CNN makes a final decision based on a mixture of significant and insignificant features, therefore, it is required to establish a trustworthy intelligence fault diagnosis model with the controllable feature learning capability to identify fault types. In this paper, an explainable intelligence fault diagnosis framework is proposed to recognize the fault signals, using data obtained through short-time Fourier transformation, which is easily modified from a standard CNN. The post hoc explanation method is used to visualize the features the model learned from a signal. The experimental results show that the proposed explainable intelligence fault diagnosis framework provides 100% testing accuracy and visualizations, the Average Drop and the Average Increase from a classification activation mappings method demonstrate the interpretability of the proposed framework.
Continuous-time semi-Markovian jump neural networks (semi-MJNNs) are those MJNNs whose transition rates are not constant but depend on the random sojourn time. Addressing stochastic synchronization of semi-MJNNs with time-varying delay, an improved stochastic stability criterion is derived in this paper to guarantee stochastic synchronization of the response systems with the drive systems. This is achieved through constructing a semi-Markovian Lyapunov-Krasovskii functional together as well as making use of a novel integral inequality and the characteristics of cumulative distribution functions. Then, with a linearization procedure, controller synthesis is carried out for stochastic synchronization of the drive-response systems. The desired state-feedback controller gains can be determined by solving a linear matrix inequality-based optimization problem. Simulation studies are carried out to demonstrate the effectiveness and less conservatism of the presented approach.
In this paper, we investigate the design of distributed damping systems (DDSs) for the overall seismic protection of multiple adjacent buildings. The considered DDSs contain interstory dampers implemented inside the buildings and also interbuilding damping links. The design objectives include mitigating the buildings seismic response by reducing the interstory-drift and story-acceleration peak-values and producing small interbuilding approachings to decrease the risk of interbuilding collisions. Designing high-performance DDS configurations requires determining convenient damper positions and computing proper values for the damper parameters. That allocation-tuning optimization problem can pose serious computational difficulties for large-scale multibuilding systems. The design methodology proposed in this work—(i) is based on an effective matrix formulation of the damped multibuilding system; (ii) follows an H ∞ approach to define an objective function with fast-evaluation characteristics; (iii) exploits the computational advantages of the current state-of-the-art genetic algorithm solvers, including the usage of hybrid discrete-continuous optimization and parallel computing; and (iv) allows setting actuation schemes of particular interest such as full-linked configurations or nonactuated buildings. To illustrate the main features of the presented methodology, we consider a system of five adjacent multistory buildings and design three full-linked DDS configurations with a different number of actuated buildings. The obtained results confirm the flexibility and effectiveness of the proposed design approach and demonstrate the high-performance characteristics of the devised DDS configurations.
This paper presents a novel method to address a Proportional Integral observer design for the actuator and sensor faults estimation based on Takagi–Sugeno fuzzy model with unmeasurable premise variables. The faults are assumed as time-varying signals whose kth time derivatives are bounded. Using Lyapunov stability theory and L 2 performance analysis, sufficient design conditions are developed for simultaneous estimation of states and time-varying actuator and sensor faults. The Proportional Integral observer gains are computed by solving the proposed conditions under Linear Matrix Inequalities constraints. A simulation example is provided to illustrate the effectiveness of the proposed approach.
The global dissipative and multipeakon dissipative behavior of the two-component Camassa-Holm shallow water system after wave breaking was studied in this paper. The underlying approach is based on a skillfully defined characteristic and a set of newly introduced variables which transform the original system into a Lagrangian semilinear system. It is the transformation, together with the associated properties, that allows for the continuity of the solution beyond collision time to be established, leading to a uniquely global dissipative solution, which constructs a semigroup, and the multipeakon dissipative solution.
No abstract is provided for this article.
In this paper, the problem of fuzzy dynamic sliding mode control design is investigated for a class of disturbed systems. Specifically, the fuzzy controller is constructed based on one feedback signal to estimate the unknown nonlinear terms and to develop the sliding mode control according to the fuzzy rules. Furthermore, it possesses the characteristic of simplicity in design and effectiveness in attenuating chattering. Finally, a numerical example is included to demonstrate the effectiveness and advantage of the proposed method.
This chapter is dedicated to present some methods for vibration protection of statues and cultural heritage objects against earthquakes and ambient vibrations. The chapter opens with short explanation about the dynamic performance test that has been done on a full-scale copy of the famous statue of Michelangelo Buonarroti Pieta Rondanini and its isolation system. Based on the results of the tests, a multidegree-of-freedom model is developed. This updated model is used to verify the proposed vibration control strategies. To reduce the level of vibration transmitted to the statue, combination of inerter with TMD (TMDI) is proposed. Optimal parameters of the passive device are found by using numerical methods. Furthermore, a scaled isolation system is designed and manufactured according to the test results of the full-scale structure. To improve the performance of the isolator, a designed and manufactured ball-screw type inerter is introduced to the scaled structure. The effectiveness of the manufactured inerter on the dynamic behavior of the isolation system is demonstrated by using dynamic performance tests on a shaking table. The results provide some numerical and experimental results considering inerter-based methods in order to vibration protection of statues and cultural heritage.
This paper focuses on the fuzzy variable structure control for uncertain systems with disturbance. Specifically, the fuzzy control is introduced to estimate the control disturbance, the switching control is included to compensate for the approximation error, and they possess the characteristic of simpleness in design and effectiveness in attenuating the control chattering. Some typical numerical examples are presented to demonstrate the effectiveness and advantage of the fuzzy variable structure controller proposed.
Design of a low-cost embedded iris recognition system is described in this paper. Firstly, we develop a simple and effective iris image acquisition unit, which is cheap and easy to use. This is achieved by both of hardware design and image evaluation algorithm development. Secondly, the iris recognition algorithm is introduced, including iris segmentation, image normalization, feature extraction, and code matching. The algorithm implementation architecture is based on an embedded dual-core processor platform, Texas Instruments TMS320DM6446 evaluation module (Davinci), which contains an ARM core and a DSP core in one chip. Thirdly, the evaluation experiments are performed on the established iris database, and the experimental results suggest that the system shows good performance both on accuracy and efficiency.
