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showing 10 items of 4526 documents
Adaptive control of uncertain nonlinear systems with quantized input signal
2018
Abstract This paper proposes new adaptive controllers for uncertain nonlinear systems in the presence of input quantization. The control signal is quantized by a class of sector-bounded quantizers including the uniform quantizer, the logarithmic quantizer and the hysteresis quantizer. To clearly illustrate our approaches, we will start with a class of single-loop nonlinear systems and then extend the results to multi-loop interconnected nonlinear systems. By using backstepping technique, a new adaptive control algorithm is developed by constructing a new compensation method for the effects of the input quantization. A hyperbolic tangent function is introduced in the controller with a new tr…
Decentralized Adaptive Control for Interconnected Nonlinear Systems with Input Quantization
2017
Abstract In this paper, a decentralized adaptive control scheme is proposed for a class of uncertain nonlinear interconnected systems with input quantization. A hysteresis uniform quantization is introduced to reduce chattering. In the control design, a smooth function is introduced with backstepping technique to compensate for the effects of interactions. It is shown that the proposed decentralized adaptive controllers can ensure global boundedness of all the signals in the closed-loop interconnected systems and the tracking errors of subsystem converge to a residual, which can be adjusted by choosing suitable design parameters. Simulation results illustrate the effectiveness of the propos…
Adaptive Backstepping Control of Nonlinear Uncertain Systems With Quantized States
2019
This paper investigates the stabilization problem for uncertain nonlinear systems with quantized states. All states in the system are quantized by a static bounded quantizer, including uniform quantizer, hysteresis-uniform quantizer, and logarithmic-uniform quantizer as examples. An adaptive backstepping-based control algorithm, which can handle discontinuity, resulted from the state quantization and a new approach to stability analysis are developed by constructing a new compensation scheme for the effects of the state quantization. Besides showing the global ultimate boundedness of the system, the stabilization error performance is also established and can be improved by appropriately adj…
Adaptive Control of Quantized Uncertain Nonlinear Systems
2017
Abstract This paper proposes a new adaptive controller for uncertain nonlinear systems in presence of quantized input signal and unknown external disturbance. A hysteresis quantizer is incorporated to reduce chattering phenomenon. By proposing a new transformation of the final control signal, using the sector-bound property of the quantizer and introducing a hyperbolic tangent function, the effects from input quantization and external disturbance are effectively compensated and the Lipschitz condition required for the nonlinear functions in the systems is removed. Besides showing global stability, tracking error performance is also established and can be adjusted by tuning certain design pa…
Surrogate models for the compressive strength mapping of cement mortar materials
2021
Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method available in the literature, which can reliably predict their strength based on the mix components. This limitation is attributed to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques for predicting the compressive strength of mortars is investigated. Specifically, Levenberg–Marquardt, biogeography-based optimization, and invasive weed optimization algorithms are used for this purpose (based on experimental data available in the literature). The c…
Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach
2020
In this paper, distributed adaptive consensus for a class of strict-feedback nonlinear systems under directed topology condition is investigated. Both leader–follower and leaderless cases are considered in a unified framework. To design distributed controller for each subsystem, a local compensatory variable is generated based on the signals collected from its neighbors. Such a technique enables us to solve the leader–follower consensus and leaderless consensus problems in a unified framework. And it further allows us to treat the leaderless consensus as a special case of the leader–follower consensus. For leader–follower consensus, the assumption that the leader trajectory is linearly para…
A class of third order iterative Kurchatov–Steffensen (derivative free) methods for solving nonlinear equations
2019
Abstract In this paper we show a strategy to devise third order iterative methods based on classic second order ones such as Steffensen’s and Kurchatov’s. These methods do not require the evaluation of derivatives, as opposed to Newton or other well known third order methods such as Halley or Chebyshev. Some theoretical results on convergence will be stated, and illustrated through examples. These methods are useful when the functions are not regular or the evaluation of their derivatives is costly. Furthermore, special features as stability, laterality (asymmetry) and other properties can be addressed by choosing adequate nodes in the design of the methods.
Prediction of Vehicle Crashworthiness Parameters Using Piecewise Lumped Parameters and Finite Element Models
2018
Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into…
Compensation of Nonlinear Torsion in Flexible Joint Robots: Comparison of Two Approaches
2015
Flexible joint robots, in particularly those which are equipped with harmonic-drive gears, can feature elasticities with hysteresis. Under heavy loads and large joint torques the hysteresis lost motion can lead to significant errors of tracking and positioning of the robotic links. In this paper, two approaches for compensating the nonlinear joint torsion with hysteresis are described and compared with each other. Both methods assume the measured signals available only on the motor side of joint transmissions. The first approach assumes a rigid-link manipulator model and transforms the desired link trajectory into that of the motor drives by using the inverse dynamics and inverse hysteresis…
On Stability of Virtual Torsion Sensor for Control of Flexible Robotic Joints with Hysteresis
2019
Author's accepted manuscript (postprint). This article has been published in a revised form in Robotica, http://doi.org/10.1017/S0263574719001358. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © 2019 Cambridge University Press. Available from 25/03/2020. Aim of the virtual torsion sensor (VTS) is in observing the nonlinear deflection in the flexible joints of robotic manipulators and, by its use, improving positioning control of the joint load. This model-based approach utilizes the motor-side sensing only and, therefore, replaces the load-side encoders at nearly zero hardware costs. For being applied in the closed control …