Search results for "TEP"
showing 10 items of 712 documents
Adaptive Backstepping Control of a 2-DOF Helicopter
2019
This paper proposes an adaptive nonlinear controller for a 2-Degree of Freedom (DOF) helicopter. The proposed controller is designed using backstepping control technique and is used to track the pitch and yaw position references independently. A MIMO nonlinear mathematical model is derived for the 2DOF helicopter based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. Unlike some existing control schemes for the helicopter control, the developed controller does not require the knowledge on the system uncertain parameters. Updating laws are used to estimate the unknown parameters. It is shown that not only the global stability is guaranteed …
Distributed Adaptive Consensus Tracking Control of Uncertain High-order Nonlinear Systems under Directed Graph Condition
2018
In this paper, we investigate the output consensus tracking problem for a class of high-order nonlinear systems subjected to unknown parameters and uncertain external disturbances. A novel backstepping based distributed adaptive control scheme is presented under the directed communication status. For the subsystems without direct access to time-varying desired trajectory, local estimators are introduced and the corresponding adaptive laws are designed in a totally distributed fashion. With the presented scheme, the assumption on linearly parameterized reference signal and the information exchange operation of subsystem inputs in the existing results are no longer needed. It is shown that al…
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 Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems with Time Delay
2016
In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main con…
Robust adaptive tracking control of uncertain systems with time-varying input delays
2017
ABSTRACTIn this paper, the problem of robust adaptive tracking control of uncertain systems with time-varying input delays is studied. Under some mild assumptions, a robust adaptive controller is designed by using adaptive backstepping technique such that the system is globally stable and the system output can track a given reference signal. At the same time, a root mean square type of bound is obtained for the tracking error as a function of design parameters and thus can be adjusted. Finally, one numerical example is given to show the effectiveness of the proposed scheme.
Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy)
2016
Debris flows are among the most hazardous phenomena in nature, requiring the preparation of suscep- tibility models in order to cope with this severe threat. The aim of this research was to verify whether a grid cell-based susceptibility model was capable of predicting the debris- flow initiation sites in the Giampilieri catchment (10 km2), which was hit by a storm on the 1st October 2009, resulting in more than one thousand landslides. This kind of event is to be considered as recurrent in the area as attested by historical data. Therefore, predictive models have been prepared by using forward stepwise binary logistic regression (BLR), a landslide inventory and a set of geo- environmental …
Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a…
2017
Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils and beans), spot urine samples from a subcohort from the PREDIMED study were stratified, using a validated food frequency questionnaire. Non-pulse consumers (≤ 4 g/day of pulse intake) and habitual pulse consumers (≥ 25 g/day of pulse intake) were analysed using a 1H-NMR metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through…
Examining the "Veggie" personality: Results from a representative German sample.
2017
Abstract An increasing proportion of people choose to follow a vegetarian diet. To date, however, little is known about if and how individual differences in personality relate to following a vegetarian diet. In the two studies presented here, we aimed to (1) estimate the prevalence of self-defined vegetarians in two waves of a German representative sample (N = 4496 and 5125, respectively), (2) analyze the effect of socio-demographic variables on dietary behavior, and (3) examine individual differences between vegetarians and meat eaters in personality traits, political attitudes, and health-related variables. In Study 1, a strict definition of vegetarians was used, while in Study 2 the defi…