Search results for "NCT"
showing 10 items of 16712 documents
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…
Optimality Conditions for Non-Qualified Parabolic Control Problems
1994
We consider parabolic state constrained optimal control problems where the usual Slater condition is not necessarily satisfied. Instead, a weaker interiority property is assumed. Optimality conditions with a Lagrange multiplier are given. As an application we present an augmented Lagrangian algorithm. Numerical test results are included.
Stealthy Attacks in Cloud-Connected Linear Impulsive Systems
2018
This paper studies a security problem for a class cloud-connected multi-agent systems, where autonomous agents coordinate via a combination of short-range ad-hoc commu- nication links and long-range cloud services. We consider a simplified model for the dynamics of a cloud-connected multi- agent system and attacks, where the states evolve according to linear time-invariant impulsive dynamics, and attacks are modeled as exogenous inputs designed by an omniscent attacker that alters the continuous and impulsive updates. We propose a definition of attack detectability, characterize the existence of stealthy attacks as a function of the system parameters and attack properties, and design a fami…
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…
Fractional-Order System Identification of Viscoelastic Behavior: A Frequency Domain Based Experimental Study
2020
In this work, the fractional-order modeling of viscoelastic behavior is investigated based on measurement data in the frequency domain. For the results of two different test setups we apply existing parameter estimation algorithms designed for fractional-order transfer functions. These algorithms require a priori knowledge of the system structure including the commensurate order of differentiation. An iterative procedure is used to evaluate the influence of the unknown structure. The measured polymer samples show a viscoelastic stress response. We can show that integer-order models are not capable of capturing this behavior. For a set of predefined structures, the best obtained fractional-o…
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.
Event-triggered robust adaptive control for discrete time uncertain systems with unmodelled dynamics and disturbances
2019
In practice, modelling errors caused by high-order unmodelled dynamics and external disturbances are unavoidable. How to ensure the robustness of an adaptive controller with respect to such modelling errors is always a critical concern. In this study, the authors consider the design of event-triggered robust adaptive control for a class of discrete-time uncertain systems which involve such modelling errors and also are allowed to be non-minimum phase. Unlike some existing event-triggered control schemes, the developed controllers do not require that the measurement errors meet the corresponding input-to-state stable condition. Global stability of the closed-loop system which means that all …
The Advantage of Digital Decision Making for Strategic Decisions – Proofed by a Supply Chain Case
2017
This paper will discuss the advantage of decision making supported by a digital system and will provide an overview of an empiric analysis researched on this topic. Decision making in organizations is a significant system implied task of managers and therefore a broad area in scientific research, not only in the disciplines management or business studies – even from technical to humanistic disciplines. Nowadays the trend of digitalization captures all areas of life especially in business, as well as the typical management task of decision making. Triggered by the digitalization trend business will move toward an autonomous decision making of machines or cyber systems. The important step tow…
Density Flow in Dynamical Networks via Mean-Field Games
2016
Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic a…
Integral Control Action in Precise Positioning Systems with Friction
2016
Abstract For high precision positioning systems a fast and accurate settling to the reference state is most significant and, at the same time, challenging from the control point of view. Traditional use of an integral coaction in feedback can attain a desired reference tracking at steady-state motion, but can fail in case of precise positioning. Most crucial is that this is independent on how accurate the integral control part is tuned. This paper addresses the feedback control action in precise positioning systems with friction. Analyzing the closed-loop control dynamics with nonlinear friction in feedback it is shown why the integral action cannot efficiently cope with Coulomb friction wh…