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A neural network empowered dynamic surface control (DSC) technique is addressed for robot manipulators system with unknown dynamics. In comparison to the conventional adaptive neural control algorithms, which could guarantee semi-globally uniformly ultimate boundedness (SGUUB) only when neural approximation keeps effective, the scheme designed in this paper ensures globally uniformly ultimately bounded...
This paper presents a new variable gain robust state observer for a class of uncertain linear systems. The robust state observer proposed in this paper is composed of fixed and variable gain matrices. In this paper, LMI-based sufficient conditions for the existence of the proposed robust state observer are given. Finally, a simple illustrative example is included.
In this paper, a class of second-order nonlinear time-delayed multiagent systems with disturbance is investigated. In order to improve the adaptivity, neural networks are used to learn the unknown dynamics. Then, by utilizing Lyapunov-Krasovskii functional, time delays can be eliminated. Moreover, a robustifying term is introduced to constrain external disturbance. With divide-and-conquer idea, the...
In the pharmaceutical industry, it is common to determine the maximum allowable set of uncertain parameters—called the design space—that guarantees that the product quality attributes obtained by a manufacturing process are within specified limits. In industrial practice, design spaces are constructed without considering the effects of process dynamics or feedback control, which results in poor characterization...
This work proposes a new approach to cope with robust stabilization of uncertain linear systems. Differently from the traditional methods in the literature, that employ slack and scalar variables to provide more relaxed conditions than the ones based on quadratic stabilization, a new strategy is proposed to iteratively search for the robust gain directly on the decision parameter space (no change...
In this paper, a sufficient delay-dependent condition for the stabilization of overlapping linear continuous-time uncertain systems with multiple delays by robust overlapping output feedback controllers is given. The overlapping system is first expanded into a higher dimensional system (expanded system) where the overlapping subsystems appear as disjointed from each other. Then, robust local delay-dependent...
We propose new asymptotic notions that capture the robustness of a large interconnected network as dimension of the network grows. Specifically, we address the question of how robustness of a network changes with the network dimension. Motivated by applications in transportation and economic networks, we study network topologies that are robust to scaling in network dimension, and investigate characteristics...
A global task coordinate frame (GTCF) based learning adaptive robust controller (LARC) is practically synthesized for an industrial X-Y linear-motor-driven stage to achieve not only good parametric adaptation ability and uncertain disturbance robustness, but also excellent transient/steady-state contouring performance. With the employment of GTCF which is globally based on the shape of the desired...
In the Quality-by-Design (QbD) paradigm for pharmaceutical processes, critical quality attributes (CQAs) must meet specifications for all possible realizations of critical process parameters (CPPs) within a design space. During the startup of such a process, it is desired to begin meeting CQA specifications as quickly as possible and then robustly guarantee that specifications will continue to be...
In this paper, the problem of robust H∞ filter design for uncertain time-invariant discrete-time linear systems is addressed. The filter makes use of an arbitrary number of past output measurements. The filter stores the measurements in a buffer and is therefore of order higher than the system being filtered. The robust filtering design conditions are based on Lyapunov matrices with polynomial parameter...
In this paper, we study the robust consensus problem of a network of general discrete-time linear agents coordinating through unreliable communication channels. Two neighboring agents exchange information via a communication channel, which is modeled in this paper as an ideal transmission system subject to a multiplicative stochastic uncertainty. This uncertain channel model includes the commonly...
This paper presents a novel approach to incorporating soft constraints into the robust MPC design in the LMI framework. As soft constraints are frequently used in industrial applications, using the proposed approach leads to improved control performance and enables implementing the robust MPC for more complex control problems. The main advantage of the strategy is preserved structure of the optimization...
This paper addresses the robust consensus reliable control protocol design problem against actuator faults for linear parameter-varying multi-agent systems. First, the actuator faults are modeled via a polytopic uncertainty method. Second, a distributed observer is designed for the single agent by sharing the communication network sensors to estimate the state information. Then by these estimated...
When collecting samples via crowd-sourcing for semi-supervised learning, often labels that designate events of interest are assigned unreliably, resulting in label noise. In this paper, we propose a robust method for graph-based image classifier learning given noisy labels, leveraging on recent advances in graph signal processing. In particular, we formulate a graph-signal restoration problem, where...
The paper has studied the problem of H∞ filtering for Markovian jump stochastic systems with uncertain transition probabilities. The systems under consideration not only involve uncertainties both in the system matrices and in the mode transition rate matrix, but also contain time-varying delays. By free-weighting matrix technique, a sufficient condition for the existence of an H∞ filter is developed...
New conditions for the design of robust periodic observer-based controllers for periodic discrete-time linear time-varying (LTV) systems are proposed in this paper. The control system is designed to be robust to external noises, and such robustness is achieved by minimizing the ℋ∞ norm from the input noise to the error output in the observer design, and the ℋ∞ norm from the error and disturbance signal...
This paper investigates the robust reduced order observer design for nonlinear stochastic systems with muliplicative noises. The parametric uncertainties are bounded and unstructured. The proposed reduced order observer guarantees that the equilibrium point of the estimation error is almost surely exponentially stable despite of the uncertainties. The observer matrices are computed by solving LMI.
In this paper, the complex modified projective synchronization (CMPS) of two different fractional-order chaotic complex systems is firstly investigated. We assume that the slave system is perturbed by external disturbances. The master and slave systems achieved CMPS can be synchronized up to a complex scaling matrix. On the basis of a novel stability theory, a robust control law is designed to realize...
In this paper, a RISE type of tracking controllers for a class of nonlinear mechanical systems is proposed. The proposed chattering-free controller provides global asymptotic tracking in the presence of external disturbances. The proof of global asymptotic stability is based on a novel approach to the construction of a Lyapunov function which is parameterized by a time-varying function of reference...
This paper deals with the sensor fault detection problem for T-S fuzzy systems with unmeasurable premise variables. A new observer is constructed to detect the faults, where measurable premise variables and the estimations of unmeasurable premise variables are used as the premise variables of the observer simultaneously. Different from the existing results, where all premise variables of the observer...
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