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Wind turbine control has attracted increasing attention, driven in part by evolving challenges due to the growing size and complexity of wind turbines. Addressing these challenges and maximizing wind turbine power production requires the application of advanced nonlinear control methods. Sliding Mode Control (SMC) has emerged as a promising approach in this context. Recent studies have explored the integration of an integral term with SMC, called I-SMC. This technique has been shown to result in system responses that exhibit chattering phenomena with noticeable state errors. This study aimed to address these issues through the introduction of a novel controller known as Integral Backstepping SMC (IB-SMC). This study demonstrated that IBSMC not only ensured the stability of wind turbines but also outperformed other control strategies, even in the presence of disturbances of approximately 30% of the rated electromagnetic torque. To validate the effectiveness of the proposed controller, extensive simulation tests were carried out using MATLAB/Simulink software to evaluate the controller's responsiveness to rapid changes in conditions, as well as its robustness and overall performance. A comparison was carried out between the IBSMC and previous SMCs to evaluate their ability to reduce steady-state error and chattering. [ABSTRACT FROM AUTHOR]

This paper details how to construct a small-scale shaking table attached to a magnetorheological (MR) damper. The motivation for this construction relies on the increasing interest in modeling the dynamics of MR dampers—MR dampers have been used in structures for safety reasons. To model the MR damper, we use the so-called 'Dahl model', which is useful to represent systems with a hysteresis. The Dahl model, validated through experimental data collected in a laboratory, was combined with a linear model to represent a two-story building. This two-story building model allows us to simulate the dynamics of that building when its floors are attached to MR dampers. By doing so, we can assess—through simulation—to what extent MR dampers can protect structures from vibrations. Using data from the 'El Centro' earthquake (1940), we can conclude that MR dampers have the potential to reduce the impact of earthquakes upon structures. This finding emphasizes the potential benefits of MR dampers for the safety of structures, which is a conclusion taken from the apparatus detailed in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes an extension of the model predictive control framework for switching continuous‐time linear systems. The switching times follow a stochastic process with limited statistical information. At each switching time, the controller knows the system state, but it is blind with respect to the switching continuous‐time subsystems. In this setting, the paper's main contribution is to show how to compute the model predictive control gain. The paper also illustrates the implications of our approach for applications. The approach was used in practice to control an electric current source that supplied a switching load. The experimental data support the usefulness of our approach. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic hit hard society, strongly affecting the emotions of the people and wellbeing. It is difficult to measure how the pandemic has affected the sentiment of the people, not to mention how people responded to the dramatic events that took place during the pandemic. This study contributes to this discussion by showing that the negative perception of the people of the COVID-19 pandemic is dropping. By negative perception, we mean the number of negative words the users of Twitter, a social media platform, employ in their online posts. Seen as aggregate, Twitter users are using less and less negative words as the pandemic evolves. The conclusion that the negative perception is dropping comes from a careful analysis we made in the contents of the COVID-19 Twitter chatter dataset , a comprehensive database accounting for more than 1 billion posts generated during the pandemic. We explore why the negativity of the people decreases, making connections with psychological traits such as psychophysical numbing, reappraisal, suppression, and resilience. In particular, we show that the negative perception decreased intensively when the vaccination campaign started in the USA, Canada, and the UK and has remained to decrease steadily since then. This finding led us to conclude that vaccination plays a key role in dropping the negativity of the people, thus promoting their psychological wellbeing. [ABSTRACT FROM AUTHOR]

This paper shows a result for the load frequency control with event‐triggering mechanism under deception attacks. Specifically, the event‐triggering mechanism and deception attacks are considered in the dynamic model of power systems. The event‐triggering is used to reduce the frequency of controller update and communication between nodes. The H∞ controller is designed and the stability of the system is guaranteed by utilising the Lyapunov–Krasovskii functional method and truncated Bessel–Legendre inequality. Finally, a three‐area interconnected networked power system is given and the simulated results are presented to show the effectiveness of the developed theoretical results. [ABSTRACT FROM AUTHOR]

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in engineering education, allowing instructors and students to learn through hands-on experiences of essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy that seems novel when applied to the MagLev. Experiments performed in the laboratory provide comparisons of the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education. [ABSTRACT FROM AUTHOR]

This paper presents a stabilization control for positive, Takagi-Sugeno fuzzy systems subject to Markov jump parameters. In the continuous-time formulation, the approach guarantees mean-square stability with constraints on the control—the main condition hinges upon linear matrix inequalities. The proposed method's usefulness is illustrated by a practical-oriented example, which was designed to control the output voltage of a DC-DC boost converter subject to both voltage and load variations driven by a Markov chain. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of designing a control strategy to guarantee stability in probability for high-order stochastic systems. The control hinges on the sliding-mode scheme. We first prove that the control design can stabilize a fast terminal sliding-mode function. We further show that the stable sliding mode is able to assure the stability in probability for the high-order stochastic system. The resulting system may account nonvanishing diffusion terms, which is regarded as a novelty. The derived control strategy has implications for applications—experiments are carried out to control the pitch angle of a one-degree-of-freedom aerial device. The corresponding experimental results demonstrate the benefits and effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Summary: This article presents conditions to assure the second‐moment stability for a class of nonlinear Markov jump systems. The main assumption requires that the control and nonlinear terms form orthogonal vectors, a novel condition in the context of Markov jump systems. The second‐moment stability is verified through linear matrix inequalities—the conditions account the case in which the Markovian mode is either accessible or inaccessible to the controller. A real‐time automotive application illustrates the potential benefits of our approach. [ABSTRACT FROM AUTHOR]

Abstract The paper presents a method for checking the robust mean square stability of continuous-time Markov jump linear systems. The robustness arises in the analysis due to the assumption that the Markovian transition probability matrix is partially known. The corresponding infinite-dimensional robust stability problem, difficult to solve, is then converted into a probabilistic problem, amenable to the numerical viewpoint, taking advantage of the randomized (scenario) approach. The paper shows examples—including a real-time electronic-circuit application—for which the results from the literature fail to determine the robust stability but the randomized approach gives a positive answer. [ABSTRACT FROM AUTHOR]

This paper presents a strategy for computing model predictive control of linear Gaussian noise systems with probability constraints. As usual, constraints are taken on the system state and control input. The novelty relies on setting bounds on the underlying cumulative probability distribution, and showing that the model predictive control can be computed in an efficient manner through these novel bounds-- an application confirms this assertion. Indeed real-time experiments were carried out to control a direct current (DC) motor. The corresponding data show the effectiveness and usefulness of the approach. [ABSTRACT FROM AUTHOR]

Networked control systems have recently experienced a surge in fundamental theoretical results ignited by numerous advantages of introducing shared multipurpose communication networks in control systems. Regarding developments on the practical side, however, a networked control system is still wanting when it comes to experimental platforms suitable for research and educational purposes, which contributes to most of networked control system theory being validated by means of numerical examples and simulations. This paper addresses this issue by presenting a low-cost real-time networked control system platform, based on custom hardware and software solutions that can be readily explored with the sole use of a web browser connected to the Internet. The technical decisions made during development represent a fundamentally novel take on networked control system experimental platforms that can potentially be reproduced by several universities. The platform provides the user with multiple controller and input reference options, network configurations, delay statistics, and even a downloadable file containing advanced experiment data. A survey conducted with students located over 1200 km away from the platform who used it during laboratory assignments highlight the system's usability and interactivity, and supports the platform is suitable for educational purposes. [ABSTRACT FROM AUTHOR]

This paper focuses on the filter design problem for semi-Markov jump linear systems. The system outputs are transmitted to the filter via networks, and it is assumed that the transmission is imperfect with data packet dropouts subject to the Bernoulli random binary distribution. A σ-error mean square stability criterion is first derived for the underlying systems. On the basis of the criterion, the H ∞ performance analysis is conducted. By constructing a time-varying Lyapunov function, a time-varying H ∞ filter scheme is investigated. Because the presented approach can cover the mode-dependent and mode-independent time-invariant H ∞ filter schemes as special cases, the conservatism of the derived results is less than those of the time-invariant filter schemes. An active suspension system with activator uncertainties is lastly presented to illustrate the effectiveness and feasibility of the derived theoretical results. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The note presents an algorithm for the average cost control problem of continuous-time Markov jump linear systems. The controller assumes a linear state-feedback form and the corresponding control gain does not depend on the Markov chain. In this scenario, the control problem is that of minimizing the long-run average cost. As an attempt to solve the problem, we derive a global convergent algorithm that generates a gain satisfying necessary optimality conditions. Our algorithm has practical implications, as illustrated by the experiments that were carried out to control an electronic dc-dc buck converter. The buck converter supplied a load that suffered abrupt changes driven by a homogeneous Markov chain. Besides, the source of the buck converter also suffered abrupt Markov-driven changes. The experimental results support the usefulness of our algorithm. [ABSTRACT FROM AUTHOR]

This paper introduces a polyhedral approximation algorithm for set-valued estimation of switching linear systems. The algorithm generates set-valued estimates for any possible sequence of switching parameters, under the assumption that the system has unknown but bounded disturbances and measurement noises. Our algorithm has practical implications; namely, set-valued estimates were generated for the position and electrical current of a real-time automotive electronic throttle valve, and the corresponding experimental data demonstrate the practical benefits of our approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The note presents an output feedback control strategy for Markov jump linear systems with no mode observation. Based on minimizing a finite-time quadratic cost, we derive an algorithm that generates output feedback gains that satisfy a necessary optimality condition. These gains can be computed off-line relying only on the initial condition of the system. This result expands a previous one from the literature that considered state-feedback only. To illustrate the usefulness of the approach, real-time laboratory experiments were performed to control an automotive electronic throttle valve subject to Markov-driven voltage fluctuations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents an application of unscented Kalman filters (UKFs) to an automotive electronic throttle device. The motivation of this study is on estimating the position of the throttle device when measurements of the position are inaccessible, e.g., due to failures in the sensor of position. In this case, an external wattmeter is connected in the circuitry to measure the power consumed by the throttle, and this information feeds UKFs to produce the estimation for the position. Experimental data support the findings of this paper. Almost all of the brand-new vehicles based on spark-ignition combustion engines have an electronic throttle valve to control the power produced by the engine. The electronic throttle has a unique sensor for measuring the position of the throttle valve, and this feature can represent a serious problem when the sensor of position fails. As an attempt to prevent the effects of a failure from such a sensor, we present an algorithm (UKF) combined with the use of an additional sensor, i.e., a wattmeter. The wattmeter is detached from the throttle's structure but is arranged to measure the electric power consumed by the throttle. Measurements of the power consumption then feed the UKF. This filter then produces an estimation of the position of the throttle valve. Experimental data illustrate the practical benefits of our approach. [ABSTRACT FROM PUBLISHER]

This paper presents an improved model for an automotive electronic throttle inspired on the behaviour observed in real-time experiments. Due to a number of issues, particularly the return-spring, the performance of the throttle valve depends on whether it is opening or closing. This asymmetric behaviour was taken into account to design a mathematical model of the throttle body and to derive a nonlinear asymmetric Proportional Integral controller. The experimental demonstration suggests that considering an asymmetric term dramatically improves the performance of the controller. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The paper formulates the static control problem of Markov jump linear systems, assuming that the controller does not have access to the jump variable. We derive the expression of the gradient for the cost motivated by the evaluation of 10 gradient-based optimization techniques. The numerical efficiency of these techniques is verified by using the data obtained from practical experiments. The corresponding solution is used to design a scheme to control the velocity of a real-time DC motor device subject to abrupt power failures. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY The paper deals with the control problem of discrete-time nonlinear systems. The main contribution of this note is to present conditions that assure the existence of stationary policies that generate lower bounds for the minimal long-run average cost. These lower bounds coincide with the optimal solution when a mild convergence assumption holds. To illustrate the results, the paper presents an application for the simultaneous state-feedback control problem, and the derived strategy is used to design a real-time simultaneous control for two direct current motor devices. The dynamics of these two devices are written in terms of a nonlinear algebraic matrix recurrence, which in turn represents a particular case for our general nonlinear approach. The optimal gain for the corresponding simultaneous state-feedback problem is obtained, and such a gain was implemented in a laboratory testbed to control simultaneously the two direct current motors. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]