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This paper discusses a leader-following consensus problem for nonlinear multi-agent systems (MASs) subjected to generalized Lipschitz-type nonlinearity using output feedback. An event-triggered (ET) leader-following control scheme, based upon estimated states using observers, is proposed for efficient bandwidth utilization by application of invariant sets. Distributed observers are designed to estimate the states of the followers because actual states are not always readily available. Besides, in order to reduce unnecessary data communication among the followers, an ET strategy has been formulated which excludes Zeno behavior as well. Under this proposed scheme, sufficient conditions are formulated using Lyapunov theory. These conditions not only guarantee the asymptotic stability of estimation error, but also ensure the tracking consensus of nonlinear MASs. Further, a simple and less conservative design approach using a decoupling scheme for assuring necessity and sufficiency for the main design approach has also been explored. The decoupling scheme is similar to separation principle for linear systems. Contrary to the existing works, the nonlinear systems considered in this study cover a wide family of Lipschitz nonlinearities, including both globally and locally Lipschitz systems. Moreover, the proposed approach is more efficient in handling ET consensus. Finally, the obtained results are verified with single link robots and modified Chua's circuits. • Invariant sets for consensus and observation errors are focused. • Leader-following consensus for generalized Lipschitz agents is proposed. • A less conservative event-triggered consensus method is developed. • A condition for elimination of Zeno behavior is revealed. [ABSTRACT FROM AUTHOR]

This paper addresses the design of an observer-based control system for the one-sided Lipschitz (OSL) nonlinear systems under input saturation. A nonlinear matrix inequality-based control law for the nonlinear systems under input saturation and unavailable states is derived to ensure convergence of the state vector to the origin. A decoupling approach is provided for attaining simple design constraints for computing the controller and observer gains through a cone complementary linearization algorithm. In contrast to the conventional decoupling methods, the proposed approach considers OSL nonlinearity and saturation function to demonstrate both the necessity and sufficiency of the decoupled design constraints for the nonlinear matrix inequality-based main condition. To the best of our knowledge, observer-based stabilization of OSL systems under input saturation has been addressed for the first time. Novel results for the observer-based control of input-constrained Lipschitz nonlinear systems are provided as specific scenarios of the proposed results. Simulation results of the proposed control scheme to a flexible-joint robot and a complex nonlinear circuit are presented. [ABSTRACT FROM AUTHOR]

This paper addresses a simultaneous control of the positions of the bridge and trolley and the vibrations of the load of a nuclear refueling machine (RM) that transports nuclear fuel rods to given locations in the nuclear reactor. Hamilton’s principle is used to develop the equations of motion of the RM. The lateral and transverse vibrations of the fuel rods during their transportation in water are analyzed. In deriving the control law, the nonlinear hydrodynamic forces acting on the rod are considered. Then, a boundary control scheme is developed, which suppresses the lateral and transverse vibrations simultaneously in the course of the transportation of the fuel rod to the desired locations. Furthermore, Lyapunov function-based stability analyses are performed to prove the uniform ultimate boundedness of the closed loop system as well as the simultaneous control of the positions of the bridge and trolley under the influence of nonlinear hydrodynamic forces. Finally, experimental and simulation results are provided to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper reviews the dynamics and vibration control techniques for marine riser systems. The riser pipes are modeled as Euler-Bernoulli beams that vibrate under the effects of ocean loads and the movements of the surface vessel, resulting in hybrid ODE-PDE equations. Chronological development of such hybrid models is first discussed, and their approximated ODE models for simulation are examined. Theoretical and experimental techniques for instability and fatigue analyses on the riser systems are also summarized. To increase the fatigue life against ocean currents, passive vibration suppression devices (e.g., strakes and spoilers) were mounted on the surface of the riser. Whereas to tackle the instability problem caused by sea waves, active control techniques utilizing the movements of the vessel were employed. In Conclusions, as future riser technologies, seven research issues are identified. [ABSTRACT FROM AUTHOR]

The ability of the somatosensory cortex in differentiating various tactile sensations is very important for a person to perceive the surrounding environment. In this study, we utilize a lab-made multi-channel functional near-infrared spectroscopy (fNIRS) to discriminate the hemodynamic responses (HRs) of four different tactile stimulations (handshake, ball grasp, poking, and cold temperature) applied to the right hand of eight healthy male subjects. The activated brain areas per stimulation are identified with the t -values between the measured data and the desired hemodynamic response function. Linear discriminant analysis is utilized to classify the acquired data into four classes based on three features (mean, peak value, and skewness) of the associated oxy-hemoglobin (HbO) signals. The HRs evoked by the handshake and poking stimulations showed higher peak values in HbO than the ball grasp and cold temperature stimulations. For comparison purposes, additional two-class classifications of poking vs. temperature and handshake vs. ball grasp were performed. The attained classification accuracies were higher than the corresponding chance levels. Our results indicate that fNIRS can be used as an objective measure discriminating different tactile stimulations from the somatosensory cortex of human brain. [ABSTRACT FROM AUTHOR]

This paper presents an observer-based controller design for the class of nonlinear systems with time-varying parametric uncertainties and norm-bounded disturbances. The design methodology, for the less conservative one-sided Lipschitz nonlinear systems, involves astute utilization of Young’s inequality and several matrix decompositions. A sufficient condition for simultaneous extraction of observer and controller gains is stipulated by a numerically tractable set of convex optimization conditions. The constraints are handled by a nonlinear iterative cone-complementary linearization method in obtaining gain matrices. Further, an observer-based control technique for one-sided Lipschitz nonlinear systems, robust against L 2 -norm-bounded perturbations, is contrived. The proposed methodology ensures robustness against parametric uncertainties and external perturbations. Simulation examples demonstrating the effectiveness of the proposed methodologies are presented. [ABSTRACT FROM AUTHOR]

The ability of the auditory cortex in the brain to distinguish different sounds is important in daily life. This study investigated whether activations in the auditory cortex caused by different sounds can be distinguished using functional near-infrared spectroscopy (fNIRS). The hemodynamic responses (HRs) in both hemispheres using fNIRS were measured in 18 subjects while exposing them to four sound categories (English-speech, non-English-speech, annoying sounds, and nature sounds). As features for classifying the different signals, the mean, slope, and skewness of the oxy-hemoglobin (HbO) signal were used. With regard to the language-related stimuli, the HRs evoked by understandable speech (English) were observed in a broader brain region than were those evoked by non-English speech. Also, the magnitudes of the HbO signals evoked by English-speech were higher than those of non-English speech. The ratio of the peak values of non-English and English speech was 72.5%. Also, the brain region evoked by annoying sounds was wider than that by nature sounds. However, the signal strength for nature sounds was stronger than that for annoying sounds. Finally, for brain-computer interface (BCI) purposes, the linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were applied to the four sound categories. The overall classification performance for the left hemisphere was higher than that for the right hemisphere. Therefore, for decoding of auditory commands, the left hemisphere is recommended. Also, in two-class classification, the annoying vs. nature sounds comparison provides a higher classification accuracy than the English vs. non-English speech comparison. Finally, LDA performs better than SVM. [ABSTRACT FROM AUTHOR]

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that can be used for a brain-computer interface (BCI). In the present study, we concurrently measure and discriminate fNIRS signals evoked by three different mental activities, that is, mental arithmetic (MA), right-hand motor imagery (RI), and left-hand motor imagery (LI). Ten healthy subjects were asked to perform the MA, RI, and LI during a 10 s task period. Using a continuous-wave NIRS system, signals were acquired concurrently from the prefrontal and the primary motor cortices. Multiclass linear discriminant analysis was utilized to classify MA vs. RI vs. LI with an average classification accuracy of 75.6% across the ten subjects, for a 2–7 s time window during the a 10 s task period. These results demonstrate the feasibility of implementing a three-class fNIRS-BCI using three different intentionally-generated cognitive tasks as inputs. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for online estimation of brain activities with reduction in the effects of physiological noises in functional near-infrared spectroscopy signals. The input–output characteristics of a hemodynamic response are modeled as an autoregressive moving average model together with exogenous physical signals (i.e., ARMAX). In contrast to the fixed design matrix in the conventional general linear model, the proposed model incorporates the temporal variations in the experimental paradigm as well as in the hemodynamics. The performance of the proposed method has been tested by using box-car type functions followed by individual tapping tasks. The results and their significance were verified using t -statistics indicating that ARMAX seems to be better able to track/reveal the hemodynamic response. Also, online brain-activation maps were generated for localizing brain activities. Experimental results are compared with those of the existing conventional GLM-based method. [ABSTRACT FROM AUTHOR]

Highlights: [•] Classification of fNIRS signals corresponding to the right- and left-wrist motor imagery. [•] Hemodynamic responses of the right-wrist imagery are distinguishable from those of left. [•] Signal slope improves the classification accuracy significantly than signal mean. [•] Enhanced performance on examination of subset of the response data. [ABSTRACT FROM AUTHOR]

• A dual-stage median filter (DSMF) is proposed to remove motion artifacts in the fNIRS signals. • The proposed filter removes the low-frequency drifts. • DSMF outperforms existing motion artifacts removal methods in signal distortion and noise suppression. • DSMF can be implemented for real-time applications. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the non-invasive brain-computer interface (BCI). Quickly obtaining precise brain signals is very crucial for successful BCIs. This paper investigates a real-time filtering technique to remove motion artifact (MA) and low-frequency drift in the fNIRS signals. Optical intensities of two wavelengths are generated using a balloon model in the literature and an experimental paradigm. Two types of MAs (spike-like and step-like) and low-frequency drifts are generated and added to the simulated optical intensities of two wavelengths. A new dual-stage median filter (DSMF) is proposed to recover the uncontaminated signals. Five evaluation metrics are used to determine the best window sizes of the dual filters: 4 s and 9 s for the first and 18 s for the second median filter. The proposed method is compared with a wavelet-based MA correction method and spline interpolation method using the same metrics. The results show that the proposed method outperforms the compared methods in attenuating MAs and signal distortion. Finally, the designed DSMF is applied to experimental data from eight healthy subjects, in which MAs were introduced by asking the subjects to shake their heads. The filtered data of the proposed method demonstrates clean signals with no MAs and low-frequency drifts. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses the problem of an adaptive synchronization of two chaotic Hindmarsh–Rose (HR) neurons coupled with a gap junction via a single control input. Two adaptive control approaches (i.e., a nonlinear control when the entire state variables are available and a linear feedback control when only the membrane potential is available) are proposed to guarantee the asymptotic synchronization of the state trajectories of two coupled HR neurons having unknown parameters. Numerical simulations demonstrating and verifying the effectiveness of the proposed control methods are provided. [Copyright &y& Elsevier]

Abstract: In this paper, a dynamic model of a ship-mounted container crane (called the “mobile harbor”) subject to the motions of ship itself imparted by random sea waves is investigated. The condition of the sea is assumed to be State 3. The ship''s heaving, pitching and rolling motions are considered as the main motions in exciting the mounted crane. Equations of motion are derived using the Lagrange method. Simulation results reveal that the lateral sway angle of the load becomes the biggest in the beam sea, whereas the pitching motion of the ship in the heading sea is the biggest. As a conclusion, the operation of mobile harbors in the heading sea is recommended. The developed mathematical model has been validated by experiments. [Copyright &y& Elsevier]

Abstract: This paper presents an online brain imaging framework for cognitive tasks conducted with functional near-infrared spectroscopy (fNIRS). The measured signal at each channel is regarded as the output from a linear system with unknown coefficients. The unknown coefficients are estimated by using the recursive least squares estimation (RLSE) method. The validity of the estimated parameters is tested using the t-statistics. Contrary to the classical approach that is offline and applies the same preprocessing scheme to all channels, the proposed RLSE method for a linear model formulation provides an independent robust adaptive process for individual channels. The experiments carried out with two fNIRS instruments (continuous-wave and frequency-domain) have verified the potential of the proposed methodology which can facilitate a prompt medical diagnostics by providing real-time brain activation maps. [Copyright &y& Elsevier]

Abstract: In this paper, a robust configuration (i.e., position and orientation) control of an industrial forklift is investigated. The equations of motion of a typical forklift are derived. Configuration control utilizing three navigation variables (i.e., the distance to the goal point and two split angles of the orientation error) is designed. Considering that an industrial forklift should move forward and backward effectively depending on the location of a goal point, control laws with regard to forward and backward movements are separately derived. For a nominal model that does not include any uncertainty, the developed control law assures the uniform asymptotic stability. However, in the presence of uncertainties, the control law guarantees that the solutions of three navigation variables are uniformly bounded. The effectiveness of the developed algorithm is demonstrated through simulations and experiments. [Copyright &y& Elsevier]

Abstract: Near-infrared spectroscopy (NIRS) can detect two different kinds of signals from the human brain: the hemodynamic response (slow) and the neuronal response (fast). This paper explores a nonlinear aspect in the tactile-stimulus-evoked neuronal optical response over a NIRS time series (light intensity variation). The existence of the fast optical responses (FORs) over the time series recorded in stimulus sessions is confirmed by event-related averaging. The chaos levels of the NIRS time series recorded both in stimulus and in rest sessions are then identified according to the estimated largest Lyapunov exponent. The obtained results ascertain that stimulus-evoked neuronal optical responses can be detected in the somatosensory cortex using continuous-wave NIRS equipment. Further, the results strongly suggest that the chaos level can be used to recognize the FORs in NIRS time series and, thereby, the state of the pertinent brain activity. [Copyright &y& Elsevier]

Abstract: This paper discusses stabilization and tracking control using linear matrix inequalities for a class of systems with Lipschitz nonlinearities. A nonlinear state feedback stabilization control is proposed for systems containing a more general case of Lipschitz nonlinearity. The main objective of the present study is to provide, for multi-input multi-output nonlinear systems, a tracking control approach based on nonlinear state feedback, which guarantees global asymptotic output and state tracking with zero tracking error in the steady state. Further, the tracking control is formulated for optimal disturbance rejection, using gain reduction based performance criteria. The proposed methodologies are illustrated herein using two simulation examples of chaotic and unstable dynamical systems. [Copyright &y& Elsevier]

Abstract: In this paper, a mathematical model of an oxy-fuel combustion boiler system with flue gas recirculation is investigated. The reduction of CO2 emission from coal-fired power plants is an important research issue in alleviating the global warming. The entire dynamics are decomposed in two main parts; fire-side dynamics and water-side dynamics. The fire-side dynamics consist of the mass and energy balance equations in the furnace (combustion process) and the flue gas dynamics represented by the mass balance equations of five gases (O2, CO2, SO2, H2O and NO2). The water-side dynamics include a drum pressure equation and a steam temperature equation. To validate the developed models, the real experimental data in Karakas, Koumanakos, et al. (2007) are used. To investigate the local behavior near an operating point, a linearization method at its steady-state condition is pursued. The time responses of the entire dynamics using step inputs (the oxygen mass flow rate, the coal mass flow rate, the primary air mass flow rate, etc.) are also discussed. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a robust velocity control problem for hydraulic elevators is investigated. The analysis is divided into two parts, mechanical and hydraulic. A detailed mathematical model for the mechanics is established for the purpose of simulation, but the control system design is carried out with a simplified model reduced from the detailed one. The three important characteristics of a hydraulic elevator, including cylinder friction, pump friction, and pump leakage, are modeled through experiments. The leakage property is characterized as a function of temperature and pressure. A two-stage nonlinear robust controller using the Lyapunov redesign method is established for velocity tracking control. At the first stage, a robust controller for the mechanical part is designed to yield the desired cylinder pressure for reference velocity tracking. At the second stage, a robust controller for the hydraulic part is designed to track the reference pressure generated from the first controller. Simulation results validate that the proposed method is robust in the presence of nonlinearities and uncertainties. [Copyright &y& Elsevier]

Many developing nations face energy crises, in addition to the global warming issue, owing to the recent increase in oil prices, accordingly, identifying the alternate energy sources. As a result, scientists around the globe are investigating new computational techniques for the energy dispatch under hybrid power systems. The aim of this research is to explore the integration of green energy sources (GESs) such as wind and solar in the conventional hydro–thermal coordination problem (CHTCP) to reduce the energy production cost along with the environmental benefits. The proposed hybrid energy coordination problem considers a probabilistic model for incorporating GESs uncertainties by using the point-estimation technique. Weibull and Beta distribution functions are utilized for the treatment of uncertain input variables of wind and solar sources, and the overall energy production cost is optimized via an improved heuristic swarm-based paradigm, namely, adaptive salp swam algorithm (ASSA). Three complex test systems are chosen (with and without GESs) to demonstrate the effectiveness of ASSA on hybrid power systems. The control parameters of ASSA are modified to maintain a balance between the exploration and exploitation phases to improve the convergence and to achieve better solution. The simulation results indicate that the integration of GESs into CHTCP has lowered the operational expenses by 10 percent and emissions by 64 percent. The findings have been compared with the existing techniques to show the effectiveness of the proposed approach. • Optimization problem is devised for energy hubs under renewable sources. • Point estimate method is considered for uncertainty in renewable sources. • Adaptive Salp Swarm Algorithm is evaluated on benchmark test systems. • The approach achieved improved convergence and energy production cost. • ASSA achieved low greenhouse gasses emission for multi-energy scheduling. [ABSTRACT FROM AUTHOR]

This study addresses the problem of deploying multi-agent systems using single-parameter adaptive neural network control in time and space where the system is modeled by a parabolic partial differential equation (PDE). We investigate the agent model, simplify the pointwise dynamics using a PDE model, and consider the deployment problem when the number of agents is relatively large. In order for the deployed agents to follow the desired trajectory, we augment the agent dynamics with individual control inputs, accounting for the unknown interference faced by each agent during the deployment process. In the proposed approach, a radial basis function neural network structure is introduced to enhance the systems' adaptivity under unknown interference. The unknown parameter is estimated via the single-parameter idea for reducing the computation of the entire process and increasing the calculation speed. Asymmetric performance constraints are imposed on the tracking error of the system to ensure that each agent is deployed in the required position. The results of numerical simulation prove the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This paper deals with the output feedback stabilization for a nonlinear flexible beam system with a general disturbance at the boundary. An extended state observer is designed to reject the uncertain disturbance estimated by a relatively independent estimator in the feedback loop via the active disturbance rejection control approach. The existence and uniqueness of the solution to the closed-loop beam system are investigated by means of the Galerkin approximation. The asymptotic stability of the closed-loop beam system is shown by utilizing the energy perturbation method. To demonstrate the control performance, numerical simulations are provided by the finite element method. [ABSTRACT FROM AUTHOR]

This study proposes an adaptive quantized fault-tolerant control for a nonlinear two-degree of freedom (2-DOF) helicopter system with an unknown dead zone and actuator failures. First, a hysteresis quantizer is employed to reduce the jittering during signal quantization. Second, a radial basis function neural network is adopted to address the uncertainty in the nonlinear helicopter system. Bounded estimates, smoothing functions, and adaptive parameters are used to compensate for the effects of unknown dead zones, actuator faults, and quantization inputs. Subsequently, an adaptive neural network quantized fault-tolerant control strategy is developed for the nonlinear 2-DOF helicopter system using a backstepping technique. In addition, the closed-loop system is proved to be semi-globally uniformly bounded using rigorous Lyapunov stability analysis. Finally, the effectiveness of the derived control strategy is demonstrated through simulation and experimental results. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate the multi-area economic emission dispatch problem (MEEDP) in the presence of renewable energy resources (RES) to improve the energy sustainability and climatic benefits. MEEDP is a multi-objective problem in smart grids, with the purpose of minimizing the operating costs and emissions of thermal units. RES have made a substantial contribution to greenhouse gases emission control and environmental sustainability. The integration of RES into conventional grids, which is becoming increasingly prevalent, spread the research scope of MEEDP and needs to be re-examined. This work considers two renewable sources (wind and solar) along with thermal plants subjected to significant number of previously uncombined system level limitations such as power capacity limit, prohibited zones, transmission network losses, dynamic ramp limits, tie-line limits and multiple fueling options. The operating cost is computed as summation of predictive and stochastic components. The predictive part is calculated by utilization of cumulative distribution function for each wind and solar system. A swarm intelligence-based crow search optimization algorithm (CSOA) is modeled to handle the complex constrained MEEDP with adjusted predictive part of RES. Six benchmark test systems with multi-dimensional constraints have been chosen to validate the adaptability and efficacy of the presented approach. Regardless of the complexity of the problem, the proposed approach provides the best feasible solution with a finer convergence rate. Finally, the simulation results depict that the integration of the corresponding system constraints gives legitimacy to the system and delivers reliable output. • A complex multi-area economic emission dispatch problem is considered. • Crow search optimization is applied with straightforward parameter adjustment. • Improved results are attained in terms of convergence rate and stability. • Low emission profiles in guidance to emission regulatory authorities. • Integration of renewable system with conventional thermal plants is considered. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, robust adaptive boundary control for a flexible marine riser with vessel dynamics is developed to suppress the riser’s vibration. To provide an accurate and concise representation of the riser’s dynamic behavior, the flexible marine riser with vessel dynamics is described by a distributed parameter system with a partial differential equation (PDE) and four ordinary differential equations (ODEs). Boundary control is proposed at the top boundary of the riser based on Lyapunov’s direct method to regulate the riser’s vibration. Adaptive control is designed when the system parametric uncertainty exists. With the proposed robust adaptive boundary control, uniform boundedness under the ocean current disturbance can be achieved. The proposed control is implementable with actual instrumentation since all the required signals in the control can be measured by sensors or calculated by a backward difference algorithm. The state of the system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Simulations are provided to illustrate the applicability and effectiveness of the proposed control. [Copyright &y& Elsevier]

This study is concerned with a novel adaptive fault-tolerant control design for a flexible Timoshenko arm considering the effects of actuator failures, backlash-like hysteresis, and external disturbances. First, the actuator failures and backlash-like hysteresis are integrated together and resolved into desired control signals and nonlinear errors. Second, these errors and external disturbances are deemed as composite disturbance terms to be handled with adaptive techniques. Third, adaptive fault-tolerant controllers with online updates are established to eliminate the shear deformation and elastic oscillation, lay the arm in a desired angle, counteract the hybrid effects of actuator failures and hysteresis, and deal with the uncertainty of composite disturbances. Then, based on the Lyapunov's stability theory, the proposed strategy guarantees the uniformly bounded stability in the controlled system. Finally, numerical examples are presented to illustrate the efficacy of the suggested scheme. [ABSTRACT FROM AUTHOR]