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Nonlinear control theory applied to unmanned aeronautical vehicles is an engineering topic that has received higher and higher popularity during the last decade. Model-based control approaches have shown increased performance in flight control accuracy and robustness compared to model-free proposals based on parameter adaptation and estimation. However, model-based structures need more computational efforts in terms of spatial and temporal variables. To avoid these constraints, the latest drone flight controls are based on quaternion models, ensuring more advanced computational performances. To this aim, this paper deals with a flight control algorithm of a quadrotor, in which the mathematics model of the plant is defined in terms of quaternions. Additionally, when aerial vehicles are used in specific applications such as slung load transportation and agriculture fields, among others, the variation of the mass receives high importance since it could make the entire system unstable. In the same line of ideas, this paper presents a H ∞ strategy, combined with a Super-Twisting Sliding-Mode Control, ensuring the control objective of the mass variations identification, and trajectory tracking, to be solved. The stability analysis of the proposed control approach is also discussed, and the quality and performances of the presented control strategy are tested by simulations, in an interesting case in which mass variations and external perturbations cannot be negligible. [ABSTRACT FROM AUTHOR]

In response to the challenges posed by large-scale, uncoordinated electric vehicle charging on the power grid, Vehicle-to-Grid (V2G) technology has been developed. This technology seeks to synchronize electric vehicles with the power grid, improving the stability of their connections and fostering positive energy exchanges between them. The key component for implementing V2G technology is the bidirectional AC/DC converter. This study concentrates on the non-isolated bidirectional AC/DC converter, providing a detailed analysis of its two-stage operation and creating a mathematical model. A dual closed-loop control structure for voltage and current is designed based on nonlinear control theory, along with a constant current charge–discharge control strategy. Furthermore, midpoint potential balance is achieved through zero-sequence voltage injection control, and power signals for the switching devices are generated using Space Vector Pulse Width Modulation (SVPWM) technology. A simulation model of the V2G system is then constructed in MATLAB/Simulink for analysis and validation. The findings demonstrate that the control strategy proposed in this paper improves the system's robustness, dynamic performance, and resistance to interference, thus reducing the effects of large-scale, uncoordinated electric vehicle charging on the power grid. [ABSTRACT FROM AUTHOR]

This article delves into the intricate challenge of implementing prescribed-time command filtered control in the context of uncertain nonlinear systems. Firstly, a prescribed-time function is defined to lay the groundwork for subsequent controller design. Subsequently, a novel prescribed-time command Filtered controller is proposed for high-order nonlinear systems featuring unknown parameters. This controller guarantees swift error convergence within a predefined time range, with the added capability of periodic error convergence to zero during subsequent controller operations. A pivotal innovation in this study lies in the controller's design, which remains unaffected by the system's initial conditions. This unique feature enables the prescribed time to be flexibly set within physical constraints, diverging markedly from conventional finite-time control theory. Theoretical analysis has conclusively shown that the controller achieves full-state tracking error convergence within the specified time frame. The efficacy of the research findings is substantiated through two simulation cases, underscoring a substantial contribution to the refinement and adaptability of nonlinear system control theory. • This article introduces a Prescribed Time Command Filtered Controller (PTCFC) for a specific class of uncertain high-order nonlinear systems with unknown parameters. • Through the design of a novel periodic finite-time function, the article achieves periodic asymptotic convergence of the control system tracking error. • The article proposes a novel compensation signal design scheme and combines it with a controller to achieve stability analysis of the control system and strict proof of periodic error convergence. [ABSTRACT FROM AUTHOR]

The article discusses the importance of research in the field of flight dynamics, control, and simulation for advancing aeronautical sciences. It emphasizes the need for a deep understanding of flight dynamics to enhance aircraft performance, safety, and efficiency. The integration of advanced control strategies and the use of simulation play a crucial role in optimizing aircraft behavior and reducing costs. The article also provides an overview of 14 papers published in a special issue of the Aerospace journal, covering various topics such as hybrid electric propulsion, aerodynamic parameter identification, and autonomous flare control. The research presented in the papers contributes to the development of new technologies and innovations in aviation. [Extracted from the article]

Estimating and controlling dynamical systems from observable time-series data are essential for understanding and manipulating nonlinear dynamics. This paper proposes a probabilistic framework for simultaneously estimating and controlling nonlinear dynamics under noisy observation conditions. Our proposed method utilizes the particle filter not only as a state estimator and a prior estimator for the dynamics but also as a controller. This approach allows us to handle the nonlinearity of the dynamics and uncertainty of the latent state. We apply two distinct dynamics to verify the effectiveness of our proposed framework: a chaotic system defined by the Lorenz equation and a nonlinear neuronal system defined by the Morris–Lecar neuron model. The results indicate that our proposed framework can simultaneously estimate and control complex nonlinear dynamical systems. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

High-quality identification schemes are essential for controller design of nonlinear systems in the field of automatic control. In control communities, the prescribed performance technology has received wide attention as a promising methodology because of its quantitative description of the steady-state and transient performance of system control over the past several years. The improved transient performance of the parameter estimation is widely known to enable simplified controller design, reduce system regulation time, and prevent system divergence. However, in system identification communities, few studies on the transient performance of parameter identification have been published because of the difficulties in designing an error variable that reflects the transient performance of parameter identification. To address this problem, this study provides a solution by integrating the prescribed performance technique into the estimator design. In this study, we introduced an adaptively prescribed performance parameter identification for nonlinear sandwich systems subjected to quantitative observations. First, a low-pass filter and forcing variables are developed to construct an identification error expression. Subsequently, an improved prescribed performance function that characterises the error bound of parameter estimation is introduced. Second, the error transformation concept is used to obtain a new system by transforming the raw system such that constraint conditions are avoided. A novel adaptive law is proposed to guarantee original parameter identification using the prescribed performance. Finally, simulation and process examples are presented to illustrate finding results. [ABSTRACT FROM AUTHOR]

The main objective of this research is to expand right coprime factorization based on operator theory in nonlinear systems. A novel method for right coprime factorization is proposed by introducing an operator that can deform the system's response into an arbitrary shape. This enables the design of control systems that are highly effective against noise. As an application, we use a pneumatic stage. The effectiveness of this method is verified through simulations and real-world experiments. [ABSTRACT FROM AUTHOR]

This paper studies a class of input-saturated nonlinear systems with Lipschitz condition. We combine the fully actuated system approach with anti-windup control to design control system. The proposed control method has the advantages of both fully actuated system approach and anti-windup control. The main advantages are: (1) establishing a fully actuated system approach control framework based on anti-windup control. The controller of the nonlinear system can be written out immediately when a fully actuated system (FAS) model or a group of FAS models of the system is derived, simplifying the steps of control system analysis and design; (2) many actual systems are FAS models, and there is no need to convert the system into a state space model; (3) the anti-windup compensator works only when the actuator saturation occurs to ensure the stability of the control system. In fact, most of the time, the system operates in an unsaturated state, which means that in most cases, the system performance is not affected. A numerical simulation example is given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Fuzzy-based control systems have demonstrated a remarkable ability to control nonlinear processes, a characteristic commonly observed in power systems, particularly in the context of power quality enhancement. Despite this, an updated and comprehensive literature review on the applications of fuzzy logic in the domain of power quality control has been lacking. To address this gap, this study critically examines published research on the effective and efficient use of fuzzy logic in resolving quality issues within power systems. Data sources included the Web of Science and academic journal databases, followed by an evaluation of target articles based on predefined criteria. The information was then classified into seven categories, including control system type, features of the fuzzy logic controller, fuzzy logic inference strategy, power quality issue, control device, implementation methodology (efficacy testing), and efficiency improvement. Our study revealed that fuzzy-based control systems have evolved from simple type-1 fuzzy controllers to advanced control systems (type-2 fuzzy and hybrid) capable of effectively addressing complex power quality issues. We believe that the insights gained from this study will be useful to both experienced and inexperienced researchers and industry engineers seeking to leverage fuzzy logic to enhance power quality control. [ABSTRACT FROM AUTHOR]

This study numerically investigates mixed convective cooling in a two‐dimensional horizontal channel containing periodically heated blocks by applying proportional (P), proportional‐integral (PI), and proportional‐integral‐derivative (PID) controllers. Three different controller configurations regulate the amount of cold air entering the chamber. The air's non‐dimensional temperature is continuously monitored at the set point to compare the controllers' performance, and the percentage of overshoot and the steady‐state error are analysed. The investigated chamber comprises one inlet and two exit ports, a temperature sensor, and two heated blocks that are isotherm heat sources. The Galerkin finite element approach computationally solves the equations of continuity, momentum, and energy to analyse the thermo‐fluid phenomena occurring within the chamber. Parametric simulation is carried for different values of the proportional gain (Kp = 0.005, 0.010, 0.050 m s−1 K−1), the integral gain (Ki = 0.05, 0.10, 0.15 m s−2 K−1), the derivative gain (Kd = 10−5, 10−4, 10−3 m K−1) to achieve a consistent and expeditious response. Variations of Reynolds, Richardson, and mean Nusselt numbers with time are plotted to compare the system's performance. The investigation indicates that the PI controller produces a comparable level of performance with the PID controller, reducing the necessity to add a derivative controller. [ABSTRACT FROM AUTHOR]

To solve the delay problem of a unified power quality conditioner (UPQC) system during the separation of the fundamental positive-order components and to better filter out the DC and harmonic components to realize accurate phase locking, a mixed second-and third-order generalized integrator phase-locked loop (MSTOGI-PLL) has been designed to replace the traditional synchronous reference frame phase-locked loop (SRF-PLL). Under the premise of adopting the new phase-locking device of MSTOGI-PLL, the active disturbance rejection control (ADRC) controller or the super-twisting algorithm (STA) sliding mode controller is used in the DC voltage control module instead of the traditional PI controller, and the suitability of the two nonlinear controllers with the MSTOGI-PLL device is investigated. First, the new MSTOGI-PLL device is designed, and the new phase-locking method is applied to make the UPQC realize accurate phase locking under the non-ideal situation of the grid voltage containing unbalance, DC component, harmonics, and so on. Based on the above foundation, the ADRC or STA controller is independently adopted to replace the PI controller to construct the UPQC system with the ADRC + MSTOGI phase-locking device and the second-order STA + MSTOGI phase-locking device. Finally, a simulation comparison is carried out in a Simulink simulation platform regarding the UPQC system under different phase-locking devices, and the simulation results demonstrate that MSTOGI-PLL can successfully filter out the DC component and resolve the phase-locking process delay issue. Additionally, the UPQC system with ADRC + MSTOGI-PLL exhibits superior immunity and response speed to the PI controller and the second-order STA controller. [ABSTRACT FROM AUTHOR]

In this paper, we propose a class of predator-prey models with nonlinear state-dependent feedback control in the saturated state. The nonlinear state impulse control leads to a diversity of pulse and phase sets such that the Poincaré map built on the corresponding phase sets behaves like the single-peak function and multi-peak function with multiple discontinuities. We start our study by analyzing the exact pulse and phase sets of models under various cases generated by the dependent parameter space of nonlinear state feedback control, then construct the Poincaré map that is followed by investigating their monotonicity, continuity, concavity, and immobility properties. We also explore the existence, uniqueness, and sufficient conditions for the global stability of the order-1 periodic solutions of the systems. Numerical simulations are carried out to illustrate and reveal the biological significance of our theoretical findings. [ABSTRACT FROM AUTHOR]

This study examines stability improvement of the power system which includes Double Feed Induction Generators (DFIGs) and Static Series Synchronous Compensator (SSSC). The proposed nonlinear controller is designed based on the terminal sliding mode control theory. A sliding mode observer is also developed to remove the need to access the information of all the state variables. The final closedloop of the power system modeling is robust against parameter variations and uncertainties. The limitations of the control signals in the process of controller design are also considered. The application of such a method increases the stability margins and results in higher robustness degrees. A comparison with other nonlinear approaches such as back-stepping and feedback linearization approaches is carried out. The results show the faster and more reliable convergence rate of the power system-controlled trajectories to reach back to the equilibrium point after occurring a sudden fault. The results are obtained by performing a simulation on the standard 39-Bus, 10 machines NEW ENGLAND power system. [ABSTRACT FROM AUTHOR]

In response to the challenges posed by large-scale, uncoordinated electric vehicle charging on the power grid, Vehicle-to-Grid (V2G) technology has been developed. This technology seeks to synchronize electric vehicles with the power grid, improving the stability of their connections and fostering positive energy exchanges between them. The key component for implementing V2G technology is the bidirectional AC/DC converter. This study concentrates on the non-isolated bidirectional AC/DC converter, providing a detailed analysis of its two-stage operation and creating a mathematical model. A dual closed-loop control structure for voltage and current is designed based on nonlinear control theory, along with a constant current charge–discharge control strategy. Furthermore, midpoint potential balance is achieved through zero-sequence voltage injection control, and power signals for the switching devices are generated using Space Vector Pulse Width Modulation (SVPWM) technology. A simulation model of the V2G system is then constructed in MATLAB/Simulink for analysis and validation. The findings demonstrate that the control strategy proposed in this paper improves the system’s robustness, dynamic performance, and resistance to interference, thus reducing the effects of large-scale, uncoordinated electric vehicle charging on the power grid.

This paper presents a novel input channel gain adaptive active disturbance rejection control (ICGA‐ADRC) framework for the nonlinear control system with large load variation. This paper first introduces the design of ICGA‐ADRC and proves its stability through the rigorous Lyapunov approach. Subsequently, the proposed controller is simulated by subjecting it to a nonlinear mass‐spring‐damping system characterized by significant load variations. Furthermore, the position‐tracking performance of the controller is tested experimentally by using a motor‐driven pendulum system with various loads. Finally, the results of both simulations and experiments show that the ICGA‐ADRC is capable of compensating for system model uncertainty and external perturbation while accurately estimating the system input channel gain in real‐time. The innovation of this paper is that the robustness of active disturbance rejection control (ADRC) to the system load variation is significantly strengthened by integrating robust adaptive finite‐time parameter estimation method into the conventional ADRC control architecture. [ABSTRACT FROM AUTHOR]

It is the first report about fault-tolerant-based prescribed performance control of switched nonlinear systems under multiple faults. The concerned faults include not only external faults but also actuator faults. In the process of backstepping control design, prescribed performance control is fully considered, and the combination of unknown nonlinear functions is estimated by multi-dimensional Taylor network. Finally, the developed adaptive fault-tolerant control strategy guarantees the boundedness of all controlled signals while prescribed tracking performance is satisfied. In an effort to further manifest the validity of the fault-tolerant controller, a numerical simulation and a practical simulation are introduced. • This paper is dedicated to balancing prescribed tracking performance and multiple faults. • It is the first time that actuator fault, external fault are discussed in the complicated switching framework. • The adaptive fault-tolerant MTN-based controller is developed to cope with performance constraints. [ABSTRACT FROM AUTHOR]

We consider a two-mass drive with a flexible joint with a nonlinear characteristic of the transmitted torque as a function of the torsion angle. We propose a new, nonlinear, adaptive position-tracking controller, taking this nonlinearity of stiffness into account. The derivation of the controller is based on nonlinear adaptive control theory, incorporates several non-standard mathematical techniques and provides a proof of the uniform ultimate boundedness of tracking errors. As the result, we present a controller that solves the position tracking problem, attenuates dangerous tortional oscillations in the shaft and operates correctly in the presence of unknown torques acting on both sides of the joint, even if all plant parameters are unknown. We demonstrate experimentally that using some materials indeed introduces a nonlinear characteristic of the joint. We prove via real plant experiments that the proposed control algorithm is easily implementable with a DSP controller in real-world applications. [ABSTRACT FROM AUTHOR]

Quasi-parametric chirped-pulse amplification (QPCPA), which features a theoretical peak power much higher than those obtained with Ti:sapphire laser or optical parametric chirped-pulse amplification, is promising for future ultra-intense lasers. The doped rare-earth ion used for idler dissipation is critical for effective QPCPA, but is usually not compatible with traditional crystals. Thus far, only one dissipative crystal of Sm3+-doped yttrium calcium oxyborate has been grown and applied. Here we introduce optical means to modify traditional crystals for QPCPA applications. We theoretically demonstrate two dissipation schemes by idler frequency doubling and sum-frequency generation with an additional laser. In contrast to absorption dissipation, the proposed nonlinear dissipations ensure not only high signal efficiency but also high small-signal gain. The demonstrated ability to optically modify crystals will facilitate the wide application of QPCPA. [ABSTRACT FROM AUTHOR]

This article discusses the challenges and research priorities related to traffic mixed with connected and automated vehicles (CAVs). The article highlights the need to understand how different types of vehicles operate and interact in heterogeneous traffic flow, as well as the evolution mechanism of mixed traffic. The special issue of the journal includes papers on driving behavior modeling, optimization, and traffic flow modeling. The papers cover topics such as simulation platforms for hybrid transportation systems, trajectory reconstruction methods, lane management strategies, fuel consumption modeling, deadlock detection and recovery methods, crash analysis, traffic flow prediction, and gantry positioning methods. The authors conclude that there is still room for future research in areas such as the relationship between the cyber and physical network of transportation systems, driving characteristics of regular vehicles, and macro-level traffic prediction and control. [Extracted from the article]

In this paper, the problem of existence-uniqueness and global exponential stability of periodic solution (i.e., stationary oscillation) for a class of nonlinear delay systems with impulses was studied. Some new sufficient conditions ensuring the existence of stationary oscillation for the addressed equations were derived by using the inequality technique that has been reported in recent publications. Our proposed method, which is different with the existing results in the literature, shows that nonlinear delay systems may admit a stationary oscillation using proper impulsive control strategies even if it was originally unstable or divergent. As an application, we considered the single species logarithmic population model and established a new criterion to guarantee the existence of positive stationary oscillation. Some numerical examples and their computer simulations were also given at the end of this paper to show the effectiveness of our development control method. [ABSTRACT FROM AUTHOR]

This paper provides a new method to nonlinear control theory, which is developed from the eigenvalue assignment method. The main purpose of this method is to locate the pointwise eigenvalues of the linear-like structure built by freezing the nonlinear systems at a given time instant in a desired disk region. Since the control requirements for the transient response characteristics are the major constraints on the selection of the disk centre and radius, two different update algorithms are also developed to reshape the disk region by changing the disk centre and radius at each time step. The effectiveness of the proposed methods is tested in both simulations and experiments. A validated three-DOF laboratory helicopter is used for experiments. [ABSTRACT FROM AUTHOR]

This contribution presents a gain adaptation, which allows us to tune a robust asymptotic feedback linearization (RAFL). The gain adaptation allows the RAFL to attenuate the measurement noise sensitivity. The RAFL is considered here because it ensures tracking without prior information about the system's nonlinearities and parameter bounds. Also, the RAFL only has the system output available for feedback. In this work, the robust tracking problem is faced considering: modeling errors, parametric variations, external perturbations, and noisy output measurement. On one side, the RAFL control faces modeling errors, parametric variations, and external perturbations through an observer that estimates uncertainties using an extra state, which lumps all the unknown nonlinearities and uncertainties. On the other hand, the proposed adaptive gain function allows the observer's high gain to vary to have a fast observer's convergence while simultaneously avoiding amplifying the measurement noise in the steady-state. The adaptive gain function provides the RAFL control robustness against noisy measurement. Thereby, the RAFL control with adaptive gain function becomes a robust feedback linearizing against to measurement noise. Finally, the RAFL controller with the adaptive gain function is illustrated by a numerical simulation of a tracking problem for a DC-motor and a chemical oxygen demand regulation in an anaerobic digestion process. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Graduate School of Natural & Applied Sciences of Mehmet Akif Ersoy University / Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi is the property of Burdur Mehmet Akif Ersoy University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this work is to provide a novel approach for studying the chaos control of hybrid nanoparticles in a porous medium under feedback control and quasiperiodic gravity sinusoidal modulation. We use the powerful tool of Fourier modes to convert the governing flow model PDEs into ordinary ones. Under the combined effect, the properties of hybrid nanofluids a silver–magnesium oxide/water can be used to suppress heat transfer in a variety of industrial applications, i.e., cooling nuclear components. Numerical data comparison with the results presented in the previous literature shows a significant agreement with the present study. On the basis of nonlinear control theory and chaotic dynamics, the equilibrium points of the system are analyzed along with the local stability. As part of the article, different aspects of hybrid nanofluids (Ag–MgO/ H 2 O ) stability are discussed, starting from the preliminary stages to the practical application of hybrid nanofluids. It has been specifically focused on preventing nonlinear conditions from being aggravated by hybrid nanofluids. A pitchfork and inverted bifurcation can occur at various control gain and frequency or amplitude parameters. As a consequence of chaos, the paper proposes the implications of feedback control combined with quasi-gravity modulation to effectively control the chaotic system. [ABSTRACT FROM AUTHOR]

Formal power series products appear in nonlinear control theory when systems modeled by Chen–Fliess series are interconnected to form new systems. In fields like adaptive control and learning systems, the coefficients of these formal power series are estimated sequentially with real-time data. The main goal is to prove the continuity and analyticity of such products with respect to several natural (locally convex) topologies on spaces of locally convergent formal power series in order to establish foundational properties behind these technologies. In addition, it is shown that a transformation group central to describing the output feedback connection is in fact an analytic Lie group in this setting with certain regularity properties. [ABSTRACT FROM AUTHOR]

This paper focuses on the implementation of a nonlinear control technique called control by state feedback for regulating the speed of a three-phase asynchronous motor. The unique aspect of this approach is the utilization of nonlinear state feedback, resulting in an interconnected mathematical structure. The main advantage of this control technique is its ability to ensure robustness against abrupt parametric variations in the motor, particularly during full load or prolonged traction tasks. To demonstrate the effectiveness of the proposed control, a series of simulations were conducted using the MATLAB-SIMULINK environment. These simulations highlighted the robustness, stability, and reliability of the control strategy. Overall, the study showcases the application of nonlinear control by state feedback as a viable solution for controlling the speed of three-phase asynchronous motors, offering enhanced resilience in the face of varying operational conditions. [ABSTRACT FROM AUTHOR]

The inverted pendulum is controlled in this article by using the nonlinear control theory. From classical analytical mechanics, its substructure equation of motion is derived. Because of the inclusion of the restoring forces, the Taylor expansion is employed to facilitate the analysis. An estimated satisfactory periodic solution is obtained with the aid of the modified Homotopy perturbation method. A numerical technique based on the fourth-order Runge–Kutta method is employed to justify the previous solution. On the other hand, a positive position feedback control is developed to dampen the vibrations of an IP system subjected to multi-excitation forces. The multiple time scale perturbation technique of the second order is introduced as a mathematical method to solve a two-degree-of-freedom system that simulates the IP with the PPF at primary and 1:1 internal resonance. The stability of these solutions is checked with the aid of the Routh–Hurwitz criterion. A set of graphs, based on the frequency response equations resulting from the MSPT method, is incorporated. Additionally, a numerical simulation is set up with RK-4 to confirm the overall controlled performance of the studied model. The quality of the solution is confirmed by the match between the approximate solution and the numerical simulation. Numerous other nonlinear systems can be controlled using the provided control method. Illustrations are offered that pertain to implications in design and pedagogy. The linearized stability of IP near the fixed points as well as the phase portraits is depicted for the autonomous and non-autonomous cases. Because of the static stability of the IP, it is found that its instability can be suppressed by the increase of both the generalized force as well as the torsional constant stiffness of the spring. Additionally, the presence of the magnetic field enhances the stability of IP. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization of nonlinear systems with external disturbances, which are both bounded and unbounded. Firstly, the stabilization problem of the nominal nonlinear system is realized, and the corresponding stabilization controllers are designed. Then, three suitable filters are proposed and applied to asymptotically estimate the corresponding disturbances, and the disturbance estimators are presented and used to exactly eliminate the corresponding disturbances. Then, the disturbance estimator (DE)-based controllers are proposed to stabilize such nonlinear systems. It should be pointed out the unbounded disturbances are exactly estimated by suitable filters, which has advantages over the existing results. Finally, two illustrative examples, which have certain symmetrical properties, are taken, and the related numerical simulations are carried out to verify the effectiveness and correctness of the proposed results. [ABSTRACT FROM AUTHOR]

In this work, a novel nonlinear control theory design for first-order systems is developed, contributing to the improvement of the existing theory. The theory will allow a design of the open loop and closed-loop controllers that ensure the tracking of any reference, constant, or variant in time with a free initial condition where the Laplace transform was used to find all the analytical solutions, avoiding the transfer function theory. Moreover, the closed-loop control will be the best option to speed up or slow down the reference convergence rate in the desired finite time. Then, an algorithm indicating the steps for designing a closed-loop controller and achieving proper tuning for a real-time application is shown. Finally, this manuscript presents the results and discussions of the theory implemented in a prototype tank of a liquid temperature control system, where the effectiveness of the applied temperature control can be seen. [ABSTRACT FROM AUTHOR]

The shaking table has been used extensively in the structure test field to verify the structure's performance against various vibrations, for example earthquakes. In order to replicate the vibrations, which are measured by the acceleration signal, the model of the shaking table should be thoroughly constructed to design the controller. However, parametric uncertainty and strong nonlinearity, such as the nonlinear friction, make it an obstacle to obtaining an accurate model. A neural network‐based controller, specifically a long short‐term memory neural network‐based neural network controller, is designed in this paper to address this issue. The nonlinear systems are estimated by the neural network's universal approximation characteristics, and a long short‐term memory neural network is utilized to optimize the time‐series‐related errors. Furthermore, a robust sliding mode controller is utilized to compensate for the residual error of the neural network and other uncertainties. The semi‐global asymptotic stability of the controller is proved by Lyapunov analysis. Comparative experimental results indicate the superiority of the proposed controller. [ABSTRACT FROM AUTHOR]

Chaotic systems arise everywhere in control theory and nonlinear vibration. This paper uses a high-precision numerical approach for capturing chaotic attractors of the fractional EI Ni ñ o chaotic systems. The numerical results indicate that some of the chaotic attractors of fractional-order systems are topologically equivalent to those discovered in the integer-order systems, and some unusual attractors of fractional EI Ni ñ o chaotic systems are found by using the present method. [ABSTRACT FROM AUTHOR]

The dynamics model of the unmanned underwater vehicle (UUV) system is highly nonlinear, multi-degree-of-freedom, strongly coupled, and time-varying. Its motion control has been a complex problem due to the unknown information about and the uncertainty of the working environment. To improve the performance and reliability of UUV trajectory tracking control, a trajectory tracking method based on nonlinear model predictive control is designed, and an improved gray wolf optimization (IGWO) is proposed for the optimization of nonlinear model predictive control. The convergence factor of IGWO is designed as a nonlinear attenuation function, and the memory function is added to the position update equation to enhance the effect of trajectory tracking control. Through the simulation in the ROS environment, the influence of the convergence factor on the convergence rate of trajectory tracking error and tracking control performance is obtained. By comparing the tracking effects of several groups of reference trajectories, it is shown that the proposed method is universally applicable and effective to the trajectory tracking control of UUV. Compared with traditional gray wolf optimization (GWO), SQP, and other optimization algorithms, the reliability of the proposed method for UUV trajectory tracking control is demonstrated. [ABSTRACT FROM AUTHOR]

This paper focuses on the synchronous vibration suppression of an active magnetic bearing (AMB) system without a rotating speed sensor. One of the most intractable problems with AMB systems is the synchronous vibration caused by the mass imbalance of the rotor. Moreover, practically all existing unbalance control algorithms require the rotating speed sensor to determine rotation speed. However, in some unique applications, it is impossible to install and use the rotating speed sensor as intended. This study provided a nonlinear adaptive control (NAC) algorithm and a modified frequency estimator to address the above issues. The proposed approach can suppress current and displacement vibrations by regulating the control structure. The frequency estimator calculates the rotating speed based on the position of the rotor at different moments, which has a quick response time, high precision, and effective tracking. The NAC algorithm can achieve unbalanced control based on the period iteration strategy. Additionally, the Lyapunov method is used to demonstrate the stability of the NAC algorithm. Finally, the experimental and simulation results also confirm the effectiveness and reliability of the overall control scheme. The results from simulations and experiments indicate that the novel frequency estimator can track the speed accurately and that its error can be regulated to within ± 0.05 Hz. The overall control schema can reduce the displacement vibration's amplitude by 72.2% and the current vibration's amplitude by 65.6%. [ABSTRACT FROM AUTHOR]

35458980 5 Tian L., Zhang Z., Zheng C., Tian Y., Zhao Y., Wang Z., Qin Y. An Improved Rapidly-Exploring Random Trees Algorithm Combining Parent Point Priority Determination Strategy and Real-Time Optimization Strategy for Path Planning. HT

In this paper, we present a new Carleman estimate for the adjoint equations associated to a class of super strong degenerate parabolic linear problems. Our approach considers a standard geometric imposition on the control domain, which can not be removed in general. Additionally, we also apply the aforementioned main inequality in order to investigate the null controllability of two nonlinear parabolic systems. The first application is concerned a global null controllability result obtained for some semilinear equations, relying on a fixed point argument. In the second one, a local null controllability for some equations with nonlocal terms is also achieved, by using an inverse function theorem. [ABSTRACT FROM AUTHOR]

In this research, a new method named d to solve non-linear constrained and un constrained optimal control problems for trajectory optimization was proposed. The main objective of this method was defined as solving optimal control problems by the combination of the orthogonal functions, the heuristic optimization techniques, and the principles of optimal control theory. Three orthogonal functions Fourier, Chebyshev, and Legendre were considered to approximate the control variables. Also, GA-PSO and imperialist competition algorithms were considered as heuristic optimization techniques. Moreover, the motivation of the mentioned method belonged to a novel combination of zero Hamiltonian in the optimal control theory, optimality conditions, and newly proposed criteria. Furthermore, lunar landing, asteroid rendezvous, and low-thrust orbital transfer with respect to minimumtime and minimum-fuel criteria were investigated to show the ability of the proposed method in regard to constrained and un constrained optimal control problems. Results demonstrated that the d method has high accuracy in the optimal control theory for non-linear problems. Hence, the d method allows space trajectory and mission designers to solve optimal control problems with a simple and precise method for future works and studies. [ABSTRACT FROM AUTHOR]

In this paper, the problem of simultaneous stabilization of a collection of nonlinear systems is proposed by using the Takagi-Sugeno (TS) fuzzy modeling and synthesis approach. In practice, due to the uncertainty in the system model, failure modes, or different operating points, we often encounter the problem of simultaneous stabilization. The TS fuzzy model has been considered for the controller design of complex nonlinear systems as it provides a simple and effective concept. This problem refers to the stabilization of some nonlinear systems by utilizing a single nonlinear controller. Both state feedback and output feedback controllers are designed based on the PDC concept and by solving some linear matrix inequalities (LMIs). Moreover, to reduce the conservatisms related to using the common Lyapunov function and restrictive equality conditions in the design method, Finsler's lemma has been employed. Finally, three numerical examples are provided to show that the proposed controllers stabilize well-considered nonlinear systems. [ABSTRACT FROM AUTHOR]

In this paper, a new strategy for developing effective control policies suitable for guiding the motion of articulated mechanical systems that are described within the framework of multibody system dynamics is proposed. In particular, a scissor lift table having a pantograph topology is analytically modeled as a rigid multibody system by using a Lagrangian formulation. An operational approach is thus introduced in this investigation to design the control system that commands the motion of the lift table. In this vein, two dynamical models are developed in this investigation, namely a minimal coordinate multibody model and a redundant coordinate multibody model. While the minimal coordinate multibody model is used in the paper for the proper design of a high-performing nonlinear controller, the redundant coordinate multibody model is employed to verify both the efficiency and the effectiveness of the control approach adopted in this work, as well as for the refinement of the feedback controller parameters. More specifically, the nonlinear control system devised in this paper is based on the combination of an open-loop control architecture with a closed-loop control strategy. The open-loop control policy is determined by using a nonlinear quasi-static feedforward controller, whereas the closed-loop control action is obtained considering an error-based proportional-derivative feedback controller. With the use of the analytical models of the pantograph scissor lift system developed in this work, several numerical experiments were carried out by employing three multibody programs based on the computational environments relying on MATLAB and SIMSCAPE MULTIBODY, thereby demonstrating the readiness and the effectiveness of the control methodology proposed in this investigation. [ABSTRACT FROM AUTHOR]

In this paper, we consider the convolution closure problem for the class of strong subexponential distributions, denoted as ... are equivalent. Then, using examples constructed by Klüppelberg and Villasenor [The full solution of the convolution closure problem for convolution-equivalent distributions, J. Math. Anal. Appl., 41:79-92, 1991], we show that S-is not closed under convolution. [ABSTRACT FROM AUTHOR]

This paper presents new techniques for the trajectory design and control of nonlinear dynamical systems. The technique uses a convex polytope to bound the range of the nonlinear function and associates with each vertex an auxiliary linear system. Provided controls associated with the linear systems can be generated to satisfy an ordering constraint, the nonlinear control is computable by the interpolation of controls obtained by convex optimization. This theoretical result leads to two numerical approaches for solving the nonlinear constrained problem: one requires solving a single convex optimization problem and the other requires solving a sequence of convex optimization problems. The approaches are applied to two practical problems in aerospace engineering: a constrained relative orbital motion problem and an attitude control problem. The solve times for both problems and approaches are on the order of seconds. It is concluded that these techniques are rigorous and of practical use in solving nonlinear trajectory design and control problems. [ABSTRACT FROM AUTHOR]

This work presents a nonlinear model predictive control scheme with a novel structure of observers aiming to create a methodology that allows feasible implementations in industrial anaerobic reactors. In this way, a new step-by-step procedure scheme has been proposed and tested by solving two specific drawbacks reported in the literature responsible for the inefficiencies of those systems in real environments. Firstly, the implementation of control structures based on modeling depends on microorganisms' concentration measurements; the technology that achieves this is not cost-effective nor viable. Secondly, the reaction rates cannot be considered static because, in the extended anaerobic digestion model (EAM2), the large fluctuation of parameters is unavoidable. To face these two drawbacks, the concentration of acidogens and methanogens, and the values of the two reaction rates considered have been estimated by a structure of two observers using data collected by sensors. After 90 days of operation, the error in convergence was lower than 5% for both observers. Four model predictive controller (MPC) configurations are used to test all the previous information trying to maximize the volume of methane and demonstrate a satisfactory operation in a wide range of scenarios. The results demonstrate an increase in efficiency, ranging from 17.4% to 24.4%, using as a reference an open loop configuration. Finally, the operational robustness of the MPC is compared with simulations performed by traditional alternatives used in industry, the proportional-integral-derivative (PID) controllers, where some simple operational scenarios to manage for an MPC are longer sufficient to disrupt a normal operation in a PID controller. For this controller, the simulation shows an error close to the 100% of the reference value. [ABSTRACT FROM AUTHOR]

In this paper, we propose a nonlinear state feedback controller based on linear matrix inequality (LMI) for a class of nonlinear systems with parametric uncertainties and external disturbances. The primary goals of the proposed controller are to guarantee system stability and performance in the presence of system uncertainties and time-dependent disturbances. To meet the specified objectives, the LMI form is calculated as a hierarchical control structure. Using the Lyapunov stability function, the asymptotic stability of the nominal system obtained from the nonlinear state feedback is proven, and the LMI condition is attained. After applying the nonlinear state feedback controller, asymptotic stability conditions for the nominal system are constructed using the Lyapunov function, and the nonlinear state-feedback control mechanism is determined accordingly. Considering the external disturbance as input, the terms of the state matrices are substituted in the obtained LMI, and the LMI condition for a nominal system is achieved in the presence of disturbances. The asymptotic stability condition of the uncertain system in the presence of external disturbances is determined by adding uncertainties to the system. The proposed approach yields a simple control mechanism representing an independent of system order. The performance of the proposed approach was assessed using a simulation study of a ball and beam system. [ABSTRACT FROM AUTHOR]

For the nonlinear system with partially unknown dynamic, the problems of fault estimation and fault-tolerant control are considered. A novel adaptive observer is designed to reconstruct the system state, process fault, sensor fault, and the measurement disturbance, simultaneously. The designed observer can be treated as a dynamic proportional-integral observer, where both the output information and the derivative of the output are used, while the output derivative can be unmeasurable. Utilizing the estimation information obtained by the designed observer, a nonlinear fault-tolerant control technique is proposed to stabilize the system. At the end of this article, three examples are listed to verify the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a linear-based gain-determining method for nonlinear adaptive backstepping controllers. Usually, the gains for nonlinear controllers are tuned by the trial and error method. This method becomes more difficult as the number of gains increases. A user-friendly method is proposed in this work to deal with the problem. Firstly, a linear auxiliary system is formed by separating the linear parts from the nonlinear system. Then, linear state-space techniques are used to determine the gains for state-feedback by the linear auxiliary system. After that, by converting the state-feedback gains to backstepping gains, the gains of the nonlinear backstepping controller can be determined. The proficiency of the gain-determining method is proved by simulations with two linear techniques. • Linear techniques can be used for the gain determination for nonlinear control systems. • The ascending gain solution performs better than other solutions in general. • The resulted performance of the nonlinear systems is similar to that of the desired linear systems. [ABSTRACT FROM AUTHOR]

10.3390/machines9100216 5 Shen P., Wang Y.W., Chen Y., Fu P.Q., Zhou L.J., Liu L.J. Hydrodynamic Bearing Structural Design of Blood Pump Based on Axial Passive Suspension Stability Analysis of Magnetic-Hydrodynamic Hybrid Suspension System. Research and experiments on mechatronics systems, which are a synergistic integration of mechanical engineering, electronic control, and systems concepts, have contributed significantly to the design of systems, devices, processes, and products. Based on the analysis of the static moment safety protection of the human-machine linkage model, the motor driving force required in the rehabilitation process was calculated to achieve the purpose of rationalizing the rehabilitation movement of the patient's lower limb. In [[9]], the mechanism of the lower limb rehabilitation module was simplified and the geometric relationship of the human-machine linkage mechanism was deduced. [Extracted from the article]

A mathematical model of cerebral blood flow in the form of a dynamical system is studied. The cerebral blood flow autoregulation modeling problem is treated as a nonlinear control problem and the potential and applicability of the nonlinear control theory techniques are analyzed in this respect. It is shown that the cerebral hemodynamics model in question is differentially flat. Then, the integrator backstepping approach combined with barrier Lyapunov functions is applied to construct the control laws that recover the cerebral autoregulation performance of a healthy human. Simulation results confirm the good performance and flexibility of the suggested cerebral blood flow autoregulation design. The conducted research should enrich our understanding of the mathematics behind the cerebral blood flow autoregulation mechanisms and medical treatments to compensate for impaired cerebral autoregulation, e.g., in preterm infants. [ABSTRACT FROM AUTHOR]

Large scale renewable energy systems interfaced with voltage source converters (VSCs) experience several challenging issues when integrated to weak grids. One of the specific issue i.e. control loop interaction of vector-controlled VSC under high grid impedance leads to several instability mechanism ultimately resulting in unwanted tripping of the VSC unit. As a countermeasure, a unique nonlinear adaptive stabilizing control (NASC) technique has been proposed in this paper to enhance the dynamic stability of the VSC during such scenarios. A small-signal model is developed first to examine the instability mechanism of VSC connected to weak grids under abnormal operating conditions and varying set points of the power controller. The dominant modes are identified from the analysis and a stabilizing controller is developed based on adaptive dynamic surface control philosophy for enhancing its stability. The proposed controller has been proved to be uniformly ultimately bounded using Lyapunov analysis. Besides, the stabilizing mechanism of VSC is analyzed with the proposed controller by performing small-signal stability analysis of the entire system. The efficacy of the proposed control scheme is demonstrated by performing numerical simulations in MATLAB 2017a and conducting experimental validations in controller-hardware-in-the Loop (CHIL) platform. [ABSTRACT FROM AUTHOR]

This paper, presents a mathematical model of a four-level supply chain under hyperchaos circumstances. The analysis of this model shows that the hyper-chaotic supply chain has an unstable equilibrium point. Using Lyapunov's theory of stability, the problem of designing a hyperchaotic supply chain control is investigated. The design of the nonlinear controller is performed first to synchronize two identical hyper-chaotic systems with different initial conditions and then to eliminate the chaotic behavior in the supply chain and move to one of unstable equilibrium points, as well as different desired values at different times. A different supply chain is predicted to demonstrate the performance of the controller. In the next part of numerical simulation, with the control of the distributor as the center of gravity of the model, the stability of the entire chaotic supply chain can be achieved. The most important point in designing a control strategy is the ability to implement it in the real world. Numerical simulation results in all stages show that the applied nonlinear control policy can provide supply chain stability in a short period of time, also, the behavior of control signals has low amplitude and oscillations. In other words, it represents a low cost to control the hyperchaotic supply chain network. [ABSTRACT FROM AUTHOR]