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This study explores the problem of finite-time resilient control for periodic piecewise polynomial time-varying systems in the face of parameter uncertainties, time-varying state delays and external disturbances. Particularly, the considered system is characterized by dividing the fundamental period of periodic systems into numerous subintervals, each of which can be expressed by using matrix polynomial functions. The foremost intention of this work is to lay out a resilient controller such that the resulting closed-loop system is finite-time bounded and satisfies a mixed H ∞ and passivity performance index. Furthermore, by constructing a periodic piecewise time-varying Lyapunov–Krasovskii functional, a delay-dependent sufficient condition is established in line with Wiritinger's inequality and matrix polynomial lemma to guarantee the needed outcomes of the system under study. Following this, the gain matrix of the devised controller can be calculated by solving the established constraints. As a final step, we conclude with a numerical example that validates the potential and importance of the theoretical discoveries and the developed control scheme. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of event-triggered control (ETC) for vertical take-off and landing (VTOL) aircraft systems under actuator saturation. By introducing the VTOL system with saturated actuators, a composite quadratic Lyapunov function (CQLF) approach is first proposed to describe the problem of the event triggering mechanism. The proposed transfer mechanism not only further saves communication resources, but also further suppresses the conservatism of the attraction domain estimation. Then, sufficient conditions are established via linear matrix inequality (LMI) by incorporating new event triggering mechanism condition and prescribed passive performance metrics under the closed-loop system that is asymptotically stable and strictly passive, respectively. Finally, the method proposed in this paper can effectively reduce the number of triggers and expand the domain of attraction. The validity and feasibility of the obtained results are demonstrated by two example simulations. [ABSTRACT FROM AUTHOR]

The traditional second-order sliding mode (SOSM) algorithms can only achieve the finite-time regulation for standard integrator sliding mode systems and the convergence time of which is dependent on the system's initial values and grows as the initial values grow. In this paper, we propose a novel fixed-time SOSM controller whose settling time is bounded by a fixed time independent of the system's initial values. First, a new sliding mode system subjects to a non-vanishing mismatched term is developed to reduce the input uncertainties and relax the well-defined relative degree assumption. Second, a Lyapunov criterion for practical fixed-time stability with a less conservative convergence time estimation is introduced, based on which a practical fixed-time SOSM controller is designed for the new sliding mode system. Finally, a strict Lyapunov analysis demonstrates that the closed-loop system is globally practically fixed-time stable (GPFxTS). Particularly, if the mismatched term is vanishing, global fixed-time convergence of the sliding variable to zero can be achieved. Buck converter is given as an application. [ABSTRACT FROM AUTHOR]

Precise current decoupling is required to achieve good control performance in the vector control of permanent magnet synchronous motor (PMSM), but traditional decoupling methods are unable to solve the problem of poor current decoupling effectiveness when the system inductance parameters are mismatched. Therefore, a decoupling control method of PMSM based on improved nonlinear extended state observer (INESO) is proposed in this paper. Firstly, a smooth, differentiable nonlinear function is used to replace the traditional fal function, which overcomes the problem of discontinuous gain changes. Secondly, a time-varying gain is designed to address the problem of reduced observer performance due to differential peak values in traditional NESO. Finally, the stability of INESO and the current loop closed-loop system is proven, followed by simulation and experimental verification. The simulation and experimental results show the proposed method effectively observes and compensates for system uncertainties, including parameter perturbations, external disturbances, and unmodeled dynamics. This method achieves complete decoupling of d and q -axes currents, while suppressing interference and enhancing the control performance of PMSM. The proposed INESO decoupling method reduces the d -axis current fluctuation about 96% and 90% when the load changes abruptly under motor inductance parameter mismatch, and can reduce q -axis current fluctuation about 88% and 78% when the d -axis current steps, respectively, compared with the conventional Current Feedback Decoupling Control (CFDC) and CDDC decoupling methods. [ABSTRACT FROM AUTHOR]

This paper focuses on the asynchronous finite-time control of discrete-time impulsive switched positive time-delay systems (SPLTSs). The admissible edge-dependent average dwell time (AED-ADT) approach, in which the switching behavior is represented by a directed graph, is adopted in this paper to reduce the conservatism of the mode-dependent average dwell time (MDADT) method. The new sufficient conditions for the existence of a family of asynchronously switched controllers are derived by constructing the co-positive Lyapunov functional (CLF) for asynchronous intervals and the multiple piecewise co-positive Lyapunov functional (MPCLF) for synchronous intervals, ensuring that the resulting closed-loop system is finite-time stable. Then, the desired controller gains can be obtained by solving a standard linear programming (LP) problem. Finally, two numerical examples are presented to demonstrate the validity of the developed results. [ABSTRACT FROM AUTHOR]

This paper investigates the issue of observer-based H ∞ control for a class of continuous-time-switched systems with a dynamic event-triggered strategy (DETS). First, we design a DETS that introduces an internal dynamic variable (IDV) into the event-triggered condition, which can improve data transmission efficiency and decrease the cost of the system operation by expanding the interevent intervals. Second, we establish a state observer based on the DETS and further construct an observer-based state feedback controller. It is worth noting that asynchronous switching may occur between the subsystems and the controllers under the DETS. Third, by utilizing novel Lyapunov-like functions (LLFs) with IDV and the signal-combining approach, sufficient conditions to ensure the H ∞ performance of the closed-loop system are presented. Moreover, we verify that Zeno phenomenon does not exist. Finally, the effectiveness of the proposed method is verified by two examples. [ABSTRACT FROM AUTHOR]

This study explores a closed-loop multivariable control system for HVAC systems. A hybrid distributed parameter-lumped model was developed using MATLAB's System Identification Application, resulting in a transfer function matrix. The Direct Nyquist Array (DNA) control strategy was applied, dividing the HVAC system into two SISO loops, each equipped with PID controllers. Stability analysis confirmed system stability according to the Nyquist criterion. Simulation of the system under DNA control showed improved performance over the open-loop setup, with faster response times of nearly 1 s and overshoots between 7% and 15%, maintaining thermal comfort and occupant satisfaction. The system effectively managed ambient heat transfer variations, maintaining desired airflow rate and air temperature. The closed-loop setup exhibited robustness against disturbances, quickly returning to steady-state values. Settling times ranged from 1 to 2 s with minimal impact on HVAC performance. Overall, the closed-loop multivariable DNA control with SISO PID controllers proved reliable for enhancing energy efficiency and thermal comfort in HVAC systems. Practical application: This study provides a comprehensive framework for multivariable control in HVAC systems, significantly benefiting built environment professionals by enhancing energy efficiency and occupant comfort. By applying advanced control strategies, the research offers practical solutions for optimizing HVAC performance, reducing operational costs, and ensuring sustainability in building management. The detailed analysis and methodologies presented can be directly implemented to improve system reliability and responsiveness, thereby supporting professionals in creating smarter, more resilient, and environmentally friendly built environments. [ABSTRACT FROM AUTHOR]

This paper tackles the problem of trajectory tracking for wheeled mobile robots subject to time-varying input delay and bounded external disturbances. First, we establish a dynamic model for a wheeled mobile robot under sliding and skidding conditions, and determine the maximum allowable input delay that maintains system stability using Razumikhin-type stability analysis without prior knowledge of the variation in delay. The proposed adaptive robust controller combined with super-twisting sliding mode control is resilient to disturbances such as input delay, system uncertainty, and parameter variation. The proposed adaptive law enables real-time modification of switching gain based on tracking error without predefined knowledge of uncertainty bounds. Compared with traditional sliding mode control strategies, the super-twisting algorithm can eliminate chattering phenomenon while combined robust methods further reduce modeling uncertainties' influence on system performance. Finally, we select an appropriate Lyapunov function to analyze and prove uniformly ultimately bounded of the closed-loop system. MATLAB simulation comparison results demonstrate that this approach achieves high tracking accuracy, faster response speed, and robustness. [ABSTRACT FROM AUTHOR]

This paper studies the event-triggered control for uncertain switched systems under injection attacks. An adaptive event-triggered control method for neural network–approximated switched systems (NNA-SSs) is proposed. The main works are as follows: First, a neural network is introduced to approximate the uncertain nonlinear item of the systems. Second, the observer-based adaptive event-triggering (OB-AET) strategy is designed to efficiently utilize communication and computing resources. Furthermore, the closed-loop switched systems considering injection attacks are established. By utilizing the Lyapunov function method and average dwell time technique, sufficient conditions for the exponential stability of the closed-loop switched systems are given. Accordingly, the gains of the state feedback controllers and observers are solved. Finally, simulation examples are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The paper studies the design of interval observer–based event-triggered H ∞ controller for switched systems with frequent asynchronism. We first propose an interval observer–based event-triggered mechanism, which is used to transmit the observer states and the activated mode information for controller updating. Then, we design an interval observer–based event-triggered H ∞ controller for the considered systems. By using the controller mode–dependent Lyapunov function method, sufficient conditions for the globally exponential stability of the closed-loop switched systems are obtained under average dwell time switching law. Moreover, we prove that the interevent interval length is a positive constant, which can exclude the Zeno behavior. Compared with the literature, the paper removes the strict requirement of at most one switch between two event-triggered instants, that is, frequent switches within an interevent interval are allowed. Finally, a numerical example is given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the exponential finite-time formation problems for a group of locomotive agents that maintain order on a circle. In an ideal environment, that is, without external disturbances, a combined protocol with linear continuous-time states and their nonlinear continuous functions is proposed. Each agent can adjust the movement speed itself by changing the exponent of the nonlinear function. The obtained closed-loop system will converge with an exponential speed when the initial states of the agents are far from the target location, and with a finite-time speed nearby. For the case with external disturbances, a combined protocol with linear continuous-time states and their sign functions is presented. Due to the discontinuity of the sign functions, the Filippov solutions are employed. The exponential finite-time circle formation will be achieved even in the existence of external disturbances. Moreover, the above result is extended to the application in circle containment, where the defenders will form a circle formation to surround the swarm of protectees. Finally, several computational simulations illustrate the validity of the proposed protocols. [ABSTRACT FROM AUTHOR]

For systems with higher control accuracy requirements, the requirements for convergence time are also higher, such as requiring the system to maintain stability in a finite time. This paper studies the finite-time control for input-saturated system based on the event-triggered strategy and the parametric Lyapunov equation. A finite-time state feedback controller and a finite-time output feedback controller are designed by introducing a time-varying parameter which can be obtained by solving a differential equation. The proposed methods make the closed-loop system stable in finite time and save the system resources. The designed controller overcomes the problem of slow convergence speed caused by low-gain feedback control. The numerical simulation results demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we study the balance control for the rotary inverted pendulum system with two joints both subject to uncertainty. To facilitate the experiment, we apply a classical energy-based swing-up control, eschewing compensation for the uncertainty. In balance control, we employ a novel approach in the form of a modified signal compensation-based balance control, which models the uncertainty as its previously sampled term and its variation. The signal compensation-based balance control involves three steps. First, for the linearized discrete-time state-space model around the upright equilibrium point, we design the main control signal by using the pole-placement technique. Second, we estimate the discrete-time model of the system by using the least squares identification method, thereby unveiling key points in the identification procedure. The discrete-time model presents the uncertainty as a previously sampled term and its variation. Third, we design two discrete-time compensation signals for the previously sampled term and the variation. By combining the main control signal and the two compensation signals, we formulate the balance control law. We further optimize the signal compensation-based balance control by adding an extra parameter, successfully circumventing the critical stability problem, and analyze the performance of the closed-loop system. Numerical simulation and comparative experiments demonstrate its effectiveness and strong robustness against the uncertainty in frictions and modeling errors of the system. [ABSTRACT FROM AUTHOR]

In this paper, passive control and H ∞ state feedback based on non-fragile observer are presented for a class of uncertain, nonlinear and input time-delay systems. Firstly, taking uncertainties, nonlinearities and input time-delay into account, non-fragile observer and controller are designed and the perturbations of controller gain and observer gain are processed. Secondly, for the dynamic disturbances, an appropriate non-fragile state feedback controller based on the observation is selected to prove that the states of closed-loop system can be passive and stabilized with H ∞ performance for continuous time system. Moreover, the problems such as time-delay are handled in virtue of Lyapunov method and linear matrix inequalities (LMIs). Finally, the simulation results demonstrate the validity of the proposed control design method. [ABSTRACT FROM AUTHOR]

This article investigates the fixed-time stabilization (FTS) problem for lower-triangular nonlinear systems under the p -normal form. Under suitable assumptions condition of the system's nonlinearities, a novel fixed-time partial-state feedback (PSF) control law is designed using backstepping design method and adding a power integrator (API) technique. With the help of one appropriate Lyapunov function, it is shown that the partial-state of the corresponding closed-loop system is fixed-time stable. Numerical simulation is given to illustrate the potency of the suggested continuous partial-sate feedback controller. [ABSTRACT FROM AUTHOR]

This paper is devoted to adaptive trajectory tracking of quadrotor systems with full-state constraints and random disturbances. The command-filtering technology combined with error compensation mechanisms is proposed to deal with the "explosion of complexity" problem in traditional backstepping design and reduction of the filtering errors. The Barrier Lyapunov functions (BLFs) are constructed to ensure that all system states do not violate the boundary of its constraints. The command-filtered adaptive fuzzy controller is designed such that the state constraints are not breached almost surely, all signals in the closed-loop system are bounded almost surely, and the first-order moment of the tracking error converges to an arbitrarily small neighborhood of zero by parameters tuning. Finally, the effectiveness of the proposed control method is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

This paper proposes an event-triggered model predictive-preview control strategy for autonomous vehicle trajectory tracking. First, the dynamic equation is established based on the preview road curvature and the vehicle's 2 degree-of-freedom relationship. A model predictive tracking controller is designed by predicting the system dynamics in the future. Second, to reduce the computational burden of the controller, the triggering conditions are designed according to the system's stability and feasibility. The proposed event-triggered model predictive-preview control strategy not only makes the autonomous vehicles maintain tracking accuracy but also reduces the number of online optimization. Then, asymptotically stable of closed-loop systems are proved by using Lyapunov's theorem. Finally, simulation experiments show that the proposed strategy has some advantages over traditional model predictive control in terms of improving vehicle tracking accuracy and reducing algorithm complexity. [ABSTRACT FROM AUTHOR]

In this paper, an on-line closed-loop identification of mainly mass and inertia of an under-actuated aerial vehicle, namely a quadrotor acting as an aerial manipulator, is presented. Being treated as a rigid body, only one set of eighteen- or six tri-axial linear accelerometers is used to facilitate such estimation. Force and torque disturbances acting upon the vehicle during identification are also estimated which will refine the overall estimation quality of the unknown parameters. Namely, recursive linear and nonlinear least squares methods are used to obtain initial and refined estimations, respectively. Random disturbances are introduced to the closed-loop system to ensure enough excitation of the overall system. Issues related to identifiability, stability and performance are discussed. Since the proposed method depends on general kinematical and dynamical analyses of motion, it is claimed that the presented method will be also applicable to a wider range of, mainly, aerial vehicles. [ABSTRACT FROM AUTHOR]

For the high control performance of the manipulator system, a fixed-time control algorithm based on a super-twisting disturbance observer (STDO) is designed in this paper. Firstly, an STDO is proposed to process the disturbance and then compensate the system with feedforward for the issue that the lumped disturbance is difficult to determine. On this basis, the fixed-time sliding mode (SM) surface and adaptive reaching law are designed. The reaching law gains are changed by the adaptive law to enhance the robustness and anti-interference of the system. Meanwhile, the Lyapunov theory is used to examine the stability of the closed-loop system, and it is shown that the system state can converge to a specific area during the sliding and reaching phases. Finally, the superiority and effectiveness of the control strategy raised in this work are verified by simulation. [ABSTRACT FROM AUTHOR]

Differing from the response control in civil and engineering applications, the excitation in a closed-loop sensing system is unknown and the control is designed to balance and measure the unknown excitation in real time. In this paper, a novel optimal force-balance control for a closed-loop sensing system with time delay is proposed. By introducing the errors between the control force and the unknown input as new variables, the force-balance control problem is transformed into a response minimization one with a time delay. Then, the discretization method is applied, and the continuous time system with time delay is converted into an extended discrete system without time delay, from which the analytical expression of the optimal force-balance control force is obtained. To illustrate the effectiveness of the proposed control, the optimal control of a practical quartz flexible force-balance accelerometer (FBA) is solved as an application. Numerical results show that the proposed control can realize the accurate measurement of wide-band random acceleration signals with a time delay of up to 10 times of control period. Besides, the proposed control can also significantly inhibit the vibration response of the FBA while guaranteeing measurement accuracy, which will benefit the obtaining of a large dynamic measurement range as a sensing application. [ABSTRACT FROM AUTHOR]

A fast trajectory tracking controller is designed for the airship, involving dynamic uncertainties of parameters, capable of guaranteeing the prescribed performance of tracking errors, and fast response of the closed-loop system. To achieve the decoupling of velocity control and attitude control of the airship, a new guidance and control integration framework is proposed first. Then, based on the dynamics model established by the spinor method, the lumped disturbance, caused by unknown aerodynamic parameter uncertainties and exogenous disturbances, is estimated online using a high-order finite-time observer. The control performance, namely, overshoot and steady-state performance of tracking errors, is significantly improved by utilizing the prescribed output performance constraints, while the convergence rate is further enhanced by combining the finite-time convergence property of the fast terminal sliding mode control. Simulation results attest to the effectiveness of the strategy in this paper. Compared with the adaptive fast terminal sliding mode control, the strategy effectively utilizes the capability of the actuator within the allowed range and reduces the convergence time by more than half with similar control inputs. [ABSTRACT FROM AUTHOR]

This paper proposes the finite-time state-constrained adaptive fault-tolerant control method for a class of heavy launch vehicles subject to quantized input signals and actuator faults. Firstly, the attitude dynamic model of the heavy launch vehicles suffering from the actuator faults and disturbances is formulated. Secondly, to deal with the completely unknown nonlinear functions, radial basis function neural networks (RBFNNs) are introduced for approximation and compensation. Meanwhile, the barrier Lyapunov function (BLF) is introduced to ensure that all the states in the closed-loop system are bounded and the constraints of the system states are satisfied. As a result, the finite-time state-constrained adaptive fault-tolerant control structure is constructed for the heavy launch vehicles and the semi-globally practical finite-time stability (SGPFS) of the closed-loop control system is proved. Finally, numerical simulation results show the effectiveness and the satisfactory performance of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to design a centralized model matching integer/fractional-order (FO) controller for multivariable processes. As a first step, for a linear time-delay process, a desired closed-loop reference model is formulated with the inclusion of a linear quadratic regulator with integral controller. The reference model is formulated with the objective of embodying the desired closed-loop specifications. The second step involves equating the closed-loop system with the reference model, leading to a synthesis equation that yields a higher-order controller. In the third step, the lower-order approximant of the controller is obtained by matching a set of approximate generalized time moments/approximate generalized Markov parameters of the higher-order controller to that of its lower-order approximate at a few expansion points in the s-plane. The selection of an optimal set of expansion points is formulated in an optimization problem frame with the aim of minimizing the area between responses of the desired and designed closed-loop systems, keeping the stability of the designed closed-loop system as a constraint. The efficacy of the proposed approach is illustrated by the design of different controllers for time-delay-dominated nonsquare process and FO square process. Comparative analysis is carried out using time-domain performance indices by introducing parameter uncertainty and disturbance signals. To demonstrate the applicability of the proposed method, a real-time investigation is carried out with the design and implementation of a controller for interacting hybrid (conical and spherical) tank process setup. [ABSTRACT FROM AUTHOR]

Unknown actuator failures are inevitable in practical systems. At the same time, time delay exists in many physical actuators, and the system performance will be affected by such actuator delay and faults. However, the results of studies that attempt to compensate for unknown failures of actuators with time delay are still very limited. In this paper, such a problem is studied, and an adaptive control scheme is proposed based on backstepping approaches. First, the input delay of actuator faults and output disturbances are transformed into unknown effects on the output signal. In the backstepping recursive design, these unknown effects will accumulate to the last step of the controller design. Then, a new Lyapunov function is constructed by introducing auxiliary signals to prove the stability of the system. It is shown that the proposed control scheme can compensate for the effects caused by unknown actuator failures and input delays. The stability of the closed-loop system can be guaranteed by this adaptive controller. Finally, simulation studies are used to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered control of switched two-dimensional (2D) continuous-discrete systems in Roesser model. A more general event-triggered scheme is proposed to reduce unnecessary resource waste and data redundancy, where a weighing coefficient and multiple parameter matrices are used. Based on the proposed event-triggered mechanism, a state feedback controller and a state-dependent switching signal are proposed. By using the multiple Lyapunov function method, sufficient conditions for the exponential stability of the closed-loop system are derived in terms of linear matrix inequalities. Finally, two examples are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of maximum power point tracking of photovoltaic (PV) systems in the presence of model uncertainty as well as varying load and atmospheric conditions using techniques based on a Takagi–Sugeno fuzzy model. The proposed approach relies on the linear matrix inequality tool, Lambert W function, and the Newton–Raphson method. First, adopting a quadratic Lyapunov function, an active observer-based fuzzy non-parallel distributed compensation (non-PDC) controller is designed for asymptotic tracking of the desired reference input. Next, to subdue the impact of uncertainty on the PV system, the closed-loop nominal system is regarded as a reference model, and then the main control law is developed using an online lumped uncertainty estimator and keeping the nominal control law within the staple controller. This control law does not require that the bounds on uncertainties be known. The reference voltage is determined by a novel maximum power point-seeking algorithm that is organized based on the one-diode model of PV panel, Lambert W function, and Newton–Raphson method. Finally, simulations are performed for three scenarios to point out the merits and effectiveness of the proposed methodology in the presence of system uncertainties, environmental changes, and load variations. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time sliding mode control scheme is developed to fulfill the trajectory tracking task of a marine surface vehicle with unknown dynamics. To restrain the adverse effects of the unknown dynamics including the parameter inaccuracy and exogenous disturbances, a fixed-time disturbance observer is designed to estimate the lumped uncertainties using the bi-limit homogeneous theory without requiring any knowledge of the model uncertainties. Then, a nominal tracking controller is proposed to stabilize the error dynamic model in the sense of fixed-time Lyapunov stability, based on which a novel integral-type sliding mode manifold with bi-limit homogeneity is constructed to drive tracking error convergence in fixed time. To enhance the robustness of the vessel control system, a disturbance observer–based fixed-time integral sliding mode tracking controller is finally proposed, and the chattering phenomenon is effectively alleviated by direct estimation compensations. The analysis of Lyapunov stability indicates that the closed-loop system is fixed-time stable. Numerical simulations on a model vessel are carried out to validate theoretical results of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive control for a class of constrained stochastic nonlinear systems with parametric uncertainty and input saturation. Based on a novel radial basis function neural networks (RBF NNs), the nonlinearities are tackled without the prior knowledge of NN nodes and weights. The approximate coordinate coordination is combined with an auxiliary system to attenuate the effects generated by input saturation. Then, an opportune backstepping design procedure is presented using the barrier Lyapunov function (BLF) and RBF NN. Based on this design procedure, an adaptive state–feedback controller is constructed, which makes the closed-loop system semi-globally uniformly ultimately bounded, the tracking error bounded in a compact set of the origin, and the full-states not violated. Finally, a stochastic single-link robot arm system is simulated to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a control-error-based decentralized neural network (NN) direct adaptive controller is presented for uncertain interconnected nonlinear systems, in strict-feedback form, subject to input saturation and external disturbances with unavailable states for measurement. Different from the existing results in the literature, the proposed approach is based on the control error instead of the tracking error resulting in a separation-like principle. Furthermore, the explosion of complexity due to back-stepping recursive design is completely avoided along with discarding all restrictive assumptions imposed on the unmatched interconnections. Actually, NNs are used to approximate the unknown ideal control laws, and auxiliary control terms are appended to deal with approximation errors and enhance the stability of the closed-loop system. Besides, fuzzy inference systems are introduced to estimate the unknown control errors, leading to simplified derivation of adaptive laws. Thanks to the strictly positive real (SPR) property, the tracking errors are proved to converge asymptotically to zero using Lyapunov theory, which is superior to bounded stability results usually found in the literature. Simulation results show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This work focuses on the issue of designing a fixed-time fuzzy adaptive controller for variable-speed doubly fed induction generator-based wind turbine. The main goal is to optimize the wind turbine power production, while improving the performance of the overall control system such as, convergence speed, tracking accuracy, and robustness. For the control design, the backstepping technique is adopted, and fuzzy adaptive systems are employed as universal approximators to estimate continuous functional uncertainties. Using fixed–time stability concept, a detailed mathematical stability proof of the closed-loop control system is performed. Simulation results are presented to testify the efficiency of the designed control approach. [ABSTRACT FROM AUTHOR]

This paper explores the sensing performance displayed by warp-knitted strain sensors under biaxial stretching. These sensors were knitted using silver-plated nylon to be interlooped on a tricot warp-knitting machine. Eight types of warp-knitted sensing fabrics with different loop parameters were prepared and, afterward, electro-mechanical tests were conducted on a biaxial tensile testing machine. These specimens offered similar ground structures but differed in conductive yarn configuration in terms of linear density, number of underlapping wales, open/closed loop type, and guide-bar lapping sequence. Experimental results showed that the loop parameters significantly played a fundamental role in determining sensing performance. It is therefore possible to improve the sensing performance of warp-knitted sensors and engineer them by differing the loop parameters based on certain applications. [ABSTRACT FROM AUTHOR]

This paper considers the adaptive guaranteed cost tracking (AGCT) control problems for two classes of high-order nonlinear systems with unknown parameters. A new local smooth nonlinear function (LSNF) is introduced first, which provides an important mathematical tool for our controller design. Then, based on the LSNF and the high-order fully actuated (HOFA) system approaches, the AGCT controller is designed for HOFA system with unknown parameter, which guarantees that all of the states of the closed-loop HOFA system are globally bounded, and the tracking error is asymptotically convergent. Moreover, the upper bound of cost function (UBCF) characterizing the tracking performance can be arbitrarily preseted, and is completely independent of the system initial value and the unknown parameter, which significantly improves the tracking performance, and is difficult to achieve by using existing guaranteed cost control (GCC). Furthermore, an extra result, the AGCT controller for a class of strict-feedback systems with high-order form and unknown parameters, is obtained in this paper, which also guarantees that the system tracking error is globally asymptotically convergent with the arbitrarily preseted UBCF characterizing the tracking performance. Three simulation examples, including an inverted pendulum, are presented to show the effect and the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The attitude tracking control problem of flexible spacecraft subjected to parameter uncertainties, time-dependent external disturbances, actuator input nonlinearity, and input actuator misalignment is investigated in this paper. Explicitly, the proposed strategy addresses the input actuator misalignment and dead-zone issues that increase the controller design difficulties. Initially, a new second-order sliding mode observer (SoSMO) using an extended state approach is developed by adding a correction function to improve observer performance to estimate unwanted system perturbations. Then, a distinct SoSMO-based integral-type sliding mode control (ISMC) structure is designed in a unified manner to guarantee the asymptotic stability of the closed-loop system. Comparative numerical simulations under input actuator misalignment, the dead-zone nonlinearity, external disturbance, and inertia uncertainty are performed to illustrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper is focused on asymptotic tracking control of electro-hydraulic actuator (EHA) systems subject to matched and mismatched time-varying disturbances. To counteract the matched disturbance, a novel extended state observer (ESO) is proposed to achieve asymptotic convergence of the estimation error, by incorporating the strictly positive real (SPR) Lyapunov design method and a Nussbaum function. To further suppress the mismatched disturbance, an adaptive robust integral of the sign of the error (RISE) controller is formulated in the backstepping framework based on the proposed ESO. Asymptotic tracking performance is theoretically achieved via closed-loop system stability analysis. The efficacy of the proposed control scheme is verified through comparative experiments executed on an EHA test rig. In this study, a priori bounds of the disturbances and their higher-order derivatives are no longer needed, and only one auxiliary error signal is introduced. This approach loosens the restrictions on the disturbances and reduces the design conservativeness, thus making it promising in practice. [ABSTRACT FROM AUTHOR]

In this paper, a recursive d -step-ahead predictive control scheme based on multi-dimensional Taylor network (MTN) is proposed for the real-time tracking control of multiple-input multiple-output (MIMO) nonlinear systems with input time-delay. The MTN predictive model is designed using a recursive approach to compensate the influence of time-delay, and an extended Kalman filter (EKF) is applied as its learning algorithm. An MTN controller is developed based on a proportional–integral–derivative (PID) controller where the closed-loop errors between the reference input and the system output are set as the MTN controller's inputs. Then, a back propagation (BP) algorithm, designed to update its weights according to errors caused by system uncertainty, is used as a learning algorithm for the MTN controller. Meanwhile, the convergence of the MTN predictive model and the stability of the closed-loop system are evaluated. Two numerical examples and a practical example – continuous stirred tank reactor (CSTR) process are presented to verify the superiority of the proposed scheme. The experimental results and the computational complexity analysis show that the proposed scheme is effective, promising its desirable robustness, anti-disturbance, tracking and real-time performance. [ABSTRACT FROM AUTHOR]

This paper presents an integrated guidance and control design for the homing missiles with the radome error compensation to address the guidance problems caused by radome. Firstly, a mathematics model of the integrated guidance and control system with the compensation for the radome error is built by integrating the missile dynamics and the engagement kinematics between the missile and ground target on the longitudinal motion. Secondly, the model is transformed into a normal form by nonlinear coordinate transformation because the system is a time-varying system with mismatched uncertainties. Thirdly, an adaptive control law of the system is designed by adopting the sliding mode control theory, and the stability of the closed-loop system is also conducted. Finally, the simulation proves that the proposed integrated guidance and control scheme can effectively compensate for the radome error and ensure the hit-to-kill attack to the target. [ABSTRACT FROM AUTHOR]

Robust controllers are attracting considerable interest in control of dynamic systems due to their capability of eliminating parameterized or unparameterized uncertainties. Therefore, model based robust control law is proposed in this study for ride comfort enhancement and applied on a 7 degree-of-freedom full-car suspension system with friction non-linearity. Inertia, spring and damping forces of the system are modelled with parameterized uncertainties while friction forces and external disturbances are considered as unmodelled dynamics, namely, unparameterized uncertainties. To better understand the effectiveness of proposed controller, a dry friction model that has non-linear characteristics is used for analysis. Closed-loop stability of the system is achieved by using well-known Lyapunov Stability Theorem. To better evaluate the effect of proposed robust controller on ride comfort enhancement with successful road holding, extensive numerical analysis is performed and the results are compared with those of previous similar controller and passive suspension system. The effectiveness of proposed control method has been confirmed. Consequently, satisfactory results have been obtained proving that the ride comfort of a vehicle that has both parameterized and unparameterized uncertainties has been further improved with reasonable power consumption values for a vehicle in terms of economic viability. [ABSTRACT FROM AUTHOR]

In this study, we designed an integrated fixture system using eddy current sensors and piezoelectric actuators. With this system, active supporting forces are exerted on thin-walled workpieces to adjust their stiffness in a real-time manner and thus to suppress chatter in milling. When modeling this system, we used a mass–stiffness–damping element to characterize the dynamic behavior of the actuator under high-speed responses, and we considered the electromechanical coupling between the mechanical elements and the drive circuit of the actuator. We then proposed an optimal delayed state feedback controller for the closed-loop system. The delayed state is obtained by introducing the time delay in milling dynamics into the regular state feedback, and the optimal gain is worked out through the differential quadrature and gradient descent, which is a much more computationally efficient method than the classic semi-discretization. Among all similar approaches, our strategy leads to the largest stability region for milling of thin-walled parts and requires the least energy input, which are proved by simulations and experiments. [ABSTRACT FROM AUTHOR]

This paper investigates the simultaneous control of a spacecraft with a rigid central hub and two flexible appendages. Taking into account the coupling between the vibration of flexible appendages and the motion of the hub, the rigid–flexible spacecraft subjected to external disturbance is modeled as a hybrid lumped–distributed parameter system. To attenuate the vibrations of the hub and flexible appendages and simultaneously track the given attitude angle, two boundary control laws are developed based on the original dynamic equation, where all system modes are controlled and spillover instability can be avoided. Using the active disturbance rejection control technique, two extended state observers are designed to obtain the estimation of external disturbances, which can be canceled in the negative feedback loop. The radial basis function neural network with adaptive weight law is employed to deal with the impact of input saturation. The well-posedness of the closed-loop system is proved by applying the semigroup theory. Under the rigorous Lyapunov analysis, the proposed control strategy ensures the practical stability of the rigid–flexible spacecraft system. Simulation verifies the performance of the designed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, an optimal extended state observer (ESO) is designed for nonlinear integral chain system. For the first time, in this paper, proportional–integral (PI) extremum seeking control (ESC; PIESC) approach is applied to design a perturbation observer by minimizing the estimation error. The PI type structure of the ESC provides fast transient response for the closed-loop system to attain optimum equilibrium point. A mathematical proof is presented to show that the average error dynamic asymptotically converges to zero while the estimation error is minimized. The simulation results verify that the estimation error achieved by the proposed PIESC-based ESO (PIESC-ESO) is found significantly less than that achieved by the classic ESO and PSO-based ESO. Moreover, if slow changes occur within the system or external to it, the PIESC-ESO is still able to modify the observer gains such that the estimation error is minimized again. Therefore, this may help PIESC-ESO to be used in practical applications. [ABSTRACT FROM AUTHOR]

The robust non-singular fast terminal sliding mode (NFTSM) controller is adopted in this work to solve the problem of tracking trajectory of a mobile manipulator (MM) suffering from uncertainties. The NFTSM method has the capability to ensure convergence rate and to provide good tracking accuracy and robustness against external perturbations and parameter uncertainties (total disturbances). However, the NFTSM controller needs high discontinuous gain to reject the effect of strong disturbances, which results in vibrations in the steady-state and chattering in the control law. To solve these issues, an extended state observer–based NFTSM technique is proposed for n -degree of freedom (DoF) coupling MM. The proposed method is designed to approximate and compensate in real-time the uncertainties. It also ensures robustness against total disturbances, good convergence rate, and good tracking accuracy. The stability of the proposed control is also verified based on the Lyapunov theory. Experimental works are conducted on a 5-degree-of-freedom (5-DoF) MM where the results obtained demonstrate the effectiveness of the developed technique and prove the stability of the closed-loop system. [ABSTRACT FROM AUTHOR]

In this article, a prescribed-time state-feedback stabilization design strategy is proposed for a class of p-norm stochastic nonlinear strict feedback systems. In previous work on prescribed-time stabilization of stochastic systems, only stochastic nonlinear systems with fractional power less than or equal to one are considered. To overcome this problem, we improve the existing method and discuss the issue of prescribed-time stabilization of stochastic nonlinear systems with fractional power is arbitrary positive odd rational number. First, a prescribed-time controller is designed by combining the Lyapunov function with adding a power integrator technique. It should be pointed out that the homogeneous domination approach is adopted when dealing with the nonlinear terms of the system. Then, according to the stochastic prescribed-time stability theorem, it is proved that the designed controller can ensure the closed-loop system is prescribed-time mean-square stable. Finally, three simulation examples are given to investigate the validity of the presented method, in which the last one is an electromechanical system example. [ABSTRACT FROM AUTHOR]

This paper researches the interval observer–based event-triggered control of switched linear parameter-varying (LPV) systems, which involve unknown external disturbance and measurement noise. First, we offer an event-triggering condition and a controller which are correlated with state estimations. Then, by analyzing the relationship between switching sequences and sampling sequences, we model the resulting systems as switched time-delay systems. It deserves to note that the mismatches of the switching signal for the controllers and the systems may occur due to the sampling of switching signal. Using the merging switching signal technique and the multiple Lyapunov–Krasovskii functional method, and thinking over both synchronous and asynchronous switching of the systems and the controllers, we acquire relevant conditions which are used to realize the stability of the whole switched LPV closed-loop systems under the mode-dependent average dwell time (MDADT) switching. Next, we give a specific algorithm to design the controller gains. Finally, a numerical example is provided to verify the superiority of the outcomes. [ABSTRACT FROM AUTHOR]

Driven by the increasing industrial demands for process safety and product quality, this paper is devoted to operational performance monitoring and performance degradation recovery for closed-loop control systems under abnormal working conditions. To this end, a new operational performance indicator is designed and its benchmark with an explicit sensitivity criteria for selecting historical data, to detect the system degradation timely and accurately. Then, by embedding the operational performance indicator as a trigger condition, a data-driven performance degradation recovery method with the aid of iterative adaptive dynamic programming (ADP) algorithm is investigated. This implementation shows that iterative ADP can be applied efficiently by utilizing both value iteration and measurement data to recover the anomaly induced system performance degradation. Finally, a case study on the continuous stirred tank reactor system is provided to validate the effectiveness of these proposed methods. [ABSTRACT FROM AUTHOR]

This paper introduces an H ∞ robust constrained event-triggered fuzzy controller for discrete-time nonlinear systems in the presence of system parameter uncertainties, the parameter uncertainties of the output matrices and the disturbances, simultaneously. To reduce the communication resources and improve the robust performance, the event-triggered mechanism is incorporated with the H ∞ robust fuzzy controller design. Moreover, by employing the fuzzy modeling of the actuator saturation and a nonquadratic Lyapunov function (NQLF), the ultimate bounded stability (UBS) of the closed-loop system is guaranteed subject to the amplitude limitations of the control signal. This means, a new linear matrix inequality (LMI) problem is derived to ensure the robustness and constraints in an offline scheme based on the event-triggered strategy. Besides, to meet the practical problem to further improve the controlled system performance, the control input rate constraint is also considered and a new LMI condition is provided with no online computational burden. Therefore, the computational burden of the proposed controller is greatly reduced with less conservatism. Two simulation examples including a numerical dynamic system and a truck–trailer system are employed to illustrate the less conservatism and computational complexity of the proposed method compared with the existing approaches. [ABSTRACT FROM AUTHOR]

To overcome the mutual constraints between the system chattering and the arrival time in conventional sliding mode control in this paper, a tangent excitation function (tansig) type nonlinear extended state observer (NLESO)-based integral terminal sliding mode control is proposed to solve the trajectory tracking control task of the modular robot manipulators (MRMs) possessing strong coupling and complex time-varying properties. Through the joint torque feedback technology, the MRM system dynamic model is formulated; on this basis, the proposed NLESO based on tansig is utilized to estimate and compensate the system uncertain information, which are consisted of the friction, interconnected dynamic coupling, and external disturbance. The proposed NLESO can simplify the traditional extended state observer design parameters for theoretical analysis and practical application. The proposed tansig-type NLESO-based integral terminal sliding mode control integrated adaptive term exponential reaching law for MRMs is designed to diminish the arrival time when the system state converges to the equilibrium point. The presented algorithm improves the robotic system antidisturbance ability. Furthermore, the Lyapunov theory is utilized to verify stability of the proposed NLESO and closed-loop robotic system. Finally, the availability of the proposed algorithm is demonstrated by experiments. [ABSTRACT FROM AUTHOR]

This paper studies a novel method of the dynamic event-triggered mechanisms and the predictive control scheme for discrete-time networked linear systems subject to network delays and DoS attacks in both sensor-to-controller (S − C) and controller-to-actuator (C − A) channels. First, by assuming maximum allowable duration of DoS attacks, predictive control scheme is used to proactively offset the adverse impacts of communication constraints. Second, to further save communication resources, dynamic event-triggered mechanisms are configured on sensor and controller sides, respectively. Next, sufficient condition is derived for discrete-time networked linear systems under predictive control and dynamic event-triggered mechanisms, which guarantees the resulting closed-loop system's asymptotical stability. Finally, a simulation example is used to confirm the availability and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the mixed H ∞ and passive resilient control problem for uncertain discrete-time networked control systems subject to time delays. The measurement output is considered to be quantized by the dynamic quantizer before transmission through an unreliable communication channel, where the deception attacks may occur randomly. To further reduce the communication burden, the Round-Robin (RR) protocol is adopted to schedule sensors in a predetermined transmission order. Meanwhile, a new performance index is developed to solve restriction of the same dimension of control output and the exogenous disturbance. The S-procedure combined with a two-step uncertainties elimination method is adopted to deal with the nonlinear product terms involving multiple uncertainties. Furthermore, a decoupling method is introduced for static output feedback controller design. Sufficient conditions of the resilient controller and the dynamic quantizer are provided, which can improve the robustness of resulting closed-loop system and guarantee its stochastic stability and the specified mixed H ∞ and passivity performance index. Finally, an example is given to illustrate the feasibility of the theoretical results. [ABSTRACT FROM AUTHOR]

This study provides an adaptive fuzzy control scheme for the class of nonlinear uncertain strict-feedback systems with external disturbances. The backstepping and synergetic control theories are used to develop a robust control approach for this class of systems. The unknown behaviors of the system are estimated through fuzzy systems. The stability is analyzed using the Lyapunov method, which shows that the proposed control method ensures that all the signals of the closed-loop system are bounded, and the tracking error converges approximately to zero. Two simulation examples are given to demonstrate the efficiency of the developed control approach. [ABSTRACT FROM AUTHOR]

In this paper, a linear matrix inequality (LMI)-based design is proposed for the passivity-based output feedback control problem of fractional-order static neural networks (FOSNNs). Different from the current works, the studied model is the static fractional-order neural network. The novel convex Lyapunov function is constructed to obtain new conditions for the existence of output feedback controllers which guarantee the closed-loop systems are passive. In addition, we also extend the obtained results to generalized fractional-order neural networks. A numerical example is presented to verify the proposed results. [ABSTRACT FROM AUTHOR]