Search Results (536)

In this paper, a hybrid flying robot that utilizes water thrust and aerial propeller actuation is proposed and analyzed, with the aim of applications in hazardous tasks in the marine field, such as firefighting, ship inspections, and search and rescue missions. For such tasks, existing solutions like drones and water-powered robots inherited fundamental limitations, making their use ineffective. For instance, drones are constrained by limited flight endurance, while water-powered robots struggle with horizontal motion due to the couplings between translational motions. The proposed hydro-aerodynamic hybrid actuation in this study addresses these significant drawbacks by utilizing water thrust for sustainable vertical propulsion and propeller-based actuation for more controllable horizontal motion. The characteristics and mathematical models of the proposed flying robots are presented in detail. A state feedback controller and a proportional–integral–derivative (PID) controller are designed and implemented in order to govern the proposed robot’s motion. In particular, a linear matrix inequality approach is also proposed for the former design so that a robust performance is ensured. Simulation studies are conducted where a purely water-powered flying robot using a nozzle rotation mechanism is deployed for comparison, to evaluate and validate the feasibility of the flying robot. Results demonstrate that the proposed system exhibits superior performance in terms of stability and tracking, even in the presence of external disturbances. Full article

A well-known model of infectious diseases, described by a nonlinear system of delay differential equations, is investigated under the influence of stochastic perturbations. Using the general method of Lyapunov functional construction combined with the linear matrix inequality (LMI) approach, we derive sufficient conditions for the stability of the equilibria of the considered system. Numerical simulations illustrating the system’s behavior under stochastic perturbations are provided to support the thoretical findings. The proposed method for stability analysis is broadly applicable to other systems of nonlinear stochastic differential equations across various fields. Full article

Electric vehicles face increasing cybersecurity threats that can compromise the integrity of their electric drive systems, especially under Denial-of-Service (DoS) attacks. To precisely regulate torque and speed in electric vehicles, vector-controlled induction motor drives rely on continuous communication between controllers and sensors. This flow could be broken by a DoS attack, which could result in unstable motor operation or complete drive system failure. To address this, we propose a novel ellipsoidal-set-based state feedback controller with integral action, formulated via linear matrix inequalities (LMIs). This controller improves disturbance rejection, maintains system stability under DoS-induced input disruptions, and enhances security by constraining the system response within a bounded invariant set. The proposed tracker has a faster dynamic reaction and better disturbance attenuation capabilities than the traditional H_ꚙ control method. The effectiveness of the proposed controller is validated through a series of diverse testing scenarios. Full article

This paper introduces an extremum seeking (ES) scheme for the unknown map’s first derivative by tailoring a demodulation signal in which the closed-loop system is subject to constant transmission delays. Unlike most publications that manage delays using predictor-based methods, we are concerned with the delay-robustness of the introduced ES system via the newly developed time-delay approach. The original ES system is transformed to a nonlinear retarded-type plant with disturbances and the stability condition in the form of linear matrix inequalities is achieved. When the related bounds of the nonlinear map are not known, a rigorous practical stability proof is provided. Second, and more importantly, under the availability of prior knowledge about the nonlinear map, we are able to provide a quantitative calculation on the maximum allowable delay, the upper bound of the dither period, and the ultimate seeking error. Numerical examples are offered to exemplify the effectiveness of the proposed method. Full article

This study presents advanced control and energy management strategies for uncertain wind energy systems using a Takagi–Sugeno (T-S) fuzzy modeling framework. To address key challenges, such as system uncertainties, external disturbances, and input delays, the study integrates a fuzzy H∞ robust control approach with a neural network-based delay compensation mechanism. A fuzzy observer-based H∞ tracking controller is developed to enhance robustness and minimize the impact of disturbances. The stability conditions are rigorously derived using a quadratic Lyapunov function, H∞ performance criteria, and Young’s inequality and are expressed as Linear Matrix Inequalities (LMIs) for computational efficiency. In parallel, a neural network-based controller is employed to compensate for the input delays introduced by online learning processes. Furthermore, an energy management layer is incorporated to regulate the power flow and optimize energy utilization under varying operating conditions. The proposed framework effectively combines control and energy coordination to improve the systems’ performance. The simulation results confirm the effectiveness of the proposed strategies, demonstrating enhanced stability, robustness, delay tolerance, and energy efficiency in wind energy systems. Full article

In recent decades, the deployment of quadcopters has significantly expanded, particularly in outdoor applications such as parcel delivery. These missions require highly stable aerial platforms capable of maintaining balance under diverse environmental conditions, ensuring the safe operation of both the drone and its payload. This paper focuses on the stabilization of a quadcopter designed for outdoor use. A detailed dynamic model of a compact vertical takeoff and landing (VTOL) drone forms the basis for a non-linear control strategy targeting stability during the critical takeoff phase. The control law is designed using a quasi-linear parameter-varying (quasi-LPV) model that captures the system’s non-linear dynamics. Lyapunov theory and linear matrix inequalities (LMIs) are employed to validate the stability and design the controller. Numerical simulations demonstrate the controller’s effectiveness, and a comparative study is conducted to benchmark its performance against a reference quadrotor model. Full article

This paper presents a non-fragile observer-based dissipative control strategy for the suspension systems of electric vehicles equipped with in-wheel motors, accounting for input delays, actuator faults, and observer gain uncertainty. Traditional control approaches—such as $H_{\infty }$, passive control, and robust feedback schemes, often address these challenges in isolation and with increased conservatism. In contrast, this work introduces a unified framework that integrates fault-tolerant control, delay compensation, and robust state estimation within a dissipativity-based setting. A novel dissipativity analysis tailored to Electric Vehicle Active Suspension Systems (EV-ASSs) is developed, with nonzero delay bounds explicitly incorporated into the stability conditions. The observer is designed to ensure accurate state estimation under gain perturbations, enabling robust full-state feedback control. Stability and performance criteria are formulated via Linear Matrix Inequalities (LMIs) using advanced integral inequalities to reduce conservatism. Numerical simulations validate the proposed method, demonstrating effective fault-tolerant performance, disturbance rejection, and precise state reconstruction, thereby extending beyond the capabilities of traditional control frameworks. Full article

Improving the tracking accuracy and effectiveness of the pressurizer control system with respect to the reference signal is an effective method to enhance the safe and stable operation of nuclear reactors. This paper applies preview tracking control to the pressurizer control system. For the simplified control system model of the pressurizer, we first study its general structure, which can be characterized as a discrete-time system with state delay. Unlike conventional control systems, the system considered in this study features control inputs that are represented as cumulative sums of historical inputs. In order to design a preview tracking controller for such systems, we adopt the difference method and state augmentation technique and introduce an equality containing the reference signal and a discrete integrator to construct an augmented error system. Simultaneously, a performance signal is defined to evaluate the impact of external disturbances on system performance. Thus, the preview tracking control problem of the original system is reformulated as an $H_{\infty }$ control problem for the augmented error system. Subsequently, a memory-based state feedback controller is designed for the augmented error system. Then, by employing the Lyapunov function and linear matrix inequality (LMI), the $H_{\infty }$ preview tracking controller for the original system is derived. Finally, the proposed control strategy is applied to a pressurizer control system model, and numerical simulations are conducted to validate the effectiveness of the proposed controller by using MATLAB (R2023a, MathWorks, Natick, MA, USA). Full article

This paper proposes a high-type control loop design method for LQR-LMI based on Lyapunov and polyhedral model theory. The high-type control loop design problem is simplified into a convex constraint problem, which achieves superior tracking performance. In this framework, the input amplitude of the control signal, the poles of the closed-loop system, the suppression of external interference and the perturbation of internal parameters are considered, and the linear matrix inequality (LMI) method is effectively used to solve the problems. In this paper, the polyhedral model control theory is introduced to characterize the uncertainty of the system for the change of model parameters of the controlled plant. Aiming at the problem of external disturbance suppression, the $H_2/H_{\infty }$ control method is introduced into the system. These control methods provide the basis for the design of the high-type control loop. Compared with the simulation results of other optimization algorithms, the effectiveness and superiority of the controller parameter tuning rules in the proposed high-type control loop are verified. Full article

This paper investigates the event-triggered dissipative fuzzy tracking control problem of nonlinear networked systems with dynamic quantization and stochastic deception attacks, where the Takagi–Sugeno (T-S) fuzzy system theory is utilized to represent the studied nonlinear networked systems. The event-triggered scheme and the dynamic quantization scheme with general online adjustment rule are employed to significantly decrease the data transmission amount and achieve the rational use of the limited communication and computation resources. A stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the phenomenon of the stochastic deception attacks. The main purpose of this paper is to develop a secure event-triggered quantized tracking control scheme. This scheme guarantees the stochastic stability and prescribed dissipative tracking performance of the closed-loop system under stochastic deception attacks. Moreover, the design conditions for the desired static output feedback tracking controller are formulated in the form of linear matrix inequalities based on the matrix inequality decoupling strategy. Finally, two examples are exploited to illustrate the effectiveness of the developed tracking control scheme. Full article

This paper introduces a novel field-oriented control (FOC) strategy for an open-end stator three-phase winding induction motor (OEW-TP-IM) using dual space vector modulation-pulse width modulation (SVM-PWM) inverters. This configuration reduces common mode voltage at the motor’s terminals, enhancing efficiency and reliability. The study presents a backstepping control approach combined with a mean value theorem (MVT)-based observer to improve control accuracy and stability. Stability analysis of the backstepping controller for key control loops, including flux, speed, and currents, is conducted, achieving asymptotic stability as confirmed through Lyapunov’s methods. An advanced observer using sector nonlinearity (SNL) and time-varying parameters from convex theory is developed to manage state observer error dynamics effectively. Stability conditions, defined as linear matrix inequalities (LMIs), are solved using MATLAB R2016b to optimize the observer’s estimator gains. This approach simplifies system complexity by measuring only two line currents, enhancing responsiveness. Comprehensive simulations validate the system’s performance under various conditions, confirming its robustness and effectiveness. This strategy improves the operational dynamics of OEW-TP-IM machine and offers potential for broad industrial applications requiring precise and reliable motor control. Full article

This paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, with the dual goals of enhancing ride comfort and safety while ensuring system stability and robustness against road disturbances. The proposed approach deliberately avoids the use of Lyapunov-Krasovskii functionals, offering a more practical and computationally efficient alternative. Experimental results confirm that the proposed MR damper model outperforms traditional Lyapunov-Krasovskii-based methods. Additionally, two simulated road profiles are used to evaluate the suspension system’s behavior, further demonstrating the effectiveness of the proposed control strategy. Full article

This paper presents a secure control framework enhanced with an event-triggered mechanism to ensure resilient and resource-efficient operation under false data injection (FDI) attacks on sensor measurements. The proposed method integrates a Kalman filter and a neural network (NN) to construct a hybrid observer capable of detecting and compensating for malicious anomalies in sensor measurements in real time. Lyapunov-based update laws are developed for the neural network weights to ensure closed-loop system stability. To efficiently manage system resources and minimize unnecessary control actions, an event-triggered control (ETC) strategy is incorporated, updating the control input only when a predefined triggering condition is violated. A Lyapunov-based stability analysis is conducted, and linear matrix inequality (LMI) conditions are formulated to guarantee the boundedness of estimation and system errors, as well as to determine the triggering threshold used in the event-triggered mechanism. Simulation studies on a two-degree-of-freedom (2-DOF) robot manipulator validate the effectiveness of the proposed scheme in mitigating various FDI attack scenarios while reducing control redundancy and computational overhead. The results demonstrate the framework’s suitability for secure and resource-aware control in safety-critical applications. Full article

To improve the transient performance of speed tracking control while ensuring stability and considering actuator constraints in heavy-haul train systems, this paper proposes a novel cruise control method based on a nonparallel distributed compensation (non-PDC) fuzzy-based composite nonlinear feedback (CNF) technique. First, a low-dimensional nonlinear multi-particle error dynamics model is established based on the fencing concept, simplifying the model significantly. To facilitate controller design, a Takagi–Sugeno (T-S) fuzzy model is derived from the nonlinear model. Subsequently, sufficient conditions for the non-PDC fuzzy-based CNF controller are provided in terms of linear matrix inequalities (LMIs), with the controller design addressing asymmetric constraints on control inputs due to differing maximums of traction and braking forces. Simulations based on MATLAB/Simulink are conducted under different maneuvers to validate the effectiveness and superiority of the proposed method. The simulation results demonstrate a notable enhancement in transient performance (over 22.3% improvement in settling time) and steady-state cruise control performance for heavy-haul trains using the proposed strategy. Full article

This paper presents a new method for the simultaneous estimation of system states and unknown inputs in fractional-order Takagi–Sugeno (FO-TS) systems with unmeasurable premise variables (UPVs), by introducing a fractional-order proportional-integral unknown input observer (FO-PIUIO) based on partial state augmentation. This approach permits the estimation of both states and unknown inputs, which are essential for system monitoring and control. Partial state augmentation allows the integration of unknown inputs into a partially augmented model, ensuring accurate estimates of both states and unknown inputs. The state estimation error is formulated as a perturbed system. The convergence conditions for the state estimation errors between the system and the observer are derived using the second Lyapunov method and the $L_2$ approach. Compared to traditional integer-order unknown input observers or fuzzy observers with measurable premise variables, in our method, fractional-order dynamics are combined with partial state augmentation uniquely for the persistent estimation of states along with unknown inputs in unmeasurable premise variable systems. Such a combination allows for robust estimation even under uncertainties in systems and long memory phenomena and is a significant step forward from traditional methods. Finally, a numerical example is provided to illustrate the performance of the proposed observer. Full article