Presence Of External Disturbances Research Articles

EFFECTIVENESS OF STEP SQUARE EXERCISES TO PREVENT FALLS IN MULTIPLE SCLEROSIS PATIENTS – A NARRATIVE REVIEW

In this study the literature review focus on the available evidence for the physiotherapy intervention to prevent falls in among multiple sclerosis. Research involved a computerized data base pertaining to studies that include the physiotherapy among multiple sclerosis patients 15 articles that showed outcomes relative to falls, physiotherapy intervention to prevent falls among selected multiple sclerosis patients with multiple sclerosis are more likely to fall, especially when walking, due to their slower proactive equilibrium reactions, decreased ability to maintain balance when reaching, central integration impairment, slow somatosensory conduction, fatigue, delayed reaction, attention deficit, difficulty maintaining stability in the presence of external disturbances, and overload fatigue of the motor cortex. Stand-related trunk instability was observed in MS patients, a rise in trunk sway, and a rise in postural sway when performing two tasks at once. Minimal literature on falls prevention there is scarcity of study which intervention among Step square exercises and Wii board exercises. AIM: The study aimed to find the effectiveness of Step square exercises to prevent falls in MS patients. KEY WORDS: Multiple sclerosis, intervention, equilibrium reactions, integration impairment, somatosensory conduction, attention deficit, motor cortex, trunk stability, trunk sway,

Formation tracking control with disturbance rejection in leader-follower multi-agent systems under dynamic event-triggered mechanism

This paper investigates the problem of time-varying formation tracking (TVFT) in a linear multi-agent systems (MASs) with external disturbance in a type of directed network topology, and proposes a formation control strategy in a leader-follower control framework with disturbance rejection under a dynamic event-triggering mechanism (DETM). Firstly, in order to improve the overall performance of the system, an extended state observer is used to estimate the status of the follower and the presence of external disturbance in real time. Secondly, a DETM is designed to avoid continuous communication between adjacent intelligent agents. And the formation tracking error between adjacent multi-agents is used to formulate a distributed TVFT control strategy. Furthermore, a compensation function is designed to actively offset the impact of time-varying disturbances on system. A Lyapunov function is then established for stability analysis, verifying the absence of Zeno behavior with this DETM. Finally, a comparative numerical simulation was conducted using an unmanned aerial vehicle (UAV) cluster case to verify that the proposed method can save communication resources to a greater extent and has good control performance.

Chattering Free Sliding-Mode Controller Design for Underactuated Tower Cranes With Uncertain Disturbance

Tower cranes are widely used in various industrial sites and require a high level of anti-disturbance performance from the crane controller due to the variability of the application environment. Although sliding mode control is a typical anti-disturbance control method, most sliding mode controllers suffer from output chattering and do not reflect well under severe external disturbances. To address these issues from a practical application perspective, a finite time sliding mode control method using the super-twisting algorithm (STA) is proposed for underactuated tower cranes operating in the presence of external disturbances. The proposed method includes a finite-time chattering-free sliding mode controller that eases the output torque chattering problem and a finite-time sliding mode observer based on STA to observe the uncertain disturbances. The observed values are then applied to the controller through feedforward compensation. Experimental results show that the proposed control method effectively weakens output torque chattering, compensates for disturbance quickly, and accurately completes control tasks.

Adaptive backstepping controller based on a novel framework for dynamic solution of an ankle rehabilitation spherical parallel robot

AbstractThis research offers an adaptive model-based methodology for autonomous control of 3-RRR spherical parallel manipulator (RSPM) based on a novel modeling framework. RSPM is an overconstrained parallel mechanism that has a variety of applications in medical procedures such as ankle rehabilitation because of its precision and accuracy. However, obtaining a complete explicit dynamic model of these mechanisms for tracking purposes has been a problematic challenge due to their inherent singularities, coupling effects of the limbs, and redundant constraints imposed by the intermediate joints. This paper presents a novel algorithm to obtain the analytical kinematic solutions of RSPMs based on the closed-loop vector method, which includes constraint analysis. By incorporating constrained kinematics into the dynamic model, a comprehensive explicit dynamic solution of the non-overconstrained version 3-RCC of RSPM is developed in task space, based on screw theory and the linear homogeneous property of algebraic equations on the manipulator twist. Based on the proposed computational framework, a robust self-tuning backstepping control (STBC) strategy is applied to the robot to overcome the effect of external disturbances and time-varying uncertainties. Furthermore, an observer-based compensation (OBC) method is presented for dealing with the nonlinear hysteresis loops of the ankle during trajectory tracking purposes. The closed-loop stability of the whole system including STBC and OBC is theoretically performed by Lyapunov methods. The proposed methodologies are validated by realistic co-simulations in different scenarios. For instant, in the presence of external disturbances, the maximum tracking error norm of STBC is 37.5% less than the sliding mode approach.

Modified Universal Integral Regulator for Quadrotor UAV in the Presence of External Disturbances

Universal Integral Regulator (UIR) is a widely used control law for control problems, it is based on sliding mode control with the inclusion of a Conditional Integrator (CI). In the original approach of this control law, the main gain is considered a constant. The purpose of this paper is to solve a quadrotor tracking problem using a new nonlinear control law based on the quadrotor tracking problem using a new nonlinear control law based on the UIR, considering the main gain dependent on the tracking error (variable gain), the control law is called in the present work as Modified Universal Integral Regulator (MUIR). It is expected that the MUIR can improve the transient response and reduce the control demand when compared to previous approaches of similar controllers. The adopted Newton-Euler quadrotor model and the controller design are treated separately in two subsystems, attitude and position control loops. The stability of MUIR is demonstrated by the use of a candidate Lyapunov function. Finally, in order to validate the robustness and choice of the proposed controllers, several numerical simulations were developed in the presence of external disturbances. Less error and control activity during transient response were observed when compared to the original Universal Integral Regulator controller.

Predictor-based constrained fixed-time sliding mode control of multi-UAV formation flight

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicle formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational burden. Initially, using the Taylor series concept, we derive the predictive models for the fixed-time sliding surface and reaching law. Subsequently, we formulate a constrained performance index by integrating these predictions with the control input. Ultimately, the optimal control input is computed through solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop fixed-time system stability in the presence of external disturbances and constraints. Furthermore, the comparative analysis with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, an experimental test is conducted to demonstrate the algorithm's potential for hardware implementation by employing the Hardware-in-the-Loop test.

Fuzzy Super-Twisting Sliding Mode Controller for Switched Reluctance Wind Power Generator in Low-Voltage DC Microgrid Applications

There is limited research focused on achieving optimal torque control performance of Switched Reluctance Generators (SRGs). The majority of existing studies tend to favor voltage or power control strategies. However, a significant drawback of SRGs is their susceptibility to high torque ripple. In power generation systems, torque ripple implicates fluctuations in the generated power of the generator. Moreover, high torque ripple can lead to mechanical vibrations and noise in the powertrain, impacting the overall system performance. In this paper, a Torque Sharing Function (TSF) with Indirect Instantaneous Torque Control (IITC) for SRG applied to Wind Energy Conversion Systems (WECS) is proposed to minimize torque ripple. The proposed method adjusts the shared reference torque function between the phases based on instantaneous torque, rather than the existing TSF methods formulated with a mathematical expression. Additionally, this paper introduces an innovative speed control scheme for SRG drive using a Fuzzy Super-Twisting Sliding Mode Command (FSTSMC) method. Notably robust against parameter uncertainties and payload disturbances, the proposed scheme ensures finite-time convergence even in the presence of external disturbances, while effectively reducing chattering. To assess the effectiveness of the proposed methods, comprehensive comparisons are made with traditional control techniques, including Proportional–Integral (PI), Integral Sliding Mode Control (ISMC), and Super-Twisting Sliding Mode Control (STSMC). The simulation results, obtained using MATLAB®/SIMULINK® under various speeds and mechanical torque conditions, demonstrate the superior performance and robustness of the proposed approaches. This study presents a thorough experimental analysis of a 250 W four-phase 8/6 SRG. The generator was connected to a DC resistive load, and the analysis focuses on assessing its performance and operational characteristics across different rotational speeds. The primary objective is to validate and confirm the efficacy of the SRG under varying conditions.

Formation fault-tolerant control for multiple UAVs with external disturbances

PurposeThe purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.Design/methodology/approachFirst, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.FindingsIt achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.Originality/valueA formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Deep Deterministic Policy Gradient (DDPG) Agent-Based Sliding Mode Control for Quadrotor Attitudes

A novel reinforcement deep learning deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the quadrotor under study is derived, and the attitude control problem is described using formulas. Second, a sliding mode controller, including its sliding mode surface and reaching law, is chosen for the nonlinear dynamic system. The stability of the designed SMC system is validated through the Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adaptively adjust the switching control gain. During the training process, the input signals for the agent are the actual and desired attitude angles, while the output action is the time-varying control gain. Finally, the trained agent mentioned above is utilized in the SMC as a parameter regulator to facilitate the adaptive adjustment of the switching control gain associated with the reaching law. The simulation results validate the robustness and effectiveness of the proposed DDPG-SMC method.

Predicting shear stress distribution on structural surfaces under internal solitary wave loading: A deep learning perspective

The density of the ocean varies unevenly along the vertical axis. In the presence of external disturbances, internal solitary waves (ISWs) are generated. The strong shear flow field induced by ISW seriously threatens the operational safety of marine structures. Therefore, it has become a hot spot to study the force law of marine structures in ISW. The existing studies are conducted when the ISW parameters are known. However, ISW is not visible in real situations, which leads to difficulties in obtaining ISW parameters. Therefore, it is of great engineering value to accomplish real-time force prediction of marine structures without knowing the ISW parameters in advance. To fill the gap, this study proposes a novel hydrodynamic prediction model with a sensor array as the sensing system and a deep learning algorithm as the decision-making system. The model successfully achieves accurate prediction of the shear stress on the cylinder in the ISW. In addition, a technique for optimizing sensor placement is proposed. This will help identify critical regions in the graphical representations to enhance exploration of flow field information. The results demonstrate that the prediction accuracy of the optimized sensor layout scheme surpasses that of randomly deployed sensors. As a result, this study will provide an important assurance for the safe operation of marine structures.

Adaptive integral sliding mode MPPT control for wind turbines with fixed‐time convergence

AbstractIn the context of increasing renewable energy penetration and the imperative for efficient utilization, this paper explores the application of maximum power point tracking (MPPT) control for wind turbines. The objective is to optimize wind power generation by maximizing energy capture efficiency while addressing challenges associated with behind‐the‐meter renewables, load flexibility, and encouraging prosumers' participation. This paper proposes an adaptive integral sliding mode MPPT control strategy for wind turbines in the presence of external disturbance and model uncertainties. A new fixed‐time integral sliding mode manifold is constructed, such that the singularity problem can be avoided in the controller design without using any piecewise continuous functions. Then, an adaptive fixed‐time MPPT controller is developed to ensure that the tracking error can converge to a small neighbourhood around zero in fixed time, where the upper bound of the convergence time can be pre‐set based on actual engineering needs by selecting appropriate parameters. By designing update law, no prior knowledge on the upper bound of the lumped uncertainties is required anymore in advance. Stability analysis of the closed‐loop system is conducted using Lyapunov stability theory, and the effectiveness of the proposed strategy is validated through numerical simulations.

Attitude tracking of rigid bodies using exponential coordinates and a disturbance observer

In this paper, we study the problem of attitude trajectory tracking of rigid bodies subject to external disturbances. The attitude control problem has been studied in the last decades and novel solutions have been proposed. Nevertheless, most of the proposed controllers only achieve local or almost global asymptotic stability without considering external disturbances. Contrary to other works, we focus on the problem of achieving almost global exponential stability of the attitude tracking errors in the presence of external disturbances using continuous control laws. We propose an attitude trajectory tracking controller based on the exponential coordinates of rotation in combination with a disturbance observer that estimates the exogenous signals. To solve this problem, we adopt a hierarchical approach, where the proposed control law is divided into a kinematic controller (outer control loop) and a velocity tracking controller (inner control loop). To design the disturbance observer, it is assumed that exogenous signals can be generated by a linear exosystem, i.e. the magnitude and phase of the disturbance are unknown. The almost global exponential stability of the closed-loop dynamics' equilibrium point was proved by a strict Lyapunov function. The performance of the proposed approach is assessed by numerical simulations and experimental tests on a low-cost quadrotor.

Finite-time sliding-mode tracking control of uncertain chaotic systems in the presence of an external disturbance and an input saturation

ABSTRACT The study presents a Finite-time Sliding-mode Tracking Control (FSTC) technique to achieve the trajectory tracking of an uncertain chaotic system. The feature of the proposed control strategy possesses a high level of robustness even when the uncertain chaotic system is in the presence of external disturbances and input saturation. First, a nonlinear sliding surface with a fractional-order term is constructed using tracking errors so that the finite-time convergence of tracking errors can be attained. The design of the nonlinear sliding surface, i.e. the selection of control parameters, can shape the system response. Since chattering will result from such control design, a boundary layer is adopted in the controller design to mitigate the high-frequency switching of control signal inputs. The overall system stability and finite-time convergence of the tracking error are verified using Lyapunov stability criteria and the relevant lemma. Finally, the proposed FSTC is applied to the Genesio chaotic system in the presence of uncertainty, external disturbance, and input saturation. The simulation results reveal that the proposed control scheme is indeed feasible and effective for chaotic systems control.

L2$$ {L}_2 $$‐gain analysis and fault‐tolerant control for uncertain nonlinear switched system with actuator saturation and time‐varying delay

AbstractFor the nonlinear continuous‐time switched system with input saturation and time‐varying delay, the problem of actuator failure is investigated in the presence of external disturbances. First, the sufficient conditions for the tolerance disturbances of system are obtained by using the multiple augmented Lyapunov Krasovskii functionals method combined with the Wirtinger integral inequality method and the reciprocally convex combination inequality. Second, the restricted ‐gain is analyzed. Third, the switching law and the disturbance suppression fault‐tolerant controllers are designed to obtain the maximum value of tolerance disturbance and the minimum upper bound on the restricted ‐gain. Finally, the numerical examples are given to verified the effectiveness of the proposed method by comparing the state trajectories under the action of the fault‐tolerant controllers and the standard controllers.

Fixed-time [formula omitted] tracking control of unmanned underwater vehicles with disturbance rejection via Port-Hamiltonian framework

The fixed-time tracking control schemes of unmanned underwater vehicles (UUVs) are investigated in body-fixed coordinates frame based on Port-Hamiltonian (PH) model with external disturbances. The novel locally and globally fixed-time control laws via the interconnection and damping assignment passivity-based control (IDA-PBC) are designed for trajectory tracking in UUVs. The virtual desired equilibria consisted of the tracking error and the desired trajectory are established by the matching conditions. Moreover, the fixed-time stabilization of the UUV induced of variable parameter matrixes is analyzed. Compared with the traditional IDA-PBC controller, the UUV is guaranteed to achieve the reference trajectory within a fixed time regardless of initial conditions. In the presence of external disturbances, the H∞ laws are incorporated in the fixed-time control for the UUV, which can ensure faster trajectory tracking and strong anti-disturbance. Finally, the simulation results demonstrate the effectiveness of the main schemes.

Nonlinear system controlled using novel adaptive fixed-time SMC

<abstract><p>This work introduces a novel adaptive fixed-time control strategy for nonlinear systems subject to external disturbances. The focus pertains to the introduction of the fixed-time terminal sliding mode control (FxSMC) technique. The proposed scheme exhibits rapid convergence, chatter-free and smooth control inputs, and stability within a fixed time. The utilization of an adaptive methodology in combination with the FxSMC yields the proposed strategy. This approach is employed to address the dynamic system in the presence of external disturbances. The results obtained from the Lyapunov analysis will provide insights into the stability of the closed-loop system in a fixed time. In the end, the simulation results are presented in order to assess and demonstrate the effectiveness of the methodology.</p></abstract>

Finite-Time Output Synchronization of Multiple Weighted Reaction-Diffusion Neural Networks With Adaptive Output Couplings.

This article mainly considers the output synchronization (OS) problem of multiple weighted and adaptive output coupled reaction-diffusion neural networks (RDNNs) without and with coupling delays in finite time. Without coupling delays, an adaptive control law and an output feedback controller are, respectively, proposed to ensure that the multiple weighted and output coupled RDNNs are output synchronized and output synchronized in finite time. With coupling delays, an adaptive coupling weights control scheme and a novel feedback controller are put forward to make the multiple weighted RDNNs with output couplings achieve OS in finite time. Moreover, the finite-time OS is considered in the presence of external disturbances. By the Lyapunov approach, several finite-time OS and OS criteria are given. Finally, two simulation examples are presented to justify the effectiveness of the proposed adaptive control laws and controllers.

Modified Universal Integral Regulator for Quadrotor Uav in the Presence of External Disturbances

Modified Universal Integral Regulator for Quadrotor Uav in the Presence of External Disturbances

ROBUST SENSORLESS SPEED CONTROL OF AN INDUCTION MOTOR DRIVE USING A SYNERGETIC APPROACH

This paper uses a model reference adaptive system (MRAS) to build an improved sensorless rotor-field oriented control (RFOC) induction motor (IM) drive in all speed ranges. However, in the presence of external disturbances and parameter variations, the linear tuning method of the Proportional Integrator (PI) controller in the MRAS adaptation mechanism degrades motor performance. An advanced MRAS-based synergetic technique is proposed to develop two suitable adaptation mechanisms that generate slip speed and stator resistance estimates. The reference and adjustable models are developed in the synchronous rotation coordinate system (d-q frame). The effectiveness of the proposed control algorithm was evaluated under various operating conditions using a specific sensorless IM benchmark and the MATLAB/Simulink software environment.

Improvement of sampled-data-based stabilization and dissipativity conditions for T–S fuzzy systems under network communication environment

This paper aims to develop an improved sampled-data controller for T–S fuzzy systems in the presence of external disturbances and network-induced delays. To take more advantage of information about system state responses excited during sampling and data transmission, this paper introduces novel time integrals of the weighted derivative of the system state and they are utilized to construct an improved looped functional. Additionally, a refined discontinuous function is incorporated into the Lyapunov–Krasovskii functional, and three additional zero-equalities are incorporated into the stabilization conditions to enhance the relationship between the time integrals and other components of the augmented state. Moreover, this paper devises a less conservative relaxation technique that can numerically solve the dissipativity-based stabilization conditions dependent on affine-matched fuzzy-basis functions by exploiting their strict constraints. Finally, two examples are presented to illustrate the validity and applicability of the proposed approach.