Internal Disturbances Research Articles

The origins of the ukrainian economy vulnerability to negative financial-economic shifts

The article is devoted to the problem of ensuring the economic’s long-term stability in respons to external and internal cyclical disturbances. Its conceptual basis is the vision of the critical importance of the human capital reproduction and accumulation of to ensure the sustainability (resistance) of economic growth, which echoes the work of D. North, D. Wallis and B. Weingast. Accordingly, the initial hypothesis underlying the article assumes that those countries that rely on a strong social sphere that has a diversified system of funding sources are more resistant to negative disturbances. In particular, the high demand for qualified personnel makes economically justified large-scale private investment in human capital, which provides a strong resource base for the development of education and medicine. Decent living standards required for normal socialization lead to high levels of social standards, which in turn supports the breadth of the competitive field, a critical parameter needed to maintain development potential (rather than just growth) in unfavorable macroeconomic conditions.

Fuzzy modeling and control of a class of non‐differentiable multi‐input multi‐output nonlinear systems

AbstractThis paper presents a new approach in modeling and control of multi‐input multi‐output (MIMO) systems that have non‐differentiable operating points. A circle criterion is introduced at the non‐differentiable operating points to divide the entire operating region into two parts. Takagi‐Sugeno fuzzy models are developed in each part, and a switching framework is introduced to model the operating region. Accordingly, a sliding mode controller (SMC) is developed. The proposed modeling and controller are implemented on the benchmark quadruple tank process (QTP). It is demonstrated that the proposed modeling and controller design provides simplicity and universality in a set of nonlinear systems; it is robust with respect to various internal and external disturbances and model uncertainties which allows for accurate regulation and tracking; and it converges in finite time, is capable of controlling nonlinear systems with coupling dynamic, and enables fuzzy modeling of continuous‐time systems without imposing differentiability.

Subminiature Eddy Current Transducer for Detect Violations of the Internal Structure in Steels

This paper presents the design of the transducer, the action of which is based on the principles of eddy currents and is designed to identify closely located violations of the internal structure in steel parts. According to the authors of the study, the converter operates in conjunction with a specialized software application that includes hardware and software for amplifying the signal and suppressing spurious noise from the eddy current transducer. The application allows you to process the signal received from the device with digital algorithms, which positively affects the ability of the system to differentiate internal structural disturbances. The study included the results of a series of scans of samples with known cracks that are at different distances from each other. The practical limits of applicability and effectiveness of the system are illustrated in terms of detecting various structural violations. Including those located close enough to each other, in particular, closer to the maximum possible resolution distance of defects, determined solely by the geometric parameters of the eddy current transformer circuits, without taking into account mathematical processing.

Active disturbance rejection control for lower triangular uncertain stochastic nonlinear systems driven by coloured noises

In this paper, the active disturbance rejection control approach is addressed for a class of lower triangular uncertain stochastic nonlinear systems driven by coloured noises. An extended state observer is first constructed to estimate the stochastic total disturbance including the total effects of internal uncertainties and external disturbances affecting system performance, and then an active disturbance rejection controller based on estimation and compensation is designed to obtain desired closed-loop performance. It is shown with a rigorous analysis that the closed-loop state tracks a reference trajectory generated from the target system in practically mean square and almost sure sense. Some numerical simulations are performed to validate the practicality of the proposed control strategy.

A Distributed Strategy to Attitude Following of the Multi-DOF Parallel Electrical Manipulator Systems

Parallel electrical manipulator systems have become prevalent in attitude simulation in recent years to achieve a high precision attitude tracking. However, the attitude tracking performance is affected by internal uncertainty, external disturbances, and uncoordinated performance of the electric actuators. In this article, a coordinated attitude control strategy that combined the distributed active disturbance rejection control (ADRC) framework with a consensus algorithm is proposed for the parallel electrical manipulators. We indicate that the proposed coordinated attitude control strategy solves the uncoordinated problem of the electric actuators, and compensates the disturbances that include internal uncertainty and external disturbances. Meanwhile, a closed-loop control is achieved with a guaranteed stable tracking performance. The control strategy is applied to a 3-DOF parallel electrical manipulator system, and comparative experimental results indicate that the proposed coordinated ADRC consensus control strategy can achieve a better tracking performance than the strategy with only ADRC.

3-Dimensional Modeling and Attitude Control of Multi-Joint Autonomous Underwater Vehicles

To achieve rapid and flexible vertical profile exploration of deep-sea hybrid structures, a multi-joint autonomous underwater vehicle (MJ-AUV) with orthogonal joints was designed. This paper focuses on the 3-dimensional (3D) modeling and attitude control of the designed vehicle. Considering the situation of gravity and buoyancy imbalance, a 3D model of the MJ-AUV was established according to Newton’s second law and torque balance principle. And then the numerical simulation was carried out to verify the credibility of the model. To solve the problems that the pitch and yaw attitude of the MJ-AUV are coupled and the disturbance is unknown, a linear quadratic regulator (LQR) decoupling control method based on a linear extended state observer (LESO) was proposed. The system was decoupled into pitch and yaw subsystems, treated the internal forces and external disturbances of each subsystem as total disturbances, and estimated the total disturbances with LESO. The control law was divided into two parts. The first part was the total disturbance compensator, while the second part was the linear state feedback controller. The simulation results show that the overshoot of the controlled system in the dynamic process is nearly 0 rad, reaching the design value very smoothly. Moreover, when the controlled system is in a stable state, the control precision is within 0.005%.

Super-twisting SMC for MPPT and grid-connected WECS based on SCIG

This paper proposes a high-order sliding mode control (HO-SMC) with the super-twisting (ST) algorithm for maximum power point tracking (MPPT) and grid-connected wind energy conversion system (WECS), based on squirrel-cage induction generator (SCIG). The main features of this control strategy are attenuation of the chattering phenomenon inherent in first-order sliding mode control and its robustness against external and internal disturbances encountered by the wind power system. The simulation is carried out under SimPowerSystems of MATLAB/Simulink to evaluate the performance and effectiveness of the proposed control compared with conventional and fuzzy logic proportional-integral (PI) controllers for three different scenarios of disturbances, a fluctuating wind speed, a grid voltage drop, and parametric variations.

THE ROLE OF THE COMMITTEE OF THE RED CROSS IN REINFORCEMENT PROMOTING HUMANITARIAN WORK (CORONA PANDEMIC AS A MODEL)

Research on this topic aims to identify the impact of the spread of the Corona pandemic (COVID-19) this deadly epidemic, and its reflection on the reality and future of humanity, and the extent of the committee's contribution The International Red Cross in preventing the spread of this emerging virus, and knowing the role it plays in Alleviate the woes afflicting millions and the psychological problems the pandemic has left on Members of the humanitarian community, by defining their role in promoting humanitarian action, and through what It was suggested that the committee's privacy and legal status distinguish it from governmental and non-governmental agencies Governmental Affairs, through its focus on the main mission it adopts, which is to work on “Enforcement international humanitarian law faithfully. Several conclusions were reached, including: The committee does not differentiate in its work between individuals Detained in the context of internal disturbances and tensions, and perform its humanitarian mission without discrimination of Order to serve all those who are unable to defend themselves, and that the Corona pandemic (COVID-19) has created unprecedented levels of needs in mental health support and support Psychosocial among victims of the virus, their families, health workers and others.

Delay induced dynamical behaviors in a stochastic insect outbreak model in presence of Michaelis-Menten type harvesting

In this paper, we have considered stochastic insect outbreak model in presence of Michaelis-Menten type of harvesting. The growth of the insect species is taken as delayed logistic type together with a multiplicative noise term. The impact of internal environmental disturbances on the insect population is taken into account by adding an additive noise term in the model. The effects of the noises, cross correlation strength of the noises and time delay on the insect population are investigated and observed very rich dynamical behaviors. It is ascertained that multiplicative noise reduces population size greatly than additive noise. As usual, increase of harvesting of insect species reduces the population size at faster rate. Regime shift is possible depending on multiplicative noise only in contrast it is not possible via only additive noise. One of the key finding is the noise-delayed switching phenomenon for negatively correlated noises.

Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy.

Autonomous systems are expected to maintain a dependable operation without human intervention. They are intended to fulfill the mission for which they were deployed, properly handling the disturbances that may affect them. Underwater robots, such as the UX-1 mine explorer developed in the UNEXMIN project, are paradigmatic examples of this need. Underwater robots are affected by both external and internal disturbances that hamper their capability for autonomous operation. Long-term autonomy requires not only the capability of perceiving and properly acting in open environments but also a sufficient degree of robustness and resilience so as to maintain and recover the operational functionality of the system when disturbed by unexpected events. In this article, we analyze the operational conditions for autonomous underwater robots with a special emphasis on the UX-1 miner explorer. We then describe a knowledge-based self-awareness and metacontrol subsystem that enables the autonomous reconfiguration of the robot subsystems to keep mission-oriented capability. This resilience augmenting solution is based on the deep modeling of the functional architecture of the autonomous robot in combination with ontological reasoning to allow self-diagnosis and reconfiguration during operation. This mechanism can transparently use robot functional redundancy to ensure mission satisfaction, even in the presence of faults.

Coordinating Vulnerable Supply Chains with Option Contracts

We investigate vulnerable supply chain coordination with an option contract in the presence of supply chain disruption risk caused by external and internal disturbances. The supply chain consists of a single risk-neutral supplier and a risk-averse retailer. We characterize the retailer’s order quantity decision under the Conditional Value-at-Risk (CVaR) criterion and the supplier’s production decision. The results show that facing disruption risk and risk-aversion, both the retailer and the supplier would be more prudent to order and produce less than the risk-neutral scenario, inducing damage to the supply chain performance. The number of options purchased is decreasing in disruption risk and the risk-aversion of the retailer. The supplier will increase production as the disruption risk decreases or the shortage penalty increases. When the supplier does not know the risk-aversion of the retailer, the former will produce more and bear a higher overstock risk. We also investigate conditions that facilitate vulnerable supply chain coordination and find that the existence of risk-aversion and disruption risk restrict the option price and exercise price to lower price levels. Finally, we compare the option contract with wholesale price contract from the supplier’s and retailer’s perspectives through a numerical study.

Data-Driven Shape Sensing of a Surgical Continuum Manipulator Using an Uncalibrated Fiber Bragg Grating Sensor.

This article proposes a data-driven learning-based approach for shape sensing and Distal-end Position Estimation (DPE) of a surgical Continuum Manipulator (CM) in constrained environments using Fiber Bragg Grating (FBG) sensors. The proposed approach uses only the sensory data from an unmodeled uncalibrated sensor embedded in the CM to estimate the shape and DPE. It serves as an alternate to the conventional mechanics-based sensor-model-dependent approach which relies on several sensor and CM geometrical assumptions. Unlike the conventional approach where the shape is reconstructed from proximal to distal end of the device, we propose a reversed approach where the distal-end position is estimated first and given this information, shape is then reconstructed from distal to proximal end. The proposed methodology yields more accurate DPE by avoiding accumulation of integration errors in conventional approaches. We study three data-driven models, namely a linear regression model, a Deep Neural Network (DNN), and a Temporal Neural Network (TNN) and compare DPE and shape reconstruction results. Additionally, we test both approaches (data-driven and model-dependent) against internal and external disturbances to the CM and its environment such as incorporation of flexible medical instruments into the CM and contacts with obstacles in taskspace. Using the data-driven (DNN) and model-dependent approaches, the following max absolute errors are observed for DPE: 0.78 mm and 2.45 mm in free bending motion, 0.11 mm and 3.20 mm with flexible instruments, and 1.22 mm and 3.19 mm with taskspace obstacles, indicating superior performance of the proposed data-driven approach compared to the conventional approaches.

Learning Observer and Performance Tuning-Based Robust Consensus Policy for Multiagent Systems

This article addresses the multiagent systems consensus control problem via a learning observer-based performance tuning control policy. Specifically, a novel learning observer is presented to reconstruct the compound nonlinear terms and system states simultaneously. Based on the learning observer’s reconstructed information, a novel performance tuning control policy is proposed to deal with the internal nonlinear terms and external disturbances acting on the system while providing prescribed consensus performance. The proposed learning observer can guarantee the uniformly ultimately bounded estimation while saving computing resources, which is beneficial to the multiagent system. The proposed control policy, combined with observer and performance tuning, ensures the robustness to nonideal perturbations and the high accuracy control performance simultaneously. Mathematical simulations verify the effectiveness of the control algorithm.

Extended State Observer-Based Nonlinear Terminal Sliding Mode Control With Feedforward Compensation for Lower Extremity Exoskeleton

This paper presents and experimentally demonstrates an extended state observer (ESO) -based nonlinear terminal sliding mode control strategy with feedforward compensation (ESO-F-NTSMC) for lower extremity exoskeleton. Since the lower extremity exoskeleton (LEE) is a coupled human-exoskeleton coordination system, the internal or external disturbances and uncertainties affect its performance. A nonlinear terminal sliding mode control with feedforward compensation (F-NTSMC) is proposed to drive the lower extremity to shadow the target human gait trajectory. An ESO is employed to estimate the total disturbances including these caused by the chattering phenomenon in F-NTSMC. ESO-F-NTSMC can assure that the human gait trajectory tracking can converge to a bounded region smoothly and robustly. The phase identification-based human gait generation approach is also presented. The derivation process of the ESO-F-NTSMC is shown the and the Lyapunov-based stability analysis is conducted. To illustrate the proposed method’s effectiveness, experiments are performed on three human subjects walking on the floor at a natural speed. The results demonstrate that the exoskeleton can actively collaborate with the user under the proposed method.

Active disturbance rejection vibration control for an all-clamped piezoelectric plate with delay

All-clamped plate structures are usually subject to strong coupling, model uncertainties and system time-delay. To address these challenges, this work proposes a novel vibration control method based on a linear active disturbance rejection controller (LADRC) with time-delay compensation (TDC-LADRC). The mathematical model of the piezoelectric plate is first established based on system identification with an auxiliary variable method. Then ADRC is designed for the delay-free part by a smith predictor with a novel differentiator. An extended state observer (ESO) is drawn to estimate the internal and external disturbances, such as mode errors, higher harmonics and external environmental excitations. Then, real-time compensation is introduced via feed-forward mechanism to attenuate their adverse effects, so that optimal vibration suppression performance can be achieved by the proposed controller. Finally, based on NI-PCIe6343 acquisition card, an experimental set-up is designed to verify and compare the performance of the proposed TDC-LADRC against the traditional LADRC and the traditional predictor based LADRC (PLADRC). Comparative experimental results show that the proposed TDCLADRC possesses the best disturbance rejection and vibration suppression performance.

Robust singular perturbation control for 3D path following of underactuated AUVs

This paper presents a novel control scheme for the three-dimensional (3D) path following of underactuated Autonomous Underwater Vehicle (AUVs) subject to unknown internal and external disturbances, in term of the time scale decomposition method. As illustration, two-time scale motions are first artificially forced into the closed-loop control system, by appropriately selecting the control gain of the integrator. Using the singular perturbation theory, the integrator is considered as a fast dynamical control law that designed to shape the space configuration of fast variable. And then the stabilizing controller is designed in the reduced model independently, based on the time scale decomposition method, leading to a relatively simple control law. The stability of the resultant closed-loop system is demonstrated by constructing a composite Lyapunov function. Finally, simulation results are provided to prove the efficacy of the proposed controller for path following of underactuated AUVs under internal and external disturbances.

Communication Skills of Library Staff: A Cognitive Study of Turks Using Library Services in Canada

Throughout the historical ages, migration movements have occurred due to different reasons such as wars, internal disturbances, environmental disasters, economic depressions, technological developments, and education. Efficient integration of individuals into society as a result of migration depends on the development of a multicultural perspective. Libraries are among the leading institutions today in terms of recognizing different cultures. Libraries serve everyone in society without any discrimination. In multicultural societies, immigrants can quickly and easily access all kinds of information they need from cultural libraries and information centers so that they can adapt to their new places and get equal service in cultural and social fields. For instance Canada, which is an example of a multicultural society, people who have been in the country were interviewed in the study aiming to evaluate the communication skills of staff working in library services. The data obtained with the semi-structured interview technique were subjected to thematic analysis. As a result of the analysis, a total of seven sub-themes were determined with two themes, ‘Library Services' and ‘Communication Skills'.

Anti-Disturbance Dynamic Surface Control for Position Tracking of Interior Permanent Magnet Synchronous Motor Based on Nonlinear Extended State Observer

In this paper, an anti-disturbance output feedback dynamic surface control (DSC) method is proposed for the position tracking of interior permanent magnet synchronous motor subject to unknown nonlinearities and time-varying disturbances. Specifically, a nonlinear extended-state-observer (NLESO) based on exponential functions is designed to estimate the total disturbance composed of system uncertainties and external disturbances. Then, by compensating for the total disturbance via the NLESO, an anti-disturbance output feedback law is designed based on the DSC approach. The salient features of the proposed approach is twofold. First, the total uncertainty including internal and external disturbances can be accurately estimated by an NLESO in real time. Second, the desired anti-disturbance performance of the servo control system can be achieved regardless of the position measurement only. The stability of the closed-loop control system is proved by using the cascade theory and input-to-state stability theory. Both simulation and experiment results are conducted to illustrate the effectiveness of the proposed control method.

Multi-Kernel Neural Network Sliding Mode Control for Permanent Magnet Linear Synchronous Motors

In this paper, a multi-kernel neural network sliding mode control (MNNSMC) method is proposed to enhance the position tracking performance and disturbance suppression capability of permanent magnet linear synchronous motors (PMLSMs). The designed MNNSMC strategy consists of two parts, a sliding mode control with a dynamic boundary layer and a multi-kernel neural network (MNN). In the former, the dynamic boundary layer is utilized to guarantee that the sliding mode variable converges to the sliding manifold asymptotically. In the latter, disturbances are introduced into the design of kernel functions to further approximate and compensate for the internal and external disturbances, such as parameter variations, positioning force, friction, and un-modeled nonlinearities of PMLSMs. The stability of the proposed MNNSMC strategy is analyzed and proved based on Lyapunov Theorem. Experiments are conducted on a PMLSM servo drive system to validate the effectiveness of the presented MNNSMC method, and results show that the proposed scheme has significant improvement on the position tracking performance, disturbance suppression capability, and robustness of the PMLSM system compared with an existing method.

Linear active disturbance rejection control for the electro-hydraulic position servo system.

Valve-controlled asymmetric cylinder is widely used in servo loading system. As a kind of typical electro-hydraulic servo system (EHSS), it inherently has the characteristics such as high order nonlinear, strong coupling, and uncertain, therefore, conventional control strategy is difficult to satisfy the requirements of high-performance control. In this paper, a novel linear active disturbance rejection control (LADRC) method was proposed, in which the internal and external disturbances were actively estimated by the third-order linear extended state observer (LESO) in real-time, and rejected by the control law of proportional integral control (PID) with acceleration feed-forward. The stability of the proposed method was proved, and the influence rules of the LADRC parameters on the control performance were revealed by simulation. Finally, comparative experiments between LADRC and PID control were carried out, results showed that the disturbances can be effectively compensated and the control goals can be successfully achieved with the proposed method.