External Disturbances Research Articles

Programmable Robotic Shape Shifting and Color Morphing Dynamics Through Magneto-Mechano-Chromic Coupling.

Recreating natural organisms' dynamic shape-morphing and adaptive color-changing capabilities in a compact structure poses significant challenges but unlocks unprecedented hybridized robotic-visual applications. Overcoming programmability and predictability obstacles is key to achieving real-time, responsive changes in appearance and functionality, enhancing robot-environment-user interactions in ways previously unattainable. Herein, a Soft Magneto-Mechano-Chromic (SoMMeC) structure comprising a magnetic actuating and a synthetic photonic film, mirroring the intricate color-tuning mechanism of chameleons is devised. A model combining numerical simulation and a strain-dependent color evolution map enables precise predictions and controllable shape-color alterations across various geometrical and magnetization profiles. The SoMMeC exhibits rapid (0.1s), broad (full-visible spectrum), tether-free (remote magnetic manipulation), and programmable (model-guided control) color transformations, surpassing traditional limitations with its real-time response, broad and omnidirectional coloration for enhanced visibility, and robustness against external disturbances. The SoMMeC translates into dynamic advertising iridescence, adaptive camouflage, self-sensing, and multi-level encryption, and transcends traditional robotics by seamlessly blending dynamic movement with nuanced visual changes. It opens up a spectrum of applications that redefine robotic functionality through dynamic appearance modulation, making robotic systems more versatile, adaptive, and suitable for unexplored integrative functions.

Research on Quadrotor Control Based on Genetic Algorithm and Particle Swarm Optimization for PID Tuning and Fuzzy Control-Based Linear Active Disturbance Rejection Control

The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In this system, the outer loop position control adopts a PID controller optimized by Genetic Algorithm-based Particle Swarm Optimization (GA-PSO), while the inner loop attitude control employs a Linear Active Disturbance Rejection Controller (LADRC) with fuzzy algorithm-based adaptive tuning, forming a dual-loop control structure. Comparisons with traditional dual-loop cascaded PID controllers, conventional PID in the outer loop with LADRC in the inner loop, and conventional PID in the outer loop with fuzzy algorithm-based adaptive tuning in the inner loop demonstrate that the proposed control system can stably track the desired position and attitude angles under certain external disturbances, exhibiting excellent anti-disturbance capability and stability.

Rotational motion investigation in seismology – remote sensing by an optical fiber seismograph

This paper aims to present data recorded by a three-axial Fiber-Optic Rotational Seismograph (FORS). The laboratory and field tests showed a high correlation coefficient above 99% between two seismographs signals during the external disturbance, with an amplitude ranging from 0.5 mrad/s to 1.2 rad/s. This is achieved by ensuring a 100 ns time synchronization in the systems. At the same time, the Allan Variance analysis was applied to determine the basic parameters of random errors of the presented seismographs. The performed analysis indicates the angular random walk of 35–45 nrad/s/√Hz and a bias instability below 50 nrad/s. FORS offers the widest dynamic range available, at 170 dB, which is crucial during rotational seismology exploration due to its wide range of interest from seismology to engineering applications. Finally, a field research is also presented during an explosion in a closed limestone quarry in the border area.

Resilient and robust control strategy against deception attacks in the platoon of vehicles

AbstractA platoon must ensure the security of conducting missions due to the susceptibility of the vehicles to cyber‐attacks. The deception attack is a common type of cyber‐attack that might be introduced during data exchange through communication channels. Therefore, it can divert each vehicle by injecting uncertainty into the communication link between the agents in the cyber domain. This paper employs a leader–follower consensus system as a reference model to control the platoon vehicles. Accordingly, each agent in the reference model sends its information as a reference trajectory to its corresponding vehicle within the platoon. The vehicles are equipped with a robust local controller, enabling them to follow their desired trajectory in the presence of external disturbances. Furthermore, each vehicle employs an unknown input observer to detect a deception attack while decoupling it from external disturbances. Moreover, by introducing a switching strategy based on mode‐dependent average dwell time to the leader–follower consensus system, a novel resilient control strategy against the deception attack is implemented in the cyber domain. The resultant resilient leader–follower consensus system in the platoon retrieves and restores the attacked vehicle in the platoon to its associated states. The applicability of the proposed method is shown via simulation.

Design and Application of Fuzzy PID Controller Based on MATLAB

In an era where the development of intelligent technology is a pivotal force propelling economic advancement, enhancing production efficiency, diminishing costs, and reshaping daily life, the field of intelligent vehicle control technology has garnered significant attention among automotive researchers. The dynamics of smart cars during driving often exhibit nonlinearity and are susceptible to external environmental disturbances, such as wind resistance and road surface inequality. Traditional PID controllers have limited ability to suppress these interferences, so this study uses fuzzy PID algorithms to solve the inherent challenges in intelligent vehicle control. Through comprehensive analysis of the current landscape and technological advancements in intelligent vehicle control systems, coupled with rigorous MATLAB/Simulink simulations and real-world testing, the study showed that the overshoot of the adaptive fuzzy PID was reduced by 86% compared to the traditional PID. Consequently, it markedly enhances the precision and stability of speed control in intelligent vehicles, providing a groundbreaking perspective and practical methods for the enhancement of intelligent vehicle control systems with considerable application potential.

Stability and receptivity analyses of the heated flat-plate boundary layer with variable viscosity

This article presents the modal, non-modal, and resolvent analyses of the boundary layer developed over a heated flat-plate with temperature-dependent viscosity using linear stability theory. The governing equations are derived in the normal velocity–vorticity form by imposing small infinitesimal disturbances on the base flow with the Oberbeck-Boussinesq (OB) approximation. The spectral method is employed to discretize the governing stability equations in the wall-normal direction. The base flow comes from the similarity solution using R-K4th order method along with shooting techniques. The effects of viscosity stratification, inertia, shearing, and buoyancy on the stability of the boundary layer are investigated by varying the sensitivity parameter (ϵ), Reynolds (Re), Prandtl (Pr), and Richardson numbers (Ri). The modal analysis shows the time-asymptotic behavior of the disturbances and onset of instability is mainly caused by amplification of Tollmien–Schlichting (T-S) waves similar to as observe in the traditional Blasius case. The modal stability increases with increase in sensitivity parameter and stabilizing effects become more pronounced for liquid than gas. However, the thermal effects lead to destabilize the flow and strong destabilizing effects produced for higher Prandtl number. On the other hand, non-modal analysis displays an early transient growth of disturbances and an existence of these non-normality effects identified from the pseudospectra via. resolvent analysis. The non-modal growth increases with increase in ϵ even though T-S modes shift towards the damped region, which indicates the continuous modes in the eigenspectrum are more dominated than the discrete T-S modes due to the thermal effects. To clarify this qualitative change, a component-wise input–output analysis is performed to measure the receptivity to particular external disturbances. The results show the thermal energy of the disturbances is converted into kinetic energy due to thermal effects, resulting in strong receptivity amplification at the continuous mode due to the non-normality of the linear operator. Thus, the boundary layer under the influence of viscosity stratification, heating, and shearing effects is vulnerable to free-stream disturbances that could significantly affect bypass transition

Distributed model predictive control for asynchronous multiagent systems with self‐triggered coordinator

AbstractThis paper investigates a distributed model predictive control strategy for asynchronous nonlinear multiagent systems (MASs) with external disturbances via self‐triggered generators and prediction horizon regulators. First, a shrinking constraint related to the error between the actual state and the predicted state is introduced into the optimal control problem to enhance the robustness of the system. Then, the triggering interval and the corresponding prediction horizon are determined by altering the expression of the Lyapunov function, thus achieving a trade‐off between control performance and energy loss. By implementing the proposed algorithm, the coordination objective of the MASs is achieved under asynchronous communication. Finally, the recursive feasibility and closed‐loop stability are proven successively. An illustrative example is conducted to demonstrate the merits of the presented approach.

Prescribed-Time Dynamic Positioning Control for USV with Lumped Disturbances, Thruster Saturation and Prescribed Performance Constraints

This work studies the dynamic positioning (DP) control issue of unmanned surface vessels subjected to thruster saturation, error constraints, and lumped disturbances composed of time-varying marine environmental disturbances and model parameter uncertainties. Combining the disturbance-accurate estimation technique and the prescribed performance control strategy, a novel prescribed-time DP control scheme is established to address this challenging problem. In particular, the prescribed-time lumped disturbance observer is designed to accurately estimate external marine disturbances, which guarantees that the estimation error converges to zero within a prescribed time. Subsequently, a prescribed performance control strategy is proposed to guarantee that the positioning errors of DP surface vessels with thruster saturation constraints meet the error constraints requirements within a prescribed time. Furthermore, an anti-windup compensator is presented to mitigate the thruster saturation and improve the robustness of the DP control system. The stability analysis demonstrates that all positioning errors of the closed-loop system can converge to predefined performance constraints within a prescribed time. Finally, the numerical simulation confirms the efficacy and superiority of the proposed PTDP scheme.

Small business in structural shifts in Ukrainian economy during 2012-2022 in the context of solving the problems of economic development

The article is devoted to testing the author’s methodology for assessing the contribution of structural changes (distribution of the employees’ total number between large, medium and small enterprises) to the processes of socio-economic development in Ukraine. For this purpose, the general trends in the dynamics of the scale and efficiency of the sector of Ukrainian non-financial enterprises and the specifics of such trends for enterprises with different scales of economic activity are studied for the retrospective period 2012-2022. Due to the fundamental differences in the factors of economic dynamics, the years of relatively stable political and epidemiological situation are studied separately from the years of significant political, military-political and epidemiological disturbances. Using the additive-multiplicative model of the value added, created by Ukrainian enterprises dependence on the number of employees, the proportions of their distribution among large, medium and small enterprises and labor productivity (value added per capita) and the method of sequential substitutions, the author conducts a factor analysis of the dynamics of value added created by Ukrainian enterprises in the retrospective period. Evidence of significant convergence of the economic efficiency level of small and large enterprises during the retrospective period and the leading role of small enterprises in improving the efficiency of economic activity in Ukraine and ensuring the resilience of the economy to negative external and internal disturbances is obtained.

Adaptive Sliding Mode Control for AUV based on Backstepping and Neural Networks

Abstract Automatic Underwater Vehicle (AUV) inevitably suffers from various interference issues in the marine environment. Due to the limitations of underwater measurement methods and tools, as well as the complexity of AUV's control parameters in the underwater environment, dynamic measurement errors are easily cascaded and amplified, leading to the failure of the control system. In response to this phenomenon, this paper focuses on overcoming the influence of internal and external unknown factors in the tracking and control process of AUV trajectories. The internal factors are mainly the uncertainties generated by the model mismatch problem, and the external factors are mainly from the dynamic ocean currents. The AUV disturbances mainly affect the kinematics and dynamics levels directly or indirectly. In order to achieve the control of internal and external dynamic disturbances, we have designed a control system that employs backstepping (BS) and a sliding mode controller (SMC) with RBF neural networks to achieve the cascaded control of kinematics and dynamics. Comparison of multiple sets of simulations shows that our proposed algorithm has excellent anti-disturbance performance for dynamic conditions with low measurement accuracy.

L1 Adaptive Control for Small-Scale Unmanned Helicopters: Enhancing Speed Regulation

This paper focuses on the application of L1 adaptive control to the speed autopilot loop of small-scale unmanned helicopters. The L1 adaptive control technique is investigated for its potential to provide reliable speed control, particularly in handling external disturbances and model uncertainties. Although L1 adaptive control has been widely studied, its application to small-scale unmanned helicopters remains relatively unexplored. Through numerical simulations and a preliminary experimental test campaign conducted on a small rotary-wing platform, this paper contributes to validating L1 adaptive control as a promising solution for speed regulation in unmanned helicopter platforms.

COMBINED FIRST AND SECOND-ORDER SLIDING MODE CONTROL OF INDUCTION MOTOR

This paper uses hybrid sliding mode control to solve an output feedback tracking problem for the induction motor (IM). The main idea of this approach lies in the design of a law that ensures a smooth transition between two sliding regimes based on the choice of two sliding surfaces, one being linked to the other. The control is a combination of first and second-order sliding modes. The proposed approach controls the speed and rotor flux amplitude of the induction motor and guarantees the stability of the decoupled speed and rotor flux by using a Lyapunov method. The hybrid sliding mode algorithm provides robustness despite external disturbances and parameter variations. The controller has been implemented on an experimental setup, and results are presented to confirm the proposed method's effectiveness, robustness, and good performance.

Attitude Control System for Quadrotor Using Robust Monte Carlo Model Predictive Control

Monte Carlo Model Predictive Control (MCMPC) is a kind of non-linear Model Predictive Control (MPC) that determines control inputs using the Monte Carlo method. The Monte Carlo method used in MCMPC can handle discontinuous phenomena, and there have been reports of its application in control systems for quadrotors, where the objective is to maintain the stability of the attitude during collisions. However, as with conventional MPC, concerns remain about control performance degradation due to modeling errors and external disturbances such as unexpected wind gusts. In this study, we propose a novel Robust Monte Carlo Model Predictive Control (RMCMPC), which improves the robustness of MCMPC by considering the hypersurface known from the Sliding Mode Control (SMC) theory. The proposed RMCMPC is applied to a quadrotor attitude control system, and its effectiveness is validated through numerical simulations.

Regional efficiency analysis of fresh food cold chain logistics in China based on three-stage DEA model

PurposeAssessing the efficiency of fresh food cold chain logistics as accurately as possible is essential for industry development planning. This study was designed to analyze the efficiency of fresh food cold chain logistics in China.Design/methodology/approachA three-stage data envelopment analysis (DEA) model was used to analyze the efficiency of fresh food cold chain logistics in 30 provinces of China from 2013 to 2019. The stochastic frontier analysis (SFA) model in the second stage was used to eliminate the influence of external environmental factors and random disturbances on efficiency analysis results.Findings(1) The overall actual efficiency of fresh food cold chain logistics in China is unsatisfactory, with an average technical efficiency of 0.382 over the 7-year period. (2) The national average technical efficiency and average scale efficiency were overestimated by 29.9% and 40.0%, respectively, compared with the actual values. (3) The efficiency of fresh food cold chain logistics does not align with the level of regional economic development. (4) Distinct regional variations exist in the efficiency of fresh food cold chain logistics in China, with higher efficiencies observed in Northwest China and the Central Yangtze River regions, and the lowest efficiencies in the northeast regions.Originality/valueThis study applies a three-stage DEA model to assess the development and regional differences of fresh food cold chain logistics in China, enriching the application of models and empirical analysis in this field. By analyzing the situation in China, it provides ideas and references for other developing countries to develop cold chain logistics.

Adaptive Integral Sliding Mode Control with Chattering Elimination Considering the Actuator Faults and External Disturbances for Trajectory Tracking of 4Y Octocopter Aircraft

This paper presents a control strategy for a 4Y octocopter aircraft that is influenced by multiple actuator faults and external disturbances. The approach relies on a disturbance observer, adaptive type-2 fuzzy sliding mode control scheme, and type-1 fuzzy inference system. The proposed control approach is distinct from other tactics for controlling unmanned aerial vehicles because it can simultaneously compensate for actuator faults and external disturbances. The suggested control technique incorporates adaptive control parameters in both continuous and discontinuous control components. This enables the production of appropriate control signals to manage actuator faults and parametric uncertainties without relying only on the robust discontinuous control approach of sliding mode control. Additionally, a type-1 fuzzy logic system is used to build a fuzzy hitting control law to eliminate the occurrence of chattering phenomena on the integral sliding mode control. In addition, in order to keep the discontinuous control gain in sliding mode control at a small value, a nonlinear disturbance observer is constructed and integrated to mitigate the influence of external disturbances. Moreover, stability analysis of the proposed control method using Lyapunov theory showcases its potential to uphold system tracking performance and minimize tracking errors under specified conditions. The simulation results demonstrate that the proposed control strategy can significantly reduce the chattering effect and provide accurate trajectory tracking in the presence of actuator faults. Furthermore, the efficacy of the recommended control strategy is shown by comparative simulation results of 4Y octocopter under different failing and uncertain settings.

Observer‐based PID control for fuzzy dynamic systems with memory triggering protocol

AbstractThis paper addresses the issue of observer‐based proportional–integral–derivative control for Takagi–Sugeno fuzzy dynamic systems using a memory triggering protocol. To tackle the challenges of managing nonlinear systems, the Takagi–Sugeno fuzzy approach is employed to approximate these systems with a series of local linear models. A novel memory event‐triggering mechanism is introduced, utilizing a computer's storage unit to store historical data and adjust the triggering threshold based on this data, thereby reducing unnecessary network resource usage. Given that the system state can be affected by external disturbances and become unpredictable, an observer‐based proportional–integral–derivative controller is designed to manage these uncertainties. Finally, a car‐damper‐spring model is presented to validate the proposed methodology.

Terminal Sliding Mode Control of Microgrid Inverter Systems

ABSTRACTTo enhance the power quality of microgrid inverters and reduce the influence of changes in inductance parameters and external disturbances on the direct power control of the inverter system, a terminal sliding mode control strategy with a variable exponential power reaching law has been proposed. The designed new reaching law comprises a variable exponential term and an enhanced power term. The variable exponential term contains an arctangent function, and the power term coefficient is replaced by a function about the sliding mode. Therefore, the convergence rate can be adaptively adjusted based on different stages of the system, ensuring a faster rate of convergence throughout the process of approaching the sliding mode surface. To weaken the effects of changes in inductance parameters, a power disturbance observer is designed to estimate the internal disturbances induced by the filtered inductance in the system. Subsequently, a sliding mode control law containing disturbance observations is derived. Moreover, a variable exponential terminal sliding surface is designed to adjust the convergence rate of system errors on the sliding surface in stages, thereby enhancing the control performance of the system. The simulation results show that the new reaching law has faster convergence rate and better dynamic performance. The convergence speed of the system error can be accelerated by the designed variable exponential terminal sliding surface. The sliding mode control strategy with the variable exponential power reaching law is applicable to the power control system of three‐phase inverters in microgrids, thereby significantly enhancing the dynamic performance and robustness of the system.

STEWART PLATFORM MULTIDIMENSIONAL TRACKING CONTROL SYSTEM SYNTHESIS

Context. Creating guaranteed competitive motion control systems for complex multidimensional moving objects, including unstable ones, that operate under random controlled and uncontrolled disturbing factors, with minimal design costs, is one of the main requirements for achieving success in this class devices market. Additionally, to meet modern demands for the accuracy of motion control processes along a specified or programmed trajectory, it is essential to synthesize an optimal control system based on experimental data obtained under conditions closely approximating the real operating mode of the test object. Objective. The research presented in this article aims to synthesize an optimal tracking control system for the Stewart platform’s working surface motion, taking into account its multidimensional dynamic model. Method. The article employs a method of a multidimensional tracking control system structural transformation into an equivalent stabilization system for the motion of a multidimensional control object. It also utilizes an algorithm for synthesizing optimal stabilization systems for dynamic objects, whether stable or not, under stationary random external disturbances. The justified algorithm for synthesizing optimal stochastic stabilization systems is constructed using operations such as addition and multiplication of polynomial and fractional-rational matrices, Wiener factorization, Wiener separation of fractional-rational matrices, and the calculation of dispersion integrals. Results. As a result of the conducted research, the problem of defining the concept of analytical design for a Stewart platform’s optimal motion control system has been formalized. The results include the derived transformation equations from the tracking control system to the equivalent stabilization system of the Stewart platform’s working surface motion. Furthermore, the structure and parameters of the main controller transfer function matrix for of this control system have been determined. Conclusions. The justified use of the analytical design concept for the Stewart platform’s working surface optimal motion control system formalizes and significantly simplifies the solution to the problem of synthesizing complex dynamic systems, applying the developed technology presented in [1]. The obtained structure and parameters of the Stewart platform’s working surface motion control system main controller, which is divided into three components W1, W2, and W3, improve the tracking quality of the program signal vector, account for the cross-connections within the Stewart platform, and increase the accuracy of executing the specified trajectory by increasing the degrees of freedom in choosing the controller structure

Nonlinear Extended State Observer and Prescribed Performance Fault-Tolerant Control of Quadrotor Unmanned Aerial Vehicles Against Compound Faults

Addressing trajectory and attitude control challenges in quadrotor UAVs amid compound faults and unknown external disturbances, this paper introduces a fault-tolerant control method predicated on nonlinear extended state observers. Initially, the UAV’s dynamic model is optimized and decoupled, forming a rapid non-singular terminal sliding mode surface that circumvents the singular phenomena typical in conventional terminal sliding mode controls. A nonlinear extended state observer is then deployed to estimate the unknown states triggered by compound faults and disturbances within the control system. Theoretical analysis shows that beyond accurately estimating faults and disturbances, the proposed controllers adaptively adjust the system’s dynamic and steady-state performances, ensuring rapid stabilization of all error responses. Numerical simulations indicate significant enhancements in control precision and robustness against compound faults and disturbances, with response times and energy consumption remaining within acceptable limits for practical applications.

Finite-region dissipative control for 2-D switched systems via mode-dependent average dwell time

Dissipativity is a significant concern for 2-D switched systems, but existing research often overlooks the transient dynamics occurring within a finite region. This paper aims to address finite-region dissipativity and dissipative control for a class of Fornasini-Marchesini local state-space (FMLSS) type 2-D switched systems. The analysis employs the mode-dependent average dwell time approach. Firstly, the concept of dissipativity on finite-region for 2-D switched systems is introduced. Then, a sufficient condition under which the considered systems can demonstrate the finite-region boundedness with the external disturbances is established by the special recursive formulas. Additionally, a sufficient condition for finite-region dissipativity of the considered systems is provided. Furthermore, the dissipative state feedback controller is derived to ensure the finite-region dissipativity of the closed-loop systems. To illustrate the effectiveness of the proposed controller design approach, an example is presented.