Stable Control Research Articles

Adversarial waypoint injection attacks on Maritime Autonomous Surface Ships (MASS) collision avoidance systems

ABSTRACT Autonomous navigation is currently subject to particular interest for naval and commercial vessels. In addition to the regulatory effort, several pieces of research tackled the development of new guidance laws, stable and robust control algorithms, methodologies to increase situational awareness, and collision avoidance algorithms. However, most of these systems blindly trust information from navigation sensors, which can malfunction or, even worse, have their data altered by cyber-attacks. This last scenario will be increasingly common shortly and represents a dangerous threat that future highly computerised ships must face. The proposed work shows an approach capable of hijacking a state-of-the-art collision avoidance algorithm route by feeding it with rogue data. The effects of such a cyber-attack are shown via an extensive simulation campaign, testing the methodology on three different COLREG scenarios: head-on, crossing, and overtaking. The study additionally highlights the susceptibility of forthcoming navigation systems to security breaches, which still needs to be addressed in the existing literature. According to the experimental findings, attackers can attract the autonomous ship guidance toward their objective at a mean distance of 133 m . Finally, suggestions on how to harden these systems against this family of attacks are provided in the conclusion.

Robust and Adaptive Stabilization Controllers of State-Constrained Nonholonomic Chained Systems: A Discontinuous Approach

In this paper, two systematic control design strategies are proposed for strict-feedback nonholonomic systems with full-state constraints to solve stabilization and adaptive stabilization problems. The stabilization schemes involve the introduction of state scaling, the barrier Lyapunov function (BLF), the integrator backstepping method, and the tuning function approach. In addition, a discontinuous switching control strategy is proposed to achieve the control goal if the first system state’s initial state is confined to zero. In both stabilization and adaptive stabilization control, the system states can be regulated at the origin, and meanwhile, the full-state constraints are realized. Finally, it is shown that the simulation results are consistent with the theory analysis results, which further demonstrates the effectiveness of the proposed control schemes.

Unmeasurable flexible dynamics monitoring and tracking controller design for guidance and control system of hypersonic flight vehicle

The guidance and control system (GCS) is an important and indispensable component of hypersonic flight vehicle (HFV), and it can be viewed as a special cyber–physical system (CPS). However, the monitoring of the HFV dynamics is difficult since the inertial navigation equipment can only provides the information of acceleration and angular rate. In this case, the flexible states of HFV are difficult to be measured. This paper proposes a sliding mode observer (SMO) based GCS design method for HFV. With considering the measurement difficulties, the flexible states of HFV are assumed to be unmeasurable. Then a SMO is designed to estimated them. Combined with the actual flight environment of HFV, the measuring devices are assumed to be suffering from disturbance, then the SMO should not only guarantee the estimation error stable, but also reduce the influence of external disturbances. What is worse, the input of HFV is suffering from input delay, which brings more difficulties to the controller design. By state transformation,input delay model of HFV is transformed into a delay free model,then a SMO based robust controller is proposed for HFV based on the stable inversion controller design strategy. By the proposed SMO based controller, the GCS can be constructed for HFV. Numeral simulation are carried on HFV, and simulation results show shat, the designed SMO can realize the monitoring of flexible states of HFV and the designed GCS can get a good tracking performance.

Zinc roasting temperature field control with CFD model and reinforcement learning

As the most critical variable in the zinc roasting process, the roasting temperature has been heavily researched for stable control through its average value. However, relying solely on the average temperature cannot convey the entire temperature field information necessary to achieve the optimal production state. To address this, This paper initially proposes a control scheme for the zinc roasting temperature field. First, a computational fluid dynamics (CFD) temperature field model was established through the mechanism of the roasting process. The influence of the feeding position on the temperature field was incorporated into the mechanism model, which provided the basis for the subsequent real-time control. Second, a convolutional Q-learning network (CQLN) is proposed to learn the mapping from state and action to Q value. CQLN can fully mine the spatial information of the temperature field. Then, the feed rate and feed location are adjusted in real-time to obtain the optimal roasting temperature field. Finally, extensive comparative experiments were conducted. Experimental results show that control performance of the proposed method is better than that of the comparison methods, with more uniform temperature distribution and smaller steady-state error.

Preservation of bone organic fraction is not predictive of the preservation of bone inorganic fraction when assessing stable isotope analysis sample quality control measures

Stable isotope analysis of carbon (C), nitrogen (N), hydrogen (H), and oxygen (O) of archaeological bone has become an increasingly common research method for interpreting human behavior in the past. However, diagenesis of skeletal material can invalidate stable isotope ratios, thereby compromising interpretations. We examine patterns of bone diagenesis using infrared spectroscopy of bone bioapatite samples in relation to indicators of organic preservation quality indicators. We assess crystallinity, an indicator of bioapatite preservation, using the infrared splitting factor (IR-SF) and carbonate content (carbonate to phosphate ratio, C/P) calculated from infrared spectra. We then test the assumption that if the organic fraction of bone is preserved, the mineral fraction will also be unaffected by postmortem chemical alteration. We analyzed 454 bone bioapatite and extracted bone organic sample pairs from modern, historic, and prehistoric humans. Consistent with previous studies, we observed a strong, statistically significant negative linear relationship between IR-SF and C/P (r = −0.855, p < 0.001). Modern bone bioapatite samples unaltered by diagenesis have low IR-SF and high C/P values. There was no significant association between the collagen yield or atomic C:N ratio and IR-SF or C/P values. The range of variation in IR-SF and C/P values for samples with organic yields between 0 and >20 percent spanned the range of modern bone bioapatite unaltered by diagenesis as well as bone bioapatite significantly affected by diagenesis. The lack of predictive patterning between bone inorganic and organic diagenesis suggests that the depositional context and site formation history play critical and independent roles in the organic and mineral fraction of bone. Thus, the preservation of the organic fraction of bone is not predictive of the preservation of the inorganic fraction (e.g., bioapatite).

A data-driven Vertical Stabilization system for the ITER tokamak based on Dynamic Mode Decomposition

In this article, we propose an online method to estimate an approximate linear model of a vertically unstable tokamak plasma to consequently adapt the parameters of a Vertical Stabilization controller. The identification procedure is based on the Dynamic Mode Decomposition with control approach, while the tuning procedure takes advantage of linear control theory to impose the desired crossing frequency and gain margins. The proposed technique is aimed at controlling ITER elongated plasmas using the VS3 stabilization coils, located inside the vessel. The effectiveness of the method is proven by means of numerical simulations carried out with the CREATE-NL+ free boundary evolutionary code, also considering the presence of realistic measurement noise levels.

A forward-curved blade centrifugal compressor for anode recirculation in proton exchange membrane fuel cells

Anode recirculation is crucial for the stable and efficient operation of automotive proton exchange membrane fuel cells (PEMFCs). The circulation is commonly driven by ejectors or positive displacement compressors, rather than centrifugal compressors, which have difficulty overcoming large pressure drops at low flow rates despite their promising attributes such as stable control and smooth operation. To address this gap, the present work proposes a novel design of a magnetically levitated centrifugal compressor featuring forward-curved blades. The comprehensive design process of this compressor is described, incorporating a novel design methodology, numerical simulations, and experimental validation. The compressor operates stably within the low-power range of typical automotive PEMFCs. At the design point, it achieves a static-to-static pressure ratio of 1.10 with an isentropic efficiency of 50 % and a system efficiency of 41 %. The test results demonstrate that the forward-curved blade centrifugal compressor is a viable option for anode recirculation in PEMFCs.

A Novel Control Architecture Based on Behavior Trees for an Omni-Directional Mobile Robot

Robotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace.

Vehicle Lateral Control Based on Dynamic Boundary of Phase Plane Based on Tire Characteristics

Lateral control is an essential safety control technology for autonomous vehicles, but the effectiveness of lateral control technology relies heavily on the precision of vehicle motion state judgements. In order to achieve accurate judgements of the vehicle motion state and to improve the control effectiveness of vehicle maneuverability and the stability controller, this paper starts with an analysis of phase plane stability. A simulation analysis is conducted to investigate the effect of the vehicle steering angle of the front wheels, the longitudinal velocity, and the tire–road adhesion coefficient on the boundary of the stability area. The stable area of the phase plane was partitioned using the proposed novel quadrilateral method, and we established a stability area regression model using machine learning methods. We analyzed the inherent connection between the lateral tire forces and the principles of vehicle maneuverability and stability control, indirectly combining the characteristics of tire forces with vehicle maneuverability and stability control. An allocation algorithm for maneuverability and stability control was designed. A co-simulation indicates that the vehicle stability controller not only accurately assesses the motion state of the vehicle but also demonstrates a considerably better performance in maneuverability and stability control compared to a controller using the traditional partitioning method of stable regions. The suggested allocation method enhances vehicle maneuverability and stability by enabling a seamless transition between the two and improving the effectiveness of stability control.

Event-triggered anti-disturbance control for aerial recovery drogue stabilization with guaranteed transient performance constraints

Aiming at the drogue docking control problem in aerial recovery, this paper proposes a performance event-triggered control algorithm based on disturbance observer to stabilize the flexibly towed aerial recovery drogue subject to the unknown airflows, cable towing tensions, limited computation capacity, and actuating power resources with guaranteed transient performance. Firstly, the control-oriented 6 degrees of freedom (DOF) affine nonlinear dynamics of the flexible cable-towed drogue are formulated. Then, the event-triggered extended state observers (ETESO) are established for the trajectory and attitude subsystems by utilizing intermittently measured state, to accurately estimate the lumped disturbances caused by the unmeasurable cable tension and unknown airflow disturbance while reducing the computation cost from the sensor to the observer. Moreover, to constrain the trajectory tracking error within the guaranteed transient performance constraint with any small overshoot, an ETESO-based event-triggered control algorithm for drogue was established to ensure the specified transient performance; finally, the closed-loop stability is discussed using Lyapunov analysis. The simulation results confirmed that this method can not only constrain the drogue within the expected small error range but also effectively reduce computational costs and resource occupation, with the best control effect.

Adaptive bias control of optical IQ modulator with low LFM dither and strong fluctuation resistance.

An innovative approach has been proposed for adaptive bias control in optical IQ modulators. In contrast to traditional approaches that utilize sine dither, this method employs a linear frequency modulated (LFM) signal as the dither, associated with the fractional Fourier Transform (FrFT) to extract the bias point drift. The LFM signal, after undergoing FrFT, transforms into a compressed signal (CS) with energy concentration in the fractional domain. Utilizing this signal for bias point monitoring, the proposed method demonstrates robust bias control even in the presence of substantial interferences, as substantiated by comprehensive simulations and experimental investigations. Remarkably, in a 20-Gbaud 16QAM signal transmission, the proposed approach achieves stable control of the bias point for over 4 hours, even in the presence of voltage fluctuations, while effectively reducing the dither amplitude by half. Furthermore, it maintains a low bit error rate (BER) below 10-5 even under intentional external interference.

Intelligent control of district heating system based on RDPG

Given the continuous expansion of heating areas in recent years, the design of a precise and dependable district heating system (DHS) has become increasingly crucial. Traditional control decisions are made based on real-time environmental temperature feedback, often leading to uneven heating on the user side and affecting residents' comfort. This paper proposes an intelligent control strategy based on the deep reinforcement learning recurrent deterministic policy gradient (RDPG) algorithm for DHSs. To explore the control performance of the RDPG algorithm on DHS, we have meticulously modeled the pivotal components of the DHSs, namely plate heat exchangers, secondary heating pipe networks, and heat users. Moreover, taking into account the periodic factors in heating regulation, the traditional recurrent neural network (RNN) in the recurrent deterministic policy gradient (RDPG) algorithm has been replaced with the long short-term memory (LSTM) network. The proposed algorithm was trained using actual data from a heat exchange station in Tianjin and compared with reinforcement learning algorithms such as TD3, DPPO, DDPG, and A3C in terms of training rewards, effectiveness, and training stability. The results of the models are evaluated and visualized. Experimental results show that the proposed control method based on the RDPG algorithm, compared to other control schemes, can achieve the highest training reward and the most stable control performance, with an indoor temperature fluctuation range of only 0.1 °C.

Research on Stability Control Algorithm of Distributed Drive Bus under High-Speed Conditions

Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively.

Long-Term Follow-Up of Patients With Elevated Aldosterone-to-Renin Ratio but Negative Confirmatory Test: The Progression of Primary Aldosteronism Phenotypes.

About 10% of patients with arterial hypertension have a positive screening test for primary aldosteronism (PA) and 50% to 70% of them have a negative confirmatory test: the appropriate follow-up of these patients is currently unknown. We investigated the incidence of PA in patients with previous negative confirmatory testing, after at least a 2-year follow-up. One hundred eighty-four patients with a previously elevated aldosterone-to-renin ratio followed by a negative confirmatory test were recruited in 2 hypertension centers (Torino and Munich). We repeated the screening test for PA and, if positive, the confirmatory test (seated saline infusion test or captopril challenge test). Primary end point of the study was the incidence of newly diagnosed overt PA, as defined by a positive confirmatory test. After a mean follow-up of 5 years, 20% of patients developed overt PA. When subtype diagnosis was offered systematically, one-third of patients displayed unilateral PA. Patients who developed PA showed worsening of blood pressure control and a higher rate of cardiac organ damage, despite similar implementation of antihypertensive therapy, compared with patients without PA. A mild progression of autonomous aldosterone secretion was evident even in patients without confirmed PA but with relatively stable control of blood pressure levels over time. About one-fifth of patients with a negative confirmatory test develop overt PA over time. A clinical follow-up of patients with a negative confirmatory test is advisable, along with the repetition of PA investigation, primarily in patients with worsening of blood pressure control.

A novel high-dynamic actuator based in-situ micro-forging process for wire arc additive manufacturing of aluminum alloy

As a method of work hardening, the technology of in-situ forging was introduced to solve the problem of poor mechanical properties in the fabrication of large-structural aluminum alloys components using wire arc additive manufacturing (WAAM) technology. Unfortunately, at present, the in-situ forging devices reported could not provide the ability to flexibly adjust output forces over a wide range of frequencies and change the output mode of forces. In this work, a novel method of high-dynamic actuator based in-situ micro-forging process for WAAM was proposed. The system is of compact design and has the characteristics of high dynamic response. The terminal hammering head could automatically fits the surface of the deposited layer successfully, enabling the stable control of the real-time hammering force, meaning that it offers a solution for processing deposited layers with complex paths. In addition, the terminal hammering head could be sufficiently close to the molten pool to enable the cumulative rapid micro-deformation of the as-solidified metal. This new method significantly promotes the reduction of shrinking holes and the closure of spherical pores of the components. The microhardness and the compressive yield strength of the components increased by 12% and 13% respectively. A gradient microstructure was obtained due to the transfer of strain. The mechanism of hybrid dynamic recrystallisation induced by cumulative rapid micro-deformation is investigated. These promising results promote the possibility of applying in-situ micro-forging technology in the field of flexible and intelligent manufacturing in aerospace.

Exosomal circSCMH1/miR-874 ratio in serum to predict carotid and coronary plaque stability.

To investigate the correlation between lg (circSCMH1/miR-874) and acute coronary syndrome (ACS), acute myocardial infarction (AMI), and carotid plaque stability. 701 patients were divided into stable coronary artery disease (SCAD), ACS, and control groups. Furthermore, 225 patients who underwent carotid ultrasound were selected from the above 701 patients and were divided into low-risk plaque, medium-to-high risk plaque, and control (without carotid plaques) groups. We collected their baseline characteristics and measured the contents of exosomal circSCMH1 and miR-874 in peripheral blood. Then lg(circSCMH1/miR-874) was calculated and statistical analysis was performed. The lg (circSCMH1/miR-874) values of ACS, SCAD, and the control group decreased successively (P < 0.05). Compared with the low-risk plaque and control groups, the lg (circSCMH1/miR-874) value of medium-high risk plaque group decreased (P < 0.05). Multivariate logistic regression analysis showed that with the decrease of lg (circSCMH1/miR-874), the risk of ACS, AMI, and medium-high risk plaques increased. ROC curve analysis demonstrated that lg (circSCMH1/miR-874) has a higher diagnostic value for ACS, AMI and medium-high risk plaques than previously used predictive ratios. Lg (circSCMH1/miR-874) is closely associated with coronary and carotid plaque stability.

How Can Plants Help Restore Degraded Tropical Soils?

In the tropics, anthropogenic activities can lead to water and wind erosion, a loss of biodiversity, and a reduction in sequestered carbon, fertility, and organic matter content in the soils concerned, potentially resulting in their degradation. This study therefore aims to identify the mechanisms used by plant species to restore degraded tropical soils and plant species characteristics that are best suited to achieve this through a critical scoping review of the peer-reviewed literature. Soil restoration leads to the re-establishment of ecosystem services and an increase in soil production potential, the regeneration of biodiversity, the stopping of organic matter losses, and the creation of favorable conditions for carbon sequestration and nitrogen fixation. The choice of appropriate plant species depends on the restoration objectives to be achieved. Five key mechanisms by which plant species contribute to restore degraded tropical soils include: (1) nitrogen fixation, (2) carbon sequestration, (3) organic matter addition, (4) structure stabilization, and (5) erosion control. The main characteristics of plant species and vegetation involved in these mechanisms are (a) the capacity to form symbiotic associations with N-fixing bacteria and mycorrhizae, (b) the production of abundant root biomass releasing litter and exudates, (c) roots having a high length density, branching intensity, and depth distribution, (d) the production of an abundant and easily decomposed above ground litter, (e) the production of a vast canopy, and (f) the presence of different vegetation strata. Targeting these characteristics will contribute to acting on several mechanisms simultaneously, which will increase the chance of success in tropical soil restoration.

Bipartite containment of heterogeneous multi‐agent systems under denial‐of‐service attacks: A historical information‐based control scheme

AbstractA distributed control scheme based on historical information is designed to solve the problem of stable control of multi‐agent systems under denial of service (DoS) attacks in this article. It achieves the control objective of bipartite output containment control, that is, the output states of the followers smoothly enter the target area. The control scheme updates the states of followers through historical information in the control protocol when agents are subjected to DoS attacks. A distributed state observer with a storage module is designed to efficiently estimate the state of followers and store the observed information as history information. The historical information of control protocol calls is not necessarily the real state information in the existence of DoS attacks. Consequently, a closed‐loop feedback state compensator is designed. Then, the state compensator is converted from the time domain to the frequency domain for stability analysis using the Nyquist criterion. It is obtained that an upper bound on the amount of historical information can achieve the bipartite output trajectories containment of the controlled system. The output trajectories of the followers converge into two dynamic convex hulls, one of which is surrounded by multiple leaders, and the other is a convex hull with opposite signs of the leaders. Finally, a numerical simulation is used to verify the proposed control scheme, and the operability of the scheme is further demonstrated in a physical experiment.

Stabilization and synchronization control of quaternion-valued fuzzy memristive neural networks: Nonlinear scalarization approach

In this paper, we present new conditions ensuring existence, uniqueness, and stabilization of the equilibrium point (EP) for a large class of quaternion-valued memristive neural networks. The results are applicable to both complex-valued memristive neural networks and quaternion-valued system with uncertain terms. Subsequently, by employing suitable controller, the synchronization control conclusion is also considered. It is worth mentioning that, the nonlinear scalarization approach is employed to ensure the closed convex hull consisted by the quaternion is meaningful, which preserves the integrity of the quaternion system and makes the conclusion more reasonable. Finally, this paper provides two examples, so that the superiority of the main results can be illustrated.

Local stabilization control for a class of polynomial parameter-varying systems based on nonlinear time-varying observer

Local stabilization control for a class of polynomial parameter-varying systems based on nonlinear time-varying observer