Synchronization Problem Research Articles

Model-Free Sliding Mode Control for a Nonlinear Teleoperation System with Actuator Dynamics

Teleoperation robotic systems control, which enables humans to perform activities in remote situations, has become an extremely challenging field in recent decades. In this paper, a Model Free Proportional-Derivative Sliding Mode Controller (MFPDSMC) is devoted to the synchronization problem of teleoperation systems subject to actuator dynamics, time-varying delay, model uncertainty, and input interaction forces. For the first time, the teleoperation model used in this study combines actuator dynamics and manipulator models into a single equation, which improves model accuracy and brings it closer to the actual system than in prior studies. Further, the proposed control approach, called Free, involves the simple measurement of inputs and outputs to enhance the system's performance without relying on any knowledge from the mathematical model. In addition, our strategy includes a Sliding Mode term with the MFPD term to increase system stability and attain excellent performance against external disturbances. Finally, using the Lyapunov function under specified conditions, asymptotic stability is established, and simulation results are compared and provided to demonstrate the efficacy of the proposed strategy.

Model-Free Sliding Mode Control for a Nonlinear Teleoperation System with Actuator Dynamics

Teleoperation robotic systems control, which enables humans to perform activities in remote situations, has become an extremely challenging field in recent decades. In this paper, a Model Free Proportional-Derivative Sliding Mode Controller (MFPDSMC) is devoted to the synchronization problem of teleoperation systems subject to actuator dynamics, time-varying delay, model uncertainty, and input interaction forces. For the first time, the teleoperation model used in this study combines actuator dynamics and manipulator models into a single equation, which improves model accuracy and brings it closer to the actual system than in prior studies. Further, the proposed control approach, called Free, involves the simple measurement of inputs and outputs to enhance the system's performance without relying on any knowledge from the mathematical model. In addition, our strategy includes a Sliding Mode term with the MFPD term to increase system stability and attain excellent performance against external disturbances. Finally, using the Lyapunov function under specified conditions, asymptotic stability is established, and simulation results are compared and provided to demonstrate the efficacy of the proposed strategy.

Successive lag synchronization of heterogeneous distributed-order coupled neural networks with unbounded delayed coupling

The problem of successive lag synchronization (SLS) for heterogeneous distributed-order coupled neural networks (HDOCNNs) with unbounded delayed coupling is investigated in this paper. Firstly, a model for HDOCNNs under the framework of distributed order Caputo derivative is proposed which is the generalization of integer order and fractional order cases. Secondly, a new Razumikhin-type stability theorem for distributed order systems is proposed. On this basis, the well-known Halanay type inequality is generalized to analyze the convergence of solutions for a class of distributed order dynamical systems. Thirdly, the SLS criteria for HDOCNNs with delayed coupling by designing a novel adaptive controller and a valid feedback controller are presented herein, respectively. Finally, a numerical example is presented to illustrate the reliability of the proposed scheme.

Cooperative Differential Game-Based Distributed Optimal Synchronization Control of Heterogeneous Nonlinear Multiagent Systems.

This article presents an online off-policy policy iteration (PI) algorithm using reinforcement learning (RL) to optimize the distributed synchronization problem for nonlinear multiagent systems (MASs). First, considering that not every follower can directly obtain the leader's information, a novel adaptive model-free observer based on neural networks (NNs) is designed. Moreover the feasibility of the observer is strictly proved. Subsequently, combined with the observer and follower dynamics, an augmented system and a distributed cooperative performance index with discount factors are established. On this basis, the optimal distributed cooperative synchronization problem changes into solving the numerical solution of the Hamilton-Jacobian-Bellman (HJB) equation. Finally, an online off-policy algorithm is proposed, which can be used to optimize the distributed synchronization problem of the MASs in real time based on measured data. In order to prove the stability and convergence of the online off-policy algorithm more conveniently, an offline on-policy algorithm whose stability and convergence are proved is given before the online off-policy algorithm is proposed. We give a novel mathematical analysis method for establishing the stability of the algorithm. The effectiveness of the theory is verified by simulation results.

Hybrid-MVS: Robust Multi-View Reconstruction With Hybrid Optimization of Visual and Depth Cues

Consumer-level RGB-D cameras have been widely used for dense 3D reconstruction of scenes. Especially for textureless or non-lambertian surfaces, consumer RGB-D cameras can ensure completeness of the reconstructed models at a low cost. However, the reconstruction quality relies heavily on the accuracy of the depth sensors. Digital cameras are also used popularly for capturing high-resolution pictures to achieve high-quality dense reconstruction of the scenes, but cannot handle textureless or non-lambertian regions well due to the visual ambiguity problem. To ensure both completeness and accuracy of the reconstructed 3D models, we propose a hybrid multi-view reconstruction pipeline named Hybrid-MVS, which combines the high-resolution images taken by a digital camera and the low-resolution RGB-D frames captured by a consumer RGB-D camera for robust reconstruction of complicated scenes with challenging textureless and non-lambertian surfaces. Unlike most existing multi-sensor systems which require explicit hardware calibration and synchronization of various sensors, the calibration and synchronization problems between the digital camera and RGB-D camera are implicitly solved for compositing reliable depth prior of the digital images in our pipeline. Especially, we propose a hybrid MVS framework for robust PatchMatch stereo and Delaunay meshing, which tightly couples both visual cues given by the digital images and depth cues from the RGB-D frames to maximize the complementary advantages. The experiments with quantitative and qualitative evaluations demonstrate the effectiveness of the proposed Hybrid-MVS framework, which can successfully achieve high-quality 3D reconstruction of complicated natural scenes with robustness to weakly textured and non-lambertian areas.

Small-Signal Synchronization Stability of Grid-Forming Converters With Regulated DC-Link Dynamics

The dc-link voltage dynamics can be directly used to synchronize grid-forming (GFM) converters with ac grids. However, such control scheme is prone to unstable low-frequency oscillations (LFO), owing to the constant-power dynamics at the dc link. This paper analyzes first the small-signal stability of dc-link voltage-synchronized GFM converters, and proposes a control method for enhancing the system stability under different operating scenarios. In the approach, a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis voltage-feedforward control is introduced in parallel with the dc-link voltage control for the grid-synchronization purpose. The LFO problem with the conventional dc-link voltage-synchronization control is mitigated. Compared to conventional cascaded/paralleled dc-link voltage- and active power-based synchronization, the method mitigates the synchronous oscillation problem. Experimental tests are performed for the GFM converter operating in both rectifier and inverter modes and with different grid strengths. The results corroborate theoretical analyses and validate the effectiveness of the approach.

Resilient Consensus via Weight Learning and Its Application in Fault-Tolerant Clock Synchronization

This paper addresses the distributed consensus problem in the presence of faulty nodes. A novel weight learning algorithm is introduced such that neither the network connectivity nor a sequence of history records is required to achieve resilient consensus. The critical idea is to dynamically update the interaction weights among neighbors learnt from their credibility measurement. Basically, we define a reward function that is inversely proportional to the state difference to its neighbor, and then adjust the credibility based on the reward derived at the present step and the previous credibility. In such a way, the interaction weights are updated at every step, which integrates the historic information and degrades the influences from faulty nodes. Four classes of faulty nodes are considered, and both fixed and stochastic topologies are involved in this paper. Furthermore, we apply this novel approach in clock synchronization problem. By updating the logical clock skew and offset via the corresponding weight learning algorithms, respectively, the logical clock synchronization is eventually achieved regardless of faulty nodes. Simulations are provided to illustrate the effectiveness of the strategy.

Output Synchronization of Heterogeneous Multiagent Systems With Resilience to Link and Actuator Attacks: A Fully Distributed Event-Triggered Mechanism

In this paper, we propose a distributed resilient control method to solve an output synchronization problem for linear heterogeneous multi-agent systems (MASs) in the presence of both link and actuator attacks. A fully distributed event-trigger-based observer is proposed to estimate the state of the leader, where global information is not required and the leader's system matrices are identified in finite time. An intermittent event-triggered mechanism is also designed to avoid continuous monitor triggered conditions. For actuator attacks, a compensator, based on a distributed normal state predictor, is developed to recover paralyzed states. Theoretical analysis shows that an MAS steered by our proposed fully distributed adaptive resilient scheme achieves output synchronization, and Zeno-behaviors are excluded. Finally, a numerical example is provided to verify the effectiveness of our proposed scheme.

Synchronization of stochastic switching complex networks with a target of nonzero inputs

SummaryIn this article, we study the mean square synchronization problems for complex networks with a target of nonzero inputs under stochastic switching topology that is driven by an ergodic continuous‐time Markov process. First, we design an adaptive continuous controller based on relative full states that is consist of a synchronization term and an uncertainty elimination term, where the latter term can completely eliminate the effects of target's nonzero inputs and is continuous by adding an exponential decay function with positive initial values into the denominator. By developing a stochastic Lyapunov function, we show that zero error synchronization in the mean square sense can be achieved if the union of switching graphs contains a directed spanning tree with the target being the root. Second, we design an adaptive continuous controller based on relative outputs. Finally, we give two simulation examples to validate the theoretical results.

Flexible Robust Control Strategy for Synchronization of Uncertain Non-Linear Systems with Control Input Non-Linearity

A robust global fuzzy sliding mode controller is designed in this paper for the synchronization of non-linear systems with control input non-linearities (CIN) and uncertainties. A consistent global fuzzy sliding mode control (GFSMC) law is developed, which guarantees the suppression of the reaching phase and the presence of the sliding phase from the initial time. Chattering phenomenon, which is characteristic of customary sliding mode control (SMC), avoided by the on-line fuzzy regulation of the sliding surface in the controller, when the system is subject to disturbances and CIN. Finite-time boundedness (FTB) properties are designed with adequate conditions, which are entrenched in terms of linear matrix inequalities (LMIs) with the help of cost and Lyapunov functions. Numerical simulations for the synchronization problem of the chaotic modified Colpitt’s system and Duffing system clearly show the good performance of the proposed control scheme. The present work provides a regular procedure to design GFSMC for a class of non-linear systems with CIN.

Estimator-based event-triggered output synchronization for heterogeneous multi-agent systems under denial-of-service attacks and actuator faults

This paper studies the output synchronization problem with an event-triggered communication scheme for a class of heterogeneous multi-agent systems under denial-of-service (DoS) attacks and actuator faults. DoS attacks may render the followers incapable of acquiring the leader's states and actuator faults may cause the actuators to not perform the control operation well. Comparing with the previous studies adopting the continuous communication mechanism, a novel switching estimator with an event-triggered communication strategy is designed to estimate the leader's states for each follower. By using the Lyapunov stability theory and the average dwell time method, sufficient conditions for the upper bound of the frequency of DoS attacks are derived. The estimation error system is proved to be exponentially stable. Besides, in order to compensate for actuator faults, a distributed adaptive fault-tolerant controller is proposed. The conditions for the stability of the output regulation error when the systems suffer from DoS attacks and actuator faults are given. A simulation example is proposed to prove the effectiveness of the main results.

Back-stepping projective synchronization of fractional-order unified systems based on the lower triangular structure

The synchronization of fractional-order chaotic systems (FOCSs) plays an important role in modern control theory, the projective synchronization (PS) as a class of synchronization problems, also has huge applications and has attracted much attention. It is, however, shown in the obtained literature that the results on the PS of FOCSs either loss the rigorous theoretical demonstration or verify from the viewpoint of numerical simulations. How to derive a necessary and sufficient condition to guarantee the PS of complex FOCSs by a simple controller is still open. To this end, this article is concerned with the PS of fractional-order unified systems (FO-USs) that are important in FOCSs covering fractional-order Lorenz, Chen and Lü systems, where the controller is presented based on the lower triangular structure by use of the back-stepping technique. The necessary and sufficient criterion for the PS of FO-USs is proposed by solving an algebraic equation, and the controller for the PS of FO-USs is derived based on the lower triangular structure combined with back-stepping approach. Finally, the simulation results are reported to verify the correctness and efficiency of the obtained results.

Time-Coordinated Path Following for Multiple Agile Fixed-Wing UAVs with End-Roll Expectations

This paper presents a control strategy for multiple unmanned aerial vehicle systems (multi-UAVs) time-coordinated path following with desired endpoint roll attitudes. It utilizes the strong maneuvering capabilities of agile fixed-wing UAVs and incorporates an end-roll expectation. The strategy consists of four steps: time-coordinated control, position control, roll angle planning and attitude control. The position and attitude controllers exhibit Lyapunov exponential stability. The time-coordinated controller addresses the synchronization problem by adjusting the speed based on the coordinated state to achieve progress adjustment. The position controller operates based on the cross-track error and altitude error in the Gravity-Referenced Moving frame. By employing an optimization approach and designing a penalty function, the roll angle sequence is computed. The attitude inner-loop control operates in the [Formula: see text] space and allows for control of large deviations. High-fidelity simulation validates the effectiveness of the proposed method, with normalized coordination error and following error controlled within 2% and 1.2[Formula: see text]m.

Adaptive finite-time synchronisation of variable-order fractional chaotic systems for secure communication

The variable-order fractional (VOF) chaotic systems offer a promising solution for applications in secure communication due to their unique properties. This paper addresses the synchronisation problem in secure communication for these systems, which have uncertainties and external disturbances with unknown bounds. According to the variable-order fractional type Mittag-Leffler stability theorem, a fractional-order derivative is applied to a sliding surface, and suitable adaptive laws are devised to address uncertainties and disturbances. A variable-order fractional control strategy and a new criterion are developed to ensure the synchronisation error systems achieve asymptotic stability in finite time, for which the upper limit can be obtained. Simulation outcomes demonstrate the efficacy of the proposed synchronisation strategy in secure communication scenarios.

Event‐triggered pinning control for passivity and synchronization of directly coupled delayed reaction‐diffusion neural networks

SummaryThis article solves event‐triggered pinning control for passivity and synchronization problems of directly coupled delayed reaction‐diffusion neural networks (CDRDNNs). Outer coupling matrix of the presented model can be direct, while previous literature referred to reaction‐diffusion neural networks usually assumed this matrix undirected simply. First, through exploiting appropriate event‐triggered pinning protocol, passivity and synchronization criteria are acquired for directly CDRDNNs on account of Lyapunov functional and inequality techniques. After that, we also deal with event‐triggered pinning passivity and synchronization for undirected CDRDNNs. In the end, the effectiveness of these obtained results is verified by given examples.

Exponential synchronization of delayed coupled neural networks with delay-compensatory impulsive control

This paper studies the exponential synchronization problem for a class of delayed coupled neural networks with delay-compensatory impulsive control. A Razumikhin-type inequality involving some destabilizing delayed impulse gains and a new idea of delay-compensatory that shows two critical roles for system stability are presented, respectively. Based on the constructed inequality and the presented delay-compensatory idea, sufficient stability and synchronization criteria for globally exponential synchronization (GES) of coupled neural networks (CNNs) are presented. Compared with existing results, the uniqueness of the presented results lies in that impulse delays can be fetched and integrated to compensate for instantaneous unstable impulse dynamics caused by destabilizing gains. Moreover, constraints between system delay and impulsive delay are relaxed, and the interval of impulses no longer constrains the system delay. Comparisons and a practical application are given to demonstrate the superior performance of the presented novel control methods

Quantized fault-tolerant pinning control for finite-time H∞ synchronization of T-S fuzzy discrete Markovian-jump complex networks subject to heterogeneous delays

This paper investigates the finite-time pinning synchronization problem for a class of T-S fuzzy discrete Markovian-jump complex networks (TSFDMCNs) influenced by heterogeneous delays. The evolution of system parameters follows the Markov jump process according to a transition probability matrix with partly unknown elements. Based on the system state output, quantized fault-tolerant pinning controller (QFTPC) is designed to overcome communication limitations and varying actuator fault. Besides, the asynchronous signal generated by the hidden Markov model is employed in controller to make full use of received information. A novel mode-dependent Lyapunov- Krasovskii functional (LKF) is established to guarantee the error system mean-square finite-time bounded with the prescribed performance. In order to reduce conservatism of derived results, an improved Wirtinger-based inequality technique is applied in considering both lower and upper bounds of different delay. Finally, simulation examples illustrate the effectiveness and meliority of the proposed theoretical methods.

Improving Resources in Internet of Vehicles Transportation Systems Using Markov Transition and TDMA Protocol

In today’s world, interconnected Vehicular ad-hoc networks (VANET) and intelligent transportation systems have become more popular. Although IoV can bring many benefits for the smart cities and provide comforts for the passengers, however, the increasing needs for keeping the QoS and QoE at an acceptable level in time sensitive applications seems crucial and needs to be investigated deeply. Also, allocating the right number of resources to avoid congestions and fill the deficiencies in a distributed manner is a challenging issue. So, with the increase in users, attention must be given to Quality of Service (QoS) and resource allocation. As the vehicle network provides information to provide safety, comfort, and entertainment to drivers and passengers, they are one of the most compelling research topics in intelligent transportation systems. TDMA protocol is used in this study to increase the efficiency of the network and the quality of service it provides. To solve the synchronization problem, the Markov method predicts the size of slots and frames. The scenario field is used in the Markov application section to better predict TDMA gaps on solving the synchronization problem. Accordingly, the higher the quality of service, the lower the latency of the network, and the better the allocation of resources. Optimizing allocation and quality of service is further motivated by reducing collision between packets. In terms of its implementation, this method is divided into two components, the first being the database proposal for constructing the Markov matrix and the second being the simulation on VanetMobisim and implementation of the network in NS2. The proposed method performed better in different scenarios in terms of computational complexity, PDF, latency, and overhead, as shown in the results section.

Synchronous Networks Over Finite Fields

This paper investigates the synchronization problem of networks over finite fields. Firstly, based on the finite-field synchronizable (FFS) property of matrices, a necessary and sufficient condition is derived for finite-field synchronous networks. Then, the inverse recursion subspaces of networks over finite fields are studied. It is revealed that the synchronization of finite-field networks can be determined by a fraction of states. Finally, as an application, the obtained results are generalized to a class of Boolean networks.

Design and Simulation of Robot Gripper and Conveyor System for Workstations

Abstract: Intelligent manufacturing is going to boom in the upcoming years. The characteristic features of Industry 4.0 are fully automated production facilities where all processes are controlled in real-time and take into account the changing external conditions. The core of the Industry 4.0 is made up of digitalization and robotics, in particular, the use of collaborative robots and MES. MES (Manufacturing Execution System) is a specialized system designed to solve the problems of synchronization, coordination, analysis, and optimization of production. It involves the use of conveyor belts for rapid transportation of products. Industries where conveyor belt systems are excelling include automotive, computer, good, packaging, print finishing, bottling and canning, chemical, pharmaceutical, aerospace and food processing The safety conditions in fundamental industrial jobs are dangerous and harmful combined with ineffective manual work as a result of rising need for mass manufacturing. In industries, automation is the use of technology to jobs that were previously handled by humans. It is a potent instrument that can aid companies in enhancing quality, production, and efficiency. A typical type of mechanical handling equipment that transports things from one place to another is a conveyor system. These systems consist of conveyor belts that are designed to work seamlessly with robotic arms and other automated equipment. Increased automation and mass production rate reduces the lead time and increases the profit of a firm. The deployed robotic arms are immensely capable of handling various tasks with increased flexibility. Using a robotic arm with an end effector as a gripper to hold/pick and place the material from the conveyor belt improves the product flow process. The project comes with the NodeMCU firmware and an integrated Wi-Fi chip, the ESP8266 12E. To connect with the controller via a mobile phone, a web page would be constructed using HTML and coded using the Arduino IDE's C language. At either end of the conveyor belt, 2 robotic arms with 2 degrees of freedom (D.O.F.) would be placed. Using one arm to place the product on the belt and a second to pick it up at the other end. Also calculating the analytical data of the system that is involved in reallife industrial processes along with the simulation of entire system for the UR10 industrial robot, using the RoboDK simulation software. Through the usage of this system, productivity is boosted with improved safety of the working environment, become more effective, be more flexible, and have higher levels of job satisfaction