Communication Time Delay Research Articles

Nonlinear model predictive dynamic positioning of a remotely operated vehicle with wave disturbance preview

Exploiting preview information of disturbances within robot control is an effective method of handling state perturbations. For underwater vehicles operating in wave-dominated environments, disturbances significantly influence vehicle response and pose a threat to operational safety. In consideration of this, a complete end-to-end control architecture is developed in this work for disturbance rejection during station keeping tasks under wave perturbations, encompassing a nonlinear model predictive controller (NMPC) combined with a deterministic sea wave predictor (DSWP). The wave predictor exploits a continuous measurement of the wave elevation at a location upstream of the vehicle to form a forecast of the temporal evolution of the wave elevation at the vehicle location. The predicted wave parameters are then used to estimate the impending wave-induced hydrodynamic loading, enabling explicit consideration of accurate short-term disturbance forecasts within the controller, ensuring this preview is incorporated in the optimised control sequence. Experimental testing confirms the validity of the wave predictor, producing RMSE as low as 0.017 m. The proposed strategy is then simulated under various wave conditions, optimising control actions inclusive of the preview information. The NMPC outperforms a similar disturbance mitigating feed-forward controller, with average improvements of up to 52% and is found to perform best even with noisy, lower accuracy wave predictions, as well as with communication time delays, providing a high degree of robustness. This demonstrates the potential of the proposed control framework to effectively tackle disturbance mitigation of underwater vehicles subject to large magnitude wave disturbances, expanding the operational envelop of autonomous systems towards forbidding ocean environments.

Optimisation of synchronisation control parameters for enhanced bilateral teleoperation system

Abstract Bilateral teleoperation systems encounter challenges in achieving synchronisation between master and slave robots due to communication time delays. This paper addresses the instability caused by these delays and proposes a solution through advanced control algorithms. Nonlinear optimisation algorithms might only sometimes deliver solutions in the allotted time, particularly when handling complicated, high-dimensional issues or when optimisation iterations are extensive. The study first develops a comprehensive mathematical model encompassing the dynamics and communication intricacies of both master and slave sides in teleoperation. By recognising the limitations of existing proportional-derivative controllers in compensating for communication errors, a sequential quadratic programming-proportional-integral-derivative (SQP-PID) controller is introduced. This controller accumulates and rectifies synchronisation delay errors, ensuring precise control without steady-state deviations. The proposed SQP-PID controller stands out for its ability to handle steady-state errors effectively, offering swift response and maintaining stability. Leveraging the SQP optimisation algorithm, it intelligently tunes the parameters, minimising synchronisation errors. The approach capitalises on the simplicity, performance, and robustness of the SQP-PID controller, providing a promising avenue for enhancing bilateral teleoperation systems’ accuracy and stability, maintaining initial discrepancy with a best fitness value of 0.98 % in varied operating conditions.

Active disturbance rejection control for spacecraft relative motion in libration point orbits subject to actuator saturation and time-delays

This paper proposes a novel active disturbance rejection control (ADRC) scheme to achieve the spacecraft relative pose synchronization in the libration orbits under the constrations of the actuator saturation and time-delays. The relative kinematics and dynamics between two spacecraft are modeled using dual quaternions to avoid singularity. A set of dimensionless variables is introduced to improve computational accuracy. An extended state observer, consisting of a time-delay predictor and an anti-windup compensator, is designed to address actuator saturation and communication time delays. A composite controller is then proposed, based on the designed observer, to mitigate the impact of total disturbances. Finally, two illustrative numerical simulations, including a spacecraft close rendezvous and docking scenario and a formation flying scenario, are provided to verify the effectiveness of the proposed ADRC scheme.

The time lag in local field potential signals for the development of its Bayesian belief network

PurposeThe objective is to suggest time as an important variable to consider in the network model, specifically when discussing causality.MethodsThere is a consideration of the context of functional connectivity because of the time importance of observing the feature inside the neuroscience context. A network model was constructed using the Bayesian network method, utilizing a dataset consisting of three rats’ local field potentials. The model took into consideration the time delay of communication among brain areas, as recorded in this study. In pursuit of this objective, the delayed mutual information method was employed to ascertain the temporal delay between local field potentials and K2 score for the purpose of model comparison.ResultsBayesian network depicted the probabilistic relationship among rat’s brain areas. Delayed mutual information captured the lag among brain areas, and after its appliance on the Bayesian network model, posed better results.ConclusionThe primary novelty of this research lies in its integration of minor delays within the Bayesian network approach, accomplished through the utilization of the delayed mutual information technique prior to its implementation. The suggested methodology incorporates an essential feature that supports the analysis of functional connectivity among brain areas, thereby providing support for the dynamics of neurophysiology.

Finite-time formation trajectory tracking control for unmanned underwater vehicles with time delays and Markov-switch topology

ABSTRACT The formation trajectory tracking control strategy of unmanned underwater vehicles is proposed for communication time delay and communication topology random switching. The methods ensure that formation systems are finite-time bounded under discrete time. Firstly, based on the consistency theory and the exact feedback linearised dynamics model of unmanned underwater vehicle, a control strategy is proposed for discrete formation system with communication time delay. Secondly, a cooperative control method is designed for communication problems of Markovian switching topology and time delay. Then, definition of finite-time bounded and linear matrix inequality technique are applied to sufficient conditions of system stability for the above problem. Finally, the formation motion of discrete unmanned underwater vehicle system in three-dimensional space is simulated, fully demonstrating the feasibility of the method.

Load frequency control performance enhancement of an electric vehicle integrated time-delay multi-microgrid system

ABSTRACT Frequency control in a microgrid (μG) is problematic due to low inertia of distributed generators (DGs) and uncertainty of the renewable energy source-dependent DGs. Consequently, deploying distributed storage units (DSUs) in a μG is crucial for quickly arresting frequency deviations. The electric vehicle (EV) technology, as DSU, is being preferred over conventional energy storage due to its lower cost and slower degradation rate, facilitating demand side response in a μG. The adoption of the EV technology necessitates an open communication infrastructure in the μG, with a pre-existing communication time delay (CTD). This article explores the impact of EV integration on load frequency control (LFC) performance of a multi-microgrid (MμG) system and determines an optimal CTD value simultaneously. A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the MμG system. Simulation results reveal significant improvements in dynamic responses when integrating EVs in the MμG, with a 97.33% increase in objective function value. The recommended controller also outperforms standard controllers in terms of how quickly frequency and tie-line power variations settle down to zero. Thus, the proposed controller meets the LFC requirements. Robustness of the proposed LFC scheme is tested against parametric variations in the MμG system.

Concept of operations for increasingly autonomous space operations

Concept of Operations (ConOps) documents provide a common view of future system functions to all stakeholders. This ConOps focuses on deep space missions, such as a mission to Mars. While Earth experts will be continuously monitoring operations during crewed deep-space missions, there will be communication delays and disruptions that will impede the rapid assistance required by the crew in time- and safety-critical situations. An argument will be made that the crew will require (some kind of) assistance to quickly understand the situation enough to safe the system. This document describes a notional vision of the operational processes, practices and capabilities needed by a deep space mission crew for them to autonomously respond to anticipated and unanticipated, time-critical anomalies. A descriptive model of a Crew Performance Support System (CPSS) is used to illustrate what will be required for a safe and successful manned mission to Mars. Scenarios will address crew, Earth-Support and technology roles/responsibilities, task prioritization, teaming strategies, complex procedure development and execution, assumptions, asynchronous collaboration under communication time delay and limited data exchange to illustrate potential operational needs and approaches. Scenarios are responsive to known human risks identified during and after long duration spaceflight and incorporate transition plans as space travel moves from ISS to Lunar to Mars operations specifically identifying test bed and research activity needs. The envisioned CPSS will alter the current operational paradigm of crew reliance on Earth experts to resolve anomalies. The intent of this ConOps is to advance the research and development of a CPSS.

Adaptive Iterative Learning Tracking Control for Nonlinear Teleoperators with Input Saturation

Addressing input saturation, external disturbances, and uncertain system parameters, this paper investigates the position tracking control problem for bilateral teleoperation systems with a time delay communication channel. Based on a composite energy function, we propose an adaptive iterative learning control (AILC) method to achieve the objective of position tracking under the alignment condition. This extends the existing research on the control of nonlinear teleoperation systems with time delay. The saturation constraint property of the Softsign function ensures that no state of the system exceeds its constraints. The controller learns to simultaneously deal with the uncertainty of system parameters online, reject external disturbances, and eliminate positional errors along the time and iteration axes. All signals in the system for any constant time delay are proved to be bounded. Ultimately, the performance of the proposed controller is further verified through numerical simulations.

Impact of Communication Time Delay in a 5G Network on Frequency Regulation Performance of a High Renewable Energy Penetrated Power System

Impact of Communication Time Delay in a 5G Network on Frequency Regulation Performance of a High Renewable Energy Penetrated Power System

Optimally tuned cascaded FOPI-FOPIDN with improved PSO for load frequency control in interconnected power systems with RES

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

Distributed Control for Nonlinear Time-Delay Multiagent Systems: Hybrid Saturation-Constraint Impulsive Approach.

This article mainly studies the problem of impulse consensus of multiagent systems under communication constraints and time delay. Considering the limited communication bandwidth of the agent, global and partial saturation constraints are considered. In addition, so as to further improve communication efficiency by reducing communication frequency, the novel control protocol combining event-triggered strategy and general impulse control protocol is proposed. Under this kind of novel control protocol, the communication frequency of multiagent systems can be reduced while avoiding "Zeno behavior." Through theoretical analysis, sufficient conditions for the systems to achieve consensus are obtained for the above two saturation constraint cases. In the end, the effectiveness of the novel protocols is proved by providing two different simulation instances.

Development of a novel model matching decentralized controller design algorithm and its experimental validation through load frequency controller implementation in restructured power system using TMS320F28379D controlCARD

A three-stage decentralized controller design algorithm is developed to achieve setpoint tracking and disturbance rejection in MIMO systems with communication time delay, and nonlinearities such as saturation and dead band. The first stage involves reference model formulation. The second stage comprises equating approximate generalized time moments/approximate generalized Markov parameters of closed-loop system model with reference model at certain expansion points in s-plane to obtain synthesis-like equation, concerning products of unknown controller numerator and denominator polynomials. This process yields simultaneous linear equations, whose solution provides the coefficients of the product polynomials. In the third stage, the controller parameters are extracted from the product polynomials using exact model matching. The proposed method is illustrated by designing load frequency controller in traditional and restructured power systems under scenarios like system parameter uncertainties, random load variation, and time-varying communication delays. Simulation studies reveal the efficacy of the proposed technique over existing techniques. Furthermore, the practical implementation feasibility of the decentralized controller designed for the restructured power system is validated using the TMS320F28379D controlCARD.

Time-delay-aware power coordinated control approach for series hybrid electric vehicles

Series hybrid electric vehicles (S-HEVs) have attracted extensive attention thanks to the simple structure and excellent efficiency, which power transfer rely on high-voltage microgrids consisting of engine-generator set, battery, motor, and other actuators. However, with possible communication time delays (CTDs), the interaction between the actuators and control unit in terms of state and control command is desynchronize, resulting in the unstable operation of S-HEVs, such as engine stalls and bus voltage jitter. This presents a great challenge to the power coordinated control approach (PCCA) design that controls different actuators. Motivated by the mentioned above, this paper presents a time-delay-aware PCCA to achieve the stable driving of S-HEVs. First, an integrated powertrain control-oriented model that incorporates communication is built. Second, an increment model predictive control method (MPC) is designed. And then by leveraging the Lyapunov-Razumikhin stability theorem, a stability condition is derived by defining a parameterization weight matrix and known upper bound of CTDs, reducing the complexity of parameter designing. Additionally, an adaptive mechanism is designed to extend application of the proposed approach in unknown CTDs condition. Finally, the hardware-in-the-loop experiment is performed, and the results demonstrate that the presented approach in the mean and root mean square of the engine speed error and DC-bus voltage error decrease 39.87%, 43.85%, 44.67%, and 79.94% than nominal MPC in one period CTDs condition, respectively. And for the larger CTDs condition, the proposed method also shows efficient robustness. These substantiate that the proposed control method effectively improves vehicle running stability when encountering CTDs.

Adaptive Active Disturbance Rejection Control for Vehicle Steer-by-Wire under Communication Time Delays

In this paper, an adaptive active disturbance rejection control is newly designed for precise angular steering position tracking of the uncertain and nonlinear SBW system with time delay communications. The proposed adaptive active disturbance rejection control comprises the following two elements: (1) An adaptive extended state observer and (2) an adaptive state error feedback controller. The adaptive extended state observer with adaptive gains is employed for estimating the unmeasured velocity, acceleration, and compound disturbance which consists of system parameter uncertainties, nonlinearities, exterior disturbances, and time delay in which the observer gains are dynamically adjusted based on the estimation error to enhance estimation performances. Based on the accurate estimations of the adaptive extended state observer, the proposed adaptive full state error feedback controller is equipped with variable gains driven by the tracking error to develop control precision. The integration of the advantages of the adaptive extended state observer and the adaptive full state error feedback controller can improve the dynamic transient and static steady-state effectiveness, respectively. To assess the superior performance of the proposed adaptive active disturbance rejection control, a comparative analysis is conducted between the proposed control scheme and the classical active disturbance rejection control in two different cases. It is worth noting that the active disturbance rejection control serves as a benchmark for evaluating the performance of the proposed control approach. The results from the comparison studies executing two simulated cases validate the superiority of the suggested control, in which estimation, tracking response rate, and steering angle precision are greatly improved by the scheme proposed in this article.

Super capacitor and SSSC-based coordinated strategy for performance improvement of diverse source interconnected power system

In this work, the dynamical behavior of the dual area thermal-hydro-wind (DATHW) model of the interconnected power system (IPS) is investigated. For analysis, the area-1 of the DATHW system is laid with a disturbance in step load (SLD) of 10%. The investigation is carried out on the DATHW system under the supervision of the fractional order proportional-integral-derivative-filter (FOPIDN) controller optimized with the water cycle algorithm (WCA). However, the dominance of FOPIDN in regulating the DATHW system performance deviations is validated by other regulators. To get the research near practicality, the DATHW system is deliberated with communication time delays (CTDs). The CTDs is the inherit nature of the communication peripherals that are employed in the IPS network for providing the data exchange among various devices. Further, the supplementary control approach of super capacitors (SC) and static synchronous series compensators (SSSC) is adopted with the DATHW system for performance improvement. The supplementary control is implemented by integrating the SC in the control areas and the SSSC with the tie-line. Finally, we conducted the sensitivity test to reveal the efficacy of the suggested controller mechanism in this work.

Optimal Tuning of PID Controllers for LFC in Renewable Energy Source Integrated Power Systems Using an Improved PSO

The constant rise in energy demand and concerns about climate change have led to increased penetration of renewable energy sources (RES). Maintaining active power balance between generation and demand in power systems with significant penetration of these highly variable and intermittent renewable sources requires an efficient load frequency control (LFC) strategy. One such strategy that has gained the attention of researchers is optimal tuning of PID controllers of LFC using metaheuristic method. This paper presents a PSO variant for optimal tuning of PID controllers for load frequency control of power system integrated with renewable energy resources. The proposed PID tuning technique is tested on a two-area power system commonly used in the literature. Seven scenarios have been used to validate the effectiveness of the proposed Load Frequency Control. For more realistic evaluation, governor dead band and communication time delays have been incorporated in the test system in one of the scenarios. Simulation results obtained when compared with those of three well-known PID-tuning metaheuristic algorithms produced shorter settling time and smaller frequency and tie line power deviations.

Soft Computing Algorithm-Based Intelligent Fuzzy Controller for Enhancing the Network Stability of IPS

The work furnished in this paper projects the application of fuzzy-aided tilt-integral-derivative (TID) with filter (TIDF) for regulating the dynamical behavior of the electrical interconnected power system (IPS) during uncertain conditions. The optimal design of the fuzzy TIDF is performed using the efficient soft computing technique of the water cycle algorithm (WCA). The suggested fuzzy TIDF controller performance is tested on the multi-area diverse source realistic (MADSR) IPS (MADSRIPS) subjected to control area 1 with step load disturbance (SLD) of 10%. Moreover, the analysis carried out on MADSRIPS is considered with the communication time delays (CTDs) for the investigation near to realistic environment. The efficacy of fuzzy-aided TIDF is contrasted with reported controllers available in literature, and the simulation analysis is acquired from the framework of MATLAB, which revealed the sovereignty of the suggested controller. Later, the MADSRIPS is operated with the integration of a HVDC line in conjunction with the tie-line to improve the performance.

Improved Communication-Free Coordinated Control of VSC-MTDC Integrated Offshore Wind Farms for Onshore System Frequency Support

To reduce the adverse influence of communication time delay, the DC voltage of offshore converters is usually employed as input signals of existing communication-free frequency support schemes of offshore wind farms (OWFs). However, the offshore DC voltage varies with the output power of OWFs, this distortion will deteriorate the frequency support performance. To address this issue, an improved communication-free coordinated control (ICFCC) scheme of VSC-MTDC integrated OWFs for frequency support is proposed. The ICFCC scheme involves the onshore frequency variation into the DC voltage deviation once frequency events occur, and an estimator is proposed to obtain the onshore DC voltage in offshore VSC stations to provide fast frequency support and reduce the distortion influence. Meanwhile, to obtain better support performance, the frequency support power is allocated reasonably by regulating droop coefficients adaptively, more power will be injected via the station closer to the disturbing bus. After frequency support, the offshore wind turbines will recover their rotor speed with asymptotic control to reduce second frequency drop. Case studies are carried out on the 4-terminal and 5-terminal test systems, respectively, while considering the parameter uncertainties and noise disturbance. Different control methods are compared to illustrate the effectiveness of the ICFCC scheme.

Sequential infiltration of two-photon polymerized 3D photonic crystals for mid-IR spectroscopic applications

Photonic crystals (PhCs) are spatially organized structures with lattice parameters equivalent to the operational wavelength of light. PhCs have been subject to extensive research efforts in the last two decades and are known for controlling light propagation with applications in sensing and time-delayed communication due to the slow-light phenomenon. Despite their exceptional properties, PhCs are difficult to fabricate using planar micromachining techniques due to their periodic structures. Techniques like two-photon stereolithography have been discussed for PhC fabrication in the literature, but the inherent disadvantage of poor refractive index (RI) contrast results in limited application. In this work, we present sequential infiltration synthesis performed on two-photon stereolithographically printed 3D PhCs for infiltration with zinc oxide to increase the RI of 3D PhCs. Finite element analysis was performed over a range of RI contrast values to study the change in photonic bandgap (PBG) with RI contrast. The transmission spectra were recorded on 3D PhCs before and after infiltration to demonstrate the change experimentally. An increase in the PBG width and absorbance is seen postinfiltration due to enhanced RI. This work presents the first, to our knowledge, sequentially infiltrated enhanced 3D PhC fabricated with two-photon stereolithography.

A Deep Time Delay Filter for Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) is a smart transportation solution to alleviate traffic congestion and enhance road safety. The performance of CACC systems can be remarkably affected by communication time delays, and traditional control methods often compromise control performance by adjusting control gains to maintain system stability. In this paper, we present a study on the stability of a CACC system in the presence of time delays and highlight the trade-off between control performance and tuning controller gains to address increasing delays. We propose a novel approach incorporating a neural network module called the deep time delay filter (DTDF) to overcome this limitation. The DTDF leverages the assumption that time delays primarily originate from the communication layer of the CACC network, which can be subject to adversarial delays of varying magnitudes. By considering time-delayed versions of the car states and predicting the present (un-delayed) states, the DTDF compensates for the effects of communication delays. The proposed approach combines classical control techniques with machine learning, offering a hybrid control system that excels in explainability and robustness to unknown parameters. We conduct comprehensive experiments using various deep-learning architectures to train and evaluate the DTDF models. Our experiments utilize a robot platform consisting of MATLAB, Simulink, the Optitrack motion capture system, and the Qbot2e robots. Through these experiments, we demonstrate that when appropriately trained, our system can effectively mitigate the adverse effects of constant time delays and outperforms a traditional CACC baseline in control performance. This experimental comparison, to the best of the author’s knowledge, is the first of its kind in the context of a hybrid machine learning CACC system. We thoroughly explore initial conditions and range policy parameters to evaluate our system under various experimental scenarios. By providing detailed insights and experimental results, we aim to contribute to the advancement of CACC research and highlight the potential of hybrid machine learning approaches in improving the performance and reliability of CACC systems.