Delay Control Research Articles

Design of a Self-Organizing Routing Protocol for Underwater Wireless Sensor Networks Based on Location and Energy Information

Underwater wireless sensor networks (UWSNs) are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, variable topology, limited battery, low processing power and so on. These new features pose many challenges to the design of self-organizing routing protocol for UWSNs. This paper focuses on the application of Ad Hoc On-demand Distance Vector (AODV) routing protocol in UWSNs. In order to solve the problems of packet collision and excessive energy consumption associated with the flooding-based routing discovery method and the periodic hello packet routing maintenance mechanism of AODV, a routing discovery and maintenance method based on location and energy information is proposed, and it is referred to as the route-focusing AODV (RFAODV) routing protocol. In the RFAODV protocol, the routing discovery process is focused on a few nodes through forwarding area control and dynamic delay adjustment. In addition, feedback from a media access control layer and residual energy control are used for routing maintenance. We implement the RFAODV and evaluate its performance according to the sea trial data as parameters in the NS-2. The simulation results show that compared with the other protocols, RFAODV improves the routing discovery success ratio by at least 18%, increases the packet transmission ratio by at least 4%, reduces the protocol overhead by at least 15% and reduces the energy consumption by at least 5% under various simulation scenarios. RFAODV is suitable for large-scale, high-load and dynamic networks underwater wireless sensor networks.

Aggregation Dispatch and Control Strategies for Multi-Type Loads in Industrial Parks

With the continuous expansion of renewable energy construction, the power system requires a larger-scale flexible dispatchable and controllable resource for power balance. Fully tapping into the power regulation capability of multi-type loads in industrial parks, making them a low-cost flexible dispatchable and controllable resource, is an effective approach to establish power regulation capability at scale in the new power system. However, the control characteristics of multi-type loads in industrial parks vary greatly, and their control delay characteristics, response speed, and sustainable response time are all different. Traditional dispatch and control methods cannot achieve precise control of the massive and multi-type loads in industrial parks. Therefore, this paper establishes unified models for the control characteristics of multi-type loads in industrial parks, quantitatively characterizes their control delay characteristics, start–stop characteristics, and control response speed. Based on this, the aggregated dispatch and control model and dispatch and control strategy for multi-type loads in industrial parks are developed, which provide a predictive control rate for individual loads considering the delay and segmented response characteristics to achieve precise aggregation control of multi-type loads in industrial parks. Simulation results show that the aggregated dispatch and control model and its aggregated dispatch and control strategy achieve precise control of multi-type loads in industrial parks. Flexible dispatchable and controllable loads can provide low-cost power regulation capability for the new power system.

End-Cloud Collaboration Navigation Planning Method for Unmanned Aerial Vehicles Used in Small Areas.

Unmanned aerial vehicle (UAV) collaboration has become the main means of indoor and outdoor regional search, railway patrol, and other tasks, and navigation planning is one of the key, albeit difficult, technologies. The purpose of UAV navigation planning is to plan reasonable trajectories for UAVs to avoid obstacles and reach the task area. Essentially, it is a complex optimization problem that requires the use of navigation planning algorithms to search for path-point solutions that meet the requirements under the guide of objective functions and constraints. At present, there are autonomous navigation modes of UAVs relying on airborne sensors and navigation control modes of UAVs relying on ground control stations (GCSs). However, due to the limitation of airborne processor computing power, and background command and control communication delay, a navigation planning method that takes into account accuracy and timeliness is needed. First, the navigation planning architecture of UAVs of end-cloud collaboration was designed. Then, the background cloud navigation planning algorithm of UAVs was designed based on the improved particle swarm optimization (PSO). Next, the navigation control algorithm of the UAV terminals was designed based on the multi-objective hybrid swarm intelligent optimization algorithm. Finally, the computer simulation and actual indoor-environment flight test based on small rotor UAVs were designed and conducted. The results showed that the proposed method is correct and feasible, and can improve the effectiveness and efficiency of navigation planning of UAVs.

Continuous-Control-Set Model Predictive Current Control of Asymmetrical Six- Phase Drives Considering System Nonidealities

Finite-control-set model predictive control (FCS-MPC) of multiphase ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -phase, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> is assumed to be an odd number for simplicity) drives is challenging because of the large number of actual/virtual voltage vectors and the need for current control in ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -1)/2 sub-spaces (or planes; multi-plane current control). Any sub-optimal design (poor or no current control in some of the ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -1)/2 planes) may result in high individual plane current ripples, due to the low reactance. This work therefore investigates continuous-control-set (CCS) MPC for constant switching frequency multiphase motor drives as another alternative. The high-bandwidth CCS-MPC is designed to accurately account for system non-idealities, namely digital control and pulse width modulation delays, inverter dead time, and measurement noise. It will be shown that the CCS-MPC has the advantages of full voltage vector space access, regular switching characteristic, and improved cycle-by-cycle tracking control, while maintaining some of the known advantages of the FCS-MPC, e.g., intuitive cost function design, model-based control, and fast dynamics. The proposed control scheme is benchmarked experimentally against the classical, proportional-integral-based, field-oriented control in conjunction with an asymmetrical six-phase induction motor drive.

Saturation-Tolerant Prescribed Control for Nonlinear Time-Delay Systems

This paper studies the problem of Saturation-tolerant Prescribed Control (SPC) for a class of nonlinear time-delay systems with unknown control directions. We propose a unified Finite-time Tunnel Prescribed Performance (FTPP), which not only provides more tight allowable set leading to smaller overshoot, but also drives the tracking error into the prescribed set within a known time. To remove the implicit assumption that both input and performance constraints need to be satisfied simultaneously, an auxiliary system is developed to establish a balance between these two constraints instead of ignoring their interconnection and conflict. With aid of its generated nonnegative signals, the developed Saturation-tolerant Prescribed Performance (SPP) possesses flexible performance. Namely, SPP can temporarily enlarge the performance boundaries to guarantee both constraints when input saturation occurs, and fast recover back to the prescribed boundaries when input saturation disappears. Consequently, a low-complexity SPC for uncertain nonlinear systems is developed, which can always guarantee both input and performance constraints even under unknown time delay and unknown control directions. Finally, comparative simulation is provided to illustrate the merits of the presented control strategy.

Voltage Regulating Strategy of a New LCC/S+L Inductive Power Transfer System

In the voltage control of the inductive power transfer (IPT) system, a cascaded DC-DC converter is normally adopted which reduces the power density. However, the wireless communication between the transmitter and the receiver may lead to a delay of control as well as communication instability. This paper proposes a new LCC/S+L resonance topology for the IPT system, which can realize single-stage voltage regulation on the receiving side with both buck and boost capability. Based on the fundamental wave analysis method, this paper analyzes the working principle of LCC/S+L resonant topology. Then the control strategy of the phase shift angle between bridges and within bridges is obtained by the voltage of both ends of the series inductor and the load voltage vector. It is verified by simulation that the proposed new resonance topology and control strategy can achieve output voltage regulation of 300-500 V with a constant 375 V input DC voltage.

Multi-Objective Optimization Method for Signalized Intersections in Intelligent Traffic Network.

Urban intersections are one of the most common sources of traffic congestion. Especially for multiple intersections, an appropriate control method should be able to regulate the traffic flow within the control area. The intersection signal-timing problem is crucial for ensuring efficient traffic operations, with the key issues being the determination of a traffic model and the design of an optimization algorithm. So, an optimization method for signalized intersections integrating a multi-objective model and an NSGAIII-DAE algorithm is established in this paper. Firstly, the multi-objective model is constructed including the usual signal control delay and traffic capacity indices. In addition, the conflict delay caused by right-turning vehicles crossing straight-going non-motor vehicles is considered and combined with the proposed algorithm, enabling the traffic model to better balance the traffic efficiency of intersections without adding infrastructure. Secondly, to address the challenges of diversity and convergence faced by the classic NSGA-III algorithm in solving traffic models with high-dimensional search spaces, a denoising autoencoder (DAE) is adopted to learn the compact representation of the original high-dimensional search space. Some genetic operations are performed in the compressed space and then mapped back to the original search space through the DAE. As a result, an appropriate balance between the local and global searching in an iteration can be achieved. To validate the proposed method, numerical experiments were conducted using actual traffic data from intersections in Jinzhou, China. The numerical results show that the signal control delay and conflict delay are significantly reduced compared with the existing algorithm, and the optimal reduction is 33.7% and 31.3%, respectively. The capacity value obtained by the proposed method in this paper is lower than that of the compared algorithm, but it is also 11.5% higher than that of the current scheme in this case. The comparisons and discussions demonstrate the effectiveness of the proposed method designed for improving the efficiency of signalized intersections.

Controllability of fractional dynamical systems with distributed delays in control using ψ‐Caputo fractional derivative

AbstractThis research investigates the controllability of linear and non‐linear fractional dynamical systems with distributed delays in control using the ‐Caputo fractional derivative. For controllability of linear systems, the positive definiteness of Grammian matrix, which is characterized by Mittag–Leffler functions, is used to provide necessary and sufficient conditions. For the controllability of non‐linear systems, the iterative technique with the completeness of is used to obtain sufficient conditions. Using the ‐Caputo fractional derivative, this study is new since it investigates the ideas of controllability. A couple of numerical results are offered to explain the theoretical results.

Rapid Stabilization of Timoshenko Beam System with the Internal Delay Control

Rapid Stabilization of Timoshenko Beam System with the Internal Delay Control

Cloud Control of Connected Vehicle Under Both Communication-Induced Sensing and Control Delay: A Prediction Method

In this paper, we focus on the problem of cloud control of the connected vehicle with time-varying communication-induced sensing delay and control delay. First, the connected vehicle cloud control system containing communication-induced delay is modeled as the discrete linear output feedback system with bounded input and output delay. Second, corresponding to the linear output feedback system, the “predictor-observer” structured controller is introduced and redesigned to compensate for the delay in both output and input channels actively, without measurement of actual input delay as its original version. The stability of the close-looped prediction-based control system under a certain delay boundary is analyzed, and the sufficient stability condition is proposed. Third, with the help of Cone Complementary Linearization (CCL), an iterative algorithm is proposed to design stabilized controller and observer gains. Finally, the proposed method is verified through vehicle lateral and longitudinal control simulations, and the effectiveness and the performance of the proposed delay compensation strategy are innovatively evaluated under real vehicle control scenarios.

Fractional-Order Prescribed Performance Sliding-Mode Control With Time-Delay Estimation for Wearable Exoskeletons

Wearable exoskeletons can help people with spinal cord injuries regain mobility. For the control of wearable exoskeletons, transient performance and steady-state performance are the important indices to be considered. In this paper, a model-free fractional-order prescribed performance sliding mode control scheme is proposed for the joint angle tracking control. Time delay control is developed based on the ultra-local model of the wearable exoskeleton to form the model-free feature. Afterward, a novel exponential-type barrier Lyapunov function is designed to ensure the prescribed transient performance on the tracking errors. Then, a fractional-order sliding mode surface is introduced, based on the exponential-type barrier Lyapunov function and fractional-order sliding mode surface, a fixed-time sliding mode controller is designed to further enhance the control performance. Benefiting from the above methods, the proposed controller is model-free and has fixed-time convergence with prescribed performance. In addition, the adjustable range of the parameters is enlarged by the fractional-order sliding mode surface. Stability is analyzed based on the Lyapunov theory. Finally, experiments are implemented in the wearable exoskeleton experimental platform, experiment results demonstrate the effectiveness of the proposed scheme.

Cascaded Reflection-Type Group Delay Controller With a Wideband Flat Group Delay

This letter presents a wideband group delay controller (GDC) based on cascaded reflection-type phase shifters (RTPSs). Frequency tunable resonators are used as the reflective loads of each phase shifter so that the phase shifter has a variable group delay resulting in a reflection-type GDC (RTGDC). Two RTGDCs with different types of reflective loads are cascaded to compensate for their group delay variation over frequency. The first and the second stage of the cascaded RTGDC are respectively in charge of the delay in low and high-frequency bands and the cascaded delay is flat over a wide bandwidth. The proposed cascaded RTGDC operates at 3.7 GHz over 200-MHz bandwidth. The measured group delay varies from 0.67 to 2.18 ns, which is a 1.51-ns group delay variation under 9.1% normalized group delay variation over the bandwidth. The return loss is over 18 dB and the insertion loss is 2.1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm$</tex-math> </inline-formula> 1.3 dB at 3.7 GHz.

Chaotic Behaviors of a Delay Partial Difference Equation with a Delay Controller

A delay partial difference equation with a delay controller is studied in this paper. We show that it can lead to both Devaney chaos and Li–Yorke chaos by applying the modified Marotto’s theorem, with three criteria established for generating chaos. Computer simulations of chaotic behaviors and spatiotemporal graphs are performed with three examples.

LMI-Based robust controller for load frequency control of three area interconnected system

The purpose of this research is to create a robust predictive load frequency control (RPLFC) for power systems with unpredictable parameters and temporal delays in communication networks. The study looks closely at the communication of delay constraints across the various control regions as well as the relationship between delay restrictions and control gains. In addition, the usage of delay restrictions as a new performance index to steer controller design is discussed, along with the regulation of the controller for a trade-off between delay tolerance and dynamic reaction, and opting for the upper bound of the sampling period of a discrete realization of the controller, and the upper bound of the fault counter of the communication channel. All of these topics are brought up in the context of determining how to steer controller design. To determine whether or not the proposed technique is useful, simulation studies have all been outfitted with PID-type controllers and have been run for both single-area and three-area LFC schemes. MATLAB/SIMULINK served as the platform upon which the simulations were carried out.

A Comparative Study on Solution Methods for Fractional order Delay Differential Equations and its Applications

Fractional calculus is one of the evolving fields in applied sciences. Delay differential equation of non-integer order plays a vital role in epidemiology, population growth, physiology economy, medicine, chemistry, control, and electrodynamics and many mathematical modeling problems Fractional Delay differential equations usually lacks analytic solutions and some of these equations can only be solved by some numerical methods. In this review article we present a comparative study on some standard numerical methods applied to solve linear fractional order differential equations with time delay. Fractional finite difference method (FFDM), Predictor-corrector method (PCM) with new and extended versions has been discussed in this article. All above mentioned methods use the Caputo type fractional differential operator to define fractional derivatives. Solution of a real-life problem formulated by FDDEs has been discussed under these methods. Results have been presented in tabular and graphical form to analyze the efficiency and scarcity of mentioned methods. These graphical and numerical comparisons are provided to illustrate and corroborate the similarity and differences between these methods.

Delay-Controlled Bidirectional Traffic Setup Scheme to Enhance the Network Coding Opportunity in Real-Time Industrial IoT Networks

Recently, network coding has become a promising transmission approach to support high throughput and low latency in distributed multi-hop networks. In this paper, we develop a delay-controlled distributed route establishment scheme that can provide maximal bidirectional transmission to enhance network coding gain while satisfying a time-critical route setup. The scheme is called network coding-aware delayed store and forwarding (NC-DSF). It delays the received route information packets before forwarding them according to the link status and network topology. We propose a tight delay function derived using a strict end-to-end delay bound for delay control. Subsequently, we suggest a relaxed delay function derived using realistic and practical conditions. Finally, we propose a load-weighted delay function considering the trade-off between bidirectionality and network-load balancing. The simulations confirm that the proposed scheme offers increased throughput and decreased latency in mesh and random multi-hop networks. The proposed transmission scheme, NC-DSF, can be efficiently employed in future industrial internet of things networks requiring a time-constrained route setup, high throughput, and low latency.

Enhancing Power Generation Stability in Oscillating-Water-Column Wave Energy Converters through Deep-Learning-Based Time Delay Compensation

Oscillating-water-column wave energy converters (OWC-WECs) are gaining attention for their high energy potential and environmental friendliness. However, their irregular input energy characteristics pose challenges to achieving stable power generation, particularly due to high peak power compared to average power. This study focuses on stable rating control to enable continuous power generation in the presence of irregular wave energy. It is difficult to precisely configure the existing rated power controllers due to physical time delays; this impacts system stability and utilization. To address this, we propose a rated power controller that compensates for system time delays using a deep learning algorithm. By predicting the valve control angle in advance and analyzing the input data for angle estimation, we successfully compensate for the physical time delay. The performance of the proposed rated power controller, incorporating the deep learning algorithm, is evaluated by analyzing the algorithm’s error rate. The results demonstrate that the proposed method improves power generation under various wave conditions by compensating for the unavoidable time delay of OWC-WECs, leading to a significant increase in annual power generation. In conclusion, the proposed method achieves approximately 31% higher annual power generation compared to the time delay controller.

Quadrotor UAV Dynamic Visual Servoing Based on Differential Flatness Theory

In this paper, we propose 2D dynamic visual servoing (Dynamic IBVS), where a quadrotor UAV tries to track a moving target using a single facing-down perspective camera. As an application, we propose the tracking of a car-type vehicle. In this case, data related to the altitude and the lateral angles have no importance for the visual system. Indeed, to perform the tracking, we only need to know the longitudinal displacements (along the x and y axes) and the orientation along the z-axis. However, those data are necessary for the quadrotor’s guidance problem. Thanks to the concept of differential flatness, we demonstrate that if we manage to extract the displacements according to the three axes and the orientation according to the yaw angle (the vertical axis) of the quadrotor, we can control all the other variables of the system. For this, we consider a camera equipped with a vertical stabilizer that keeps it in a vertical position during its movement (a gimbaled camera). Other specialized sensors measure information regarding altitude and lateral angles. In the case of classic 2D visual servoing, the elaboration of the kinematic torsor of the quadrotor in no way guarantees the physical realization of instructions, given that the quadrotor is an under-actuated system. Indeed, the setpoint has a dimension equal to six, while the quadrotor is controlled only by four inputs. In addition, the dynamics of a quadrotor are generally very fast, which requires a high-frequency control law. Furthermore, the complexity of the image processing stage can cause delays in motion control, which can lead to target loss. A new dynamic 2D visual servoing method (Dynamic IBVS) is proposed. This method makes it possible to generate in real time the necessary movements for the quadrotor in order to carry out the tracking of the target (vehicle) using a single point of this target as visual information. This point can represent the center of gravity of the target or any other part of it. A control by flatness has been proposed, which guarantees the controllability of the system and ensures the asymptotic convergence of the generated trajectory in the image plane. Numerical simulations are presented to show the effectiveness of the proposed control strategy.

A novel design of 9 level cascade multi-level inverter for decoupled double synchronous reference frame in state delay controller

In this study, we investigate the performance and scheme of a Decoupled Dual Synchronous Reference Frame (DDSRF) system, which is investigated for compensation power generation via Shunt Active Filter (SAF)). Traditional direct power control theory and harmonic cancellation responsibilities are unreliable for unbalanced sources and loads. 9-level cascade multi-level inverter (NLC-MLI) ensures the establishment to generate sufficient compensation power. In this paper, instantaneous active power and reactive power (PQ) are represented by positive, negative, zero sequence and harmonic components. This is to counteract the unbalanced operation of the load, i.e. twice the frequency at which each reference signal is generated. Due to the delay properties of the signal generation control loop, the compensation time can deviate from the reference signal measurement point. A state delay controller (SDC) is proposed to reduce the intermediate delay between the inserted compensation power and the acquired reference signal. The efficiency of the proposed mathematical analysis method is performed using MATLAB/Simulink and verified by an experimental setup running under unbalanced conditions.

A distributed beamforming interference minimization algorithm based on node selection

Distributed beamforming uses nodes in a wireless sensor network to transmit signals in different phases with controllable delay, to obtain coherent output signals with a gain after superposition. However, a wireless sensor network has a large topological area and wide distribution range, and it is difficult for distributed beamforming to obtain a highly directional beam as centralized beamforming does, which will cause interference to the non-target base stations. To solve this problem, a discrete adaptive dual-population cooperative differential evolution (DPCDE) algorithm is proposed, which can effectively reduce the interference by selecting nodes suitable for participating in distributed beamforming in a wireless sensor network. Simulation results show that the proposed algorithm can optimize the node set participating in distributed beamforming to minimize the interference of the wireless sensor network to the non-target base stations, and the effect is better than other classic intelligent optimization algorithms.