Local Reference Signal Research Articles

Event-triggered fuzzy adaptive output feedback containment fault-tolerant control for nonlinear multi-agent systems against actuator faults

In this paper, the observer-based fully distributed event-triggered adaptive fuzzy containment fault-tolerant control (FTC) problem is studied for nonlinear multi-agent systems (MASs) subject to unknown actuator faults. Fuzzy logic systems (FLSs) are utilized to model unknown agents, and a new state observer is constructed to estimate unmeasurable states. Since the global communication information of topology is not available, the local reference signals are also not available, a distributed estimator is introduced to obtain the information of the local reference signals. To deal with the unknown actuator faults, a novel actuator fault compensation mechanism with a projection operator is adopted. Then based on backstepping technique and by designing a two-channel event-triggered mechanism, a fully distributed event-triggered containment FTC approach is developed. It is testified that all parameters and variables of the controlled system are bounded, and the followers can converge to the dynamic convex hull spanned by the leaders. Finally, we apply the developed control algorithm to the multiple unmanned surface vehicle (USV) systems, and the corresponding simulation results further confirm the feasibility of the developed control algorithm.

Robust adaptive finite-time containment control for nonlinear multi-agent systems with unknown input saturations

In this article, the distributed adaptive finite-time containment control problem is investigated for nonlinear multi-agent systems with unknown input saturations. Since the leaders are only available to partial subsystems, a distributed estimator is designed to estimate the local reference signals. The saturated function is converted to the combination of a linear part and a nonlinear part, thus overcomes the difficulties caused by unknown saturated bounds. By utilising the command filtered and backstepping control techniques, a two-step method is adopted to construct the controller, under which the effect of unknown input saturations can be compensated well. It is proved that the closed-loop system is practical finite-time stable, and the output of each follower can converge to the dynamic convex hull spanned by the leaders in finite time. Finally, a group of four one-link manipulator systems is used to support the feasibility of the developed control scheme.

Real-time adaptive optical self-interference cancellation for in-band full-duplex transmission using SARSA(λ) reinforcement learning.

Self-interference (SI) due to signal leakage from a local transmitter is an issue in an in-band full-duplex (IBFD) transmission system, which would cause severe distortions to a receiving signal of interest (SOI). By superimposing a local reference signal with the same amplitude and opposite phase, the SI signal can be fully canceled. However, as the manipulation of the reference signal is usually operated manually, it is difficult to ensure a high speed and high accurate cancellation. To overcome this problem, a real-time adaptive optical SI cancellation (RTA-OSIC) scheme using a SARSA(λ) reinforcement learning (RL) algorithm is proposed and experimentally demonstrated. The proposed RTA-OSIC scheme can automatically adjust the amplitude and phase of a reference signal by adjusting a variable optical attenuator (VOA) and a variable optical delay line (VODL) achieved through an adaptive feedback signal, which is generated by evaluating the quality of the received SOI. To verify the feasibility of the proposed scheme, a 5 GHz 16QAM OFDM IBFD transmission experiment is demonstrated. By using the proposed RTA-OSIC scheme, for an SOI at three different bandwidths of 200, 400, and 800 MHz, the signal can be adaptively and correctly recovered within 8 time periods (TPs), which is the required time of a single adaptive control step. The cancellation depth for the SOI with a bandwidth of 800 MHz is 20.18 dB. The short- and long-term stability of the proposed RTA-OSIC scheme is also evaluated. The experimental results indicate that the proposed approach could be a promising solution for real-time adaptive SI cancellation in future IBFD transmission systems.

Distributed Adaptive Fuzzy Containment Control for State-Constrained Multiagent Systems With Uncertain Leaders

This article investigates the containment control for state-constrained multiagent systems. Existing results assume that the dynamic of the multiple leaders is known as prior knowledge. First, a distributed adaptive observer is used to estimate the leader's unknown parameters. The local reference signal and its high-order derivatives are generated by an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n$</tex-math></inline-formula> th-order filter, which will be employed in the backstepping design procedures. Second, a log-type nonlinear state-dependent barrier function is established to cope with the time-varying asymmetric full-state constraints. The constrained system is equivalently transformed into a nonconstrained one. Finally, a distributed adaptive fuzzy containment control scheme is developed for the nonconstrained system. Only one adaptive law is required in each distributed controller, and no feasibility conditions and partial-derivative terms are involved in the virtual and actual controllers. In addition, the time derivatives of the candidate Lyapunov functions are guaranteed to be negative semidefinite by introducing a series of reduced-order smooth functions. It is proved that the containment error converges to a user-predefined interval, and all the signals in the closed-loop system are bounded. The time-varying asymmetric full-state constraints imposed on the followers are not violated. Two illustrative examples demonstrate the effectiveness of the suggested approach.

Observer-based adaptive fuzzy containment control for state-constrained nonlinear MASs based on quantization communication

In this article, the fuzzy adaptive output feedback quantized containment control problem is investigated for state-constrained nonlinear multi-agent systems (MASs). The state observer and FLSs are utilized to obtain the state estimations and approximate the unknown nonlinear dynamics, respectively. An estimation is designed to model the unknown local reference signal caused by the unavailability of the global information. To solve the nondifferential problem of the virtual controllers caused by the quantized outputs of neighbors, an auxiliary system is designed, under which the noncontinuous filter errors can be replaced by the auxiliary signals. By introducing the log-type barrier Lyapunov function (BLF) to backstepping recursive design, an adaptive fuzzy quantized containment controller is developed. Based on the Lyapunov stability theory, it is proved that the closed-loop system is stable, the output of each follower can be driven into the dynamic convex hull spanned by the leaders, and the states of system will not exceed their constrained bounds. Finally, a group of two virtual leaders and three unmanned surface vehicles (USVs) are utilized to test the effectiveness of the developed control approach.

Distributed Adaptive Tracking Control for High-Order Nonlinear Multiagent Systems Over Event-Triggered Communication

In this article, we investigate the consensus problem for high-order nonlinear multiagent systems (MASs) with an uncertain leader under event-triggered communication. Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered is more general, while achieving better performance in term of asymptotic tracking. To estimate the unknown parameters of the uncertain leader, distributed intermediate parameter estimators based on event-triggered communication mechanism are first introduced. To guarantee that high-order derivatives exist when applying the backstepping method, such estimators are further modified to obtain final estimators having a polynomial form by using the Hermite interpolation method. Moreover, novel high-order filters are proposed to generate local reference signals and to ensure the existence of high-order derivatives of the filter states. Based on the developed filters, a backstepping-based decentralized adaptive controller is developed. It is proved that consensus errors are asymptotically convergent with the developed method. Finally, simulation examples are provided to show the effectiveness of the proposed method.

Privacy-preserving dynamic average consensus via state decomposition: Case study on multi-robot formation control

Dynamic average consensus is a decentralized control/estimation framework where a group of agents cooperatively track the average of local time-varying reference signals. In this paper, we develop a novel state decomposition-based privacy preservation scheme to protect the privacy of agents when sharing information with neighboring agents. Specifically, we first show that an external eavesdropper can successfully wiretap the reference signals of all agents in a conventional dynamic average consensus algorithm. To protect privacy against the eavesdropper, a state decomposition scheme is developed where the original state of each agent is decomposed into two sub-states: one succeeds the role of the original state in inter-node interactions, while the other sub-state only communicates with the first one and is invisible to other neighboring agents. Rigorous analyses are performed to show that (1) the proposed privacy scheme preserves the convergence of the average consensus; and (2) the privacy of the agents is protected such that an eavesdropper cannot discover the private reference signals with guaranteed accuracy. The developed privacy-preserving dynamic average consensus framework is then applied to the formation control of multiple non-holonomic mobile robots, in which the efficacy of the scheme is demonstrated. Numerical simulation is provided to illustrate the effectiveness of the proposed approach.

Optimized Doppler Estimation and Symbol Synchronization for Mobile M-ary Spread Spectrum Underwater Acoustic Communication

In mobile underwater acoustic (UWA) communications, the Doppler effect causes severe signal distortion, which leads to carrier frequency shift and compresses/broadens the signal length. This situation has a more severe impact on communication performance in the case of low signal-to-noise ratio and variable-speed movement. This paper proposes a non-data-aided Doppler estimation method for M-ary spread spectrum UWA communication systems in mobile scenarios. The receiver uses the spread spectrum codes dedicated to transmitting signals with different frequency offsets as local reference signals. Correlation operations are performed symbol by symbol with the received signal. The decoding and Doppler estimation of the present symbol are achieved by searching the correlation maximum in the code domain and frequency domain. The length of the current symbol is corrected for the next symbol synchronization using the estimated Doppler coefficient. To optimize the process of Doppler estimation and symbol synchronization, a heuristic search method is used. By adjusting the Doppler factor search step size, setting the threshold value, and using the Doppler factor estimation of the previous symbol, the search range can be significantly reduced and the computational complexity decreased. The Fisher-Yates shuffle algorithm is used to traverse the search range to ensure reliability of the results. Simulation results show that enlarging the frequency-domain search step size in some degree does not affect the decoding accuracy. On 15 May 2021, a shallow-water mobile UWA spread spectrum communication experiment was conducted in Weihai, China. The horizontal distance between the transmitter and the receiver is 3.7–4.0 km, and the communication rate is 41.96 bits per second. The transmitting ship moves at a speed of 0–3 m/s, and the bit error rate (BER) is lower than 1e−3, which is better than that of the sliding correlation despreading method with average Doppler compensation.

Photonic-Assisted Multipath Self-Interference Cancellation for Wideband MIMO Radio-Over-Fiber Transmission

To cancel the multipath self-interference at the receiver of a wideband in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) radio-over-fiber (RoF) transmission system, a photonic-assisted approach is proposed and experimentally demonstrated. A multipath optical tunable delay line (MOTDL) module with a large adjusting arrangement and high tuning precision is designed to manipulate the local reference signals, which are modulated onto several optical wavelengths and then poured into the MOTDL via a dense wavelength division multiplexer (DWDM). By tuning the time delay and attenuation of each path in the MOTDL, all the self-interference signals can be cancelled from other local transmit antennas of the MIMO RoF transmission system, and the desired radio frequency (RF) signal can be recovered. A proof-of-concept experiment is carried out to verify the feasibility. Results show that at the receiver of a 3 &#x00D7; 3 MIMO RoF transmission system, the multipath self-interference cancellation depths of 30.18 dB, 24.9 dB, 22.7 dB, and 20.88 dB at 16.6 GHz are achieved for the bandwidths of 100 MHz, 500 MHz, 1 GHz, and 2 GHz, respectively.

Distributed Average Tracking Problem Under Directed Networks: A Distributed Estimator-Based Design

This article considers the distributed average tracking (DAT) problem that a group of agents aims to track the average of local reference signals. The communication network is strongly connected but not required to be weight balanced. A framework of distributed estimator-based algorithm design without any initialization requirement is presented. For agents with nominal first-order (FO) dynamics, a class of distributed estimators is proposed to estimate the average of local reference signals within fixed time, with which each agent finally achieves the DAT within fixed time. For agents with second-order dynamics subject to modeling uncertainty, unmodeled dynamics, as well as external disturbances, a class of distributed estimator is proposed to estimate the average of local reference signals within fixed time, and then a local disturbance-observer-based control protocol is proposed for each agent to achieve DAT asymptotically. Different from most of the existing DAT results under general directed networks that DAT error can only be made globally ultimately bounded, the exact DAT can be achieved within fixed time or asymptotically here. Further, the idea of distributed estimator is applied to solve a class of distributed optimization problems within finite time. Finally, two simulation examples are given to show the effectiveness of the theoretical results.

Ultrastable Long-Haul Fiber-Optic Radio Frequency Transfer Based on Dual-PLL

In this paper, we demonstrate ultrastable radio-frequency (RF) transfer over long-haul optical fiber link. Our stabilized RF transfer technique is based on high-performance dual phase locked loops (dual-PLL) configuration which improves signal to noise ratio (SNR) of the round trip transmitted signals. At the local site, the frequency conversion phase-lock receiver (FCPLR) accomplishes high-quality phase tracking of the RF signal which is transmitted after long distance optical fiber link. The low phase noise signal generated by FCPLR is passively mixed with a local reference signal to realize phase conjugation. Through advisable frequency design, there is no residual RF leakage and nonlinear effect of frequency mixing. Another PLL incorporating a high-quality cleanup oscillator is located at the remote site that favourably improves short-term instability of our transmission system. In our experiment, stabilized 2.4 GHz RF signal transfer over a 1007 km optical fiber link is demonstrated without any electric relay system, and the transmission system achieves a fractional frequency instability of 8.20 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-14</sup> @1 sand 7.87 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-17</sup> @10 000 s.

Iterative receiver for the triple differential PSK modulation in the time‐varying underwater acoustic communications

Due to the time-varying property of the underwater acoustic (UWA) channel, the significant Doppler spread will severely degrade the performance of direct-sequence spread-spectrum (DSSS) communications. The relative velocity variation between the transmitter and the receiver will cause both the phase rotation and the magnitude loss of correlation peak, during the long transmission of the DSSS packet. To solve this problem, the authors propose a novel transceiver design for the UWA DSSS communications. At the transmitter, the triple differential phase shift keying (D 3 PSK) modulation is adopted to overcome the phase rotation, whereas the phase noise will be amplified resulting in the signal-to-noise ratio (SNR) loss. At the receiver, the improved bit-interleaved coded modulation with iterative decoding algorithm for D 3 PSK is used to recover the SNR loss, in which the D 3 PSK demodulator is treated as the convolutional decoder, and the linear prediction is adopted to track the channel variation. Furthermore, an adaptive selection of local reference signal is also applied to recover the correlation loss. Theoretical simulation shows that the proposed transceiver can effectively mitigate the performance loss caused by the motion acceleration, and the performance gain is significant over the conventional.

A Symbol-Based Passband Doppler Tracking and Compensation Algorithm for Underwater Acoustic DSSS Communications

In this paper, we consider the problem of Doppler tracking and compensation for a direct sequence spread spectrum (DSSS) signal in underwater acoustic (UWA) communication. Since the dynamic property of the UWA channel and the long duration of DSSS signals result in significant Doppler spread that severely distorts the propagated signal, Doppler tracking and compensation are required. Based on the ultra-wideband property of UWA signal, the Doppler spread not only results in the frequency shift, but also changes the signal duration. Therefore, the accurate estimation of the signal expansion/compression in the time domain can reflect the Doppler spread. Accordingly, we present a Doppler tracking and compensation algorithm for a DSSS signal operating on the correlation output of passband signal at a symbol-by-symbol basis. Note that the carrier frequency of UWA communication is around several kilohertz, and thus the time delay estimation can be performed on the passband to improve the accuracy. Furthermore, the prior information of Doppler limit is used to refine the resolution of delay estimation and achieve sequential estimation. To compensate the correlation magnitude distortion induced by the velocity variation, the local reference signal is selected adaptively based on the filtered Doppler factor. Simulation results demonstrate that the proposed passband Doppler tracking algorithm achieves a superior performance compared with the conventional receiver.

The Statistics of Computer Clocks and the Design of Synchronization Algorithms.

In this study, I used standard statistical tools (such as the various forms of the two-sample Allan variance) to characterize the clocks in computers, and I show how the results of this study are used to design algorithms to synchronize the computer clocks. These synchronization algorithms can be used to synchronize the time of a computer to a local reference clock or to a remote server. The algorithms by themselves are not intended to be a simple replacement for software that implements the Network Time Protocol (NTP) or any other similar application. Instead, they describe the statistical principles that should be used to design an algorithm to synchronize any computer clock by using data from any external reference received in any format. These algorithms have been used to synchronize the clocks of the computers that support the Internet Time Service operated by the National Institute of Standards and Technology (NIST), and I illustrate the performance of the algorithm with real-time data from these servers. In addition to presenting the design principles of the algorithm, I illustrate the principles with two specific examples: synchronizing a computer clock to a local reference signal, and the design of a synchronization process that is based on time-difference data received from a remote server over the public Internet. The message exchange between the local system and the remote server in this configuration is realized in NTP format, but that is not a fundamental requirement.

An Improved Pre-Processing Algorithm for Resolution Optimization in Galileo-Based Bistatic SAR

Galileo based bistatic synthetic aperture radar (Galileo-BiSAR) is a subclass of passive radar, where the Galileo satellite is used as the transmitter and the receiver can be mounted on a moving vehicle or fixed on the ground. Such scheme is cost-effective and safe, and therefore can be widely used in military areas such as battle monitoring or civil scenarios such as ground deformation monitoring, change detection, etc. However, the drawback of Galileo-BiSAR system lies on the fact that, same with other passive radar, the transmitter and receiver are separately located, which introduces the necessity of pre-processing before further processing such as image formation. The existing pre-processing algorithm for Galileo-BiSAR system was established on the idea that only single band E5b signal is used. Due to its bandwidth of 20MHz, however, the range resolution of resulting image is merely up to 15m, which is not acceptable for most applications. Aimed at improving range resolution, this article proposes a new pre-processing algorithm for Galileo-BiSAR. Rather than employing the single band signal as well as duplicate of transmitting signal as the local reference signal in tradition way, a novel technique of dual matched filtering is proposed for pre-processing. Full simulations of the proposed pre-processing and further image formation were both performed. The results demonstrated the full functionality of the proposed pre-processing algorithm and verified its capability of higher resolution imaging against traditional algorithm. In addition, the paper also highlights its good computational efficiency and performance limitation against noise.

Distributed Average Tracking in Multi-Agent Coordination: Extensions and Experiments

This paper addresses the distributed average tracking (DAT) problem for a group of agents to track the average of multiple time-varying reference signals, each of which is available to only one agent, under local interaction with neighbors and an undirected graph. We consider three cases: 1) DAT for single-integrator dynamics with a chain of integrators in algorithm design; 2) DAT with swarm behavior for single-integrator dynamics; and 3) DAT with swarm behavior for double-integrator dynamics. First, a continuous distributed algorithm with a chain of two integrators is proposed for single-integrator dynamics, where each agent needs its own and its neighbors’ filter outputs obtained through communication besides its absolute position, local relative positions, reference signal, and reference velocity. The introduced algorithm can deal with a wide class of reference signals with steady deviations among reference velocities. Then, two swarm-based DAT algorithms for, respectively, single- and double-integrator dynamics are presented. In the first swarm-based algorithm for single-integrator dynamics, each agent needs to measure the relative positions between itself and its neighbors, while in the second swarm-based algorithm for double-integrator dynamics, relative velocity information is required too. In both cases, the information can be obtained through local sensing. If correct initialization constraints can be achieved, the center of the agents will track the average of the reference signals and the agents will maintain connectivity and avoid interagent collision. Numerical simulations are also presented to illustrate the theoretical results. Finally, the algorithms presented in this paper are experimentally implemented and validated on a multirobot platform.

Detection performance improvement of photon counting chirped amplitude modulation lidar with response probability correction**Project supported by the Fundamental Research Funds for the National Defense Basic Scientific Research, China (Grant No. JCKY2016603C007).

Geiger mode avalanche photodiode detector (Gm-APD) possesses the ultra-high sensitivity. Photon counting chirped amplitude modulation (PCCAM) light detection and ranging (lidar) uses the counting results of the returned signal detected by Gm-APD to mix with the reference signal, which makes PCCAM lidar capable of realizing the ultra-high sensitivity, and this is very important for detecting the remote and weak signal. However, Gm-APD is a nonlinear device, different from traditional linear detectors. Due to the nonlinear response of Gm-APD, the counting results of the returned signal detected by Gm-APD are different from those of both the original modulation signal and the reference signal. This will affect the mixing effect and thus degrade the detection performance of PCCAM lidar. In this paper, we propose a response probability correction method. First, the response probability correction model is established on the basis of Gm-APD Poisson probability response model. Then, the response probability correction model is used to adjust the original modulation signal that is used to drive laser, in order to make the counting results of the returned signal detected by Gm-APD better mix with the local reference signal in the same form. Through this method, the detection performance of PCCAM lidar is enhanced efficiently.

Unambiguous Tracking Technique Based on Combined Correlation Functions for Sine BOC Signals

A new unambiguous tracking technique based on combined correlation functions for sine Binary Offset Carrier (BOC) signals is proposed in this paper. The key to this method is to exploit two types of local reference signals: the BOC signal and a linear combination of a series of BOC signals with different delays. They are both correlated with the received signals. Then, a correlation function without any positive side peaks is obtained by multiplying the two correlation results to make tracking completely unambiguous. Theoretical analysis and simulation in the tracking stage show that the proposed method has the best code tracking accuracy among the method tracking BOC signals like Binary Phase-Shift Keying signals (BPSK-LIKE), the Pseudo correlation function based Unambiguous Delay Lock Loop (PUDLL), Symmetrical Pulse Ambiguity Removing (SPAR) technique, the method proposed by Shen Feng (SF) and the two methods proposed by Yan Tao (YT-V1 and YT-V2). In multipath environments, the proposed method has the best anti-multipath performance of all the tracking methods mentioned above. In conclusion, the proposed method can completely eliminate ambiguity and has significant performance advantages compared with the methods mentioned above.

Improved synchronisation algorithm based on reconstructed correlation function for BOC modulation in satellite navigation and positioning system

With the development of the new generation satellite navigation and positioning systems utilise binary offset carrier (BOC) modulation to improve inter-operability. The main shortcoming of BOC modulation is its ambiguity of searching for a multi-peaked auto-correlation function (ACF). In this study, an improved unambiguous synchronisation algorithm based on compensated correlation reconstructed technique (CCRT) is proposed for the arbitrary-order BOC, which is a new modulation technique for navigation modernisation. The key technique used in this study is to generate local reference signals with different shape vectors. By recombining the piecewise correlation functions of the step-shape coded symbol, a reconstructed correlation function which has only one peak is obtained, and the energy loss is compensated by the ACF. In the proposed algorithm, different shape vectors are employed in different BOC modulation signals. The simulation results demonstrate that the ambiguity problem is completely eliminated. Compared with traditional synchronisation methods, the proposed algorithm shows outstanding detection and multipath mitigation performance. Moreover, the CCRT can be utilised for arbitrary stage BOC modulation signals.

SSCM: An Unambiguous Acquisition Algorithm for CBOC Modulated Signal

Composite binary offset carrier (CBOC) signal has been widely researched in GNSS. The main ingredient of CBOC signal is BOC(1,1) signal. Usually, the acquisition method for BOC(1,1) signal is used to capture CBOC signal, while the research of special acquisition method for CBOC signal is rare. In this letter, according to the principle and characteristics of CBOC signal, a special side-peak cancellation method (SSCM) is proposed and simulated. In this method, two special auxiliary signals are introduced. And the local reference signals are obtained by multiplying the data channel signal and pilot channel signal by the auxiliary signals. The cross-correlation results from the received pilot signal and the two local pilot signals with different auxiliary signals will subtract from one another. Then, side peaks of correlation function and in-band noise of pilot channel are suppressed, while the data channel has the same operation results. At last the outputs of pilot channel and data channel will be added up to make full use of the received signal power. By this way, the acquisition efficiency, accuracy, and adaptability to low signal-to-noise ratio (SNR) conditions for CBOC signal have been improved, alongside possible solution when the GNSS receiver works in a critical environment.