Forward Channel Research Articles

A comparative analysis of flow features of Newtonian and power law material: A New configuration

In recent years, material analysis of fluids has generated prodigious interest of researchers due to their effective role in interdisciplinary sciences. In view of its importance, the present communication is devoted to analyze the flow of power law fluid representing the features of shear thinning, shear thickening and Newtonian materials. Constitutive equations expressed in the form of tensorial representations depicting power law relation between viscosity and shear rate. The whole mathematical model is solved computationally via of finite element method by using stable P2−P1 finite element pair. A highly refined hybrid mesh is obliged for the accurate computation of results. Material properties of power law fluid are disclosed in physical configuration renowned as channel driven cavity combining various benchmark problems like cavity flow, forward and backward facing steps and channel flow. Impact of material parameters on pertinent profiles is disclosed through graphs. Verification of computed results is done by comparing the velocity, viscosity, pressure fields for power law fluid with the Newtonian case.

Hierarchical least squares identification for feedback nonlinear equation-error systems

Because of complex structures, the identification of nonlinear systems is very difficult, especially for closed-loop nonlinear systems (i.e., feedback nonlinear systems). This paper considers the parameter identification of a feedback nonlinear system where the forward channel is a controlled autoregressive model and the feedback channel is a static nonlinear function. Using the hierarchical identification principle decomposes a feedback nonlinear system into two subsystems, one contains the parameters of the linear dynamic block and the other contains the parameters of the nonlinear static block. A hierarchical least squares algorithm and a recursive least squares algorithm are presented for feedback nonlinear systems. The proposed algorithms are simple in principle and easy to implement on-line.

Stability analysis on networked control systems under double attacks with predictive control

SummaryIn this paper, stability of a networked control system under denial‐of‐service and false data injection attacks is analyzed with a predictive control method. To model denial‐of‐service attacks on the forward channel of networked control system, game theory is introduced for obtaining balanced results by denial‐of‐service frequency and duration. Then, measurement outputs of the networked control system are maliciously modified in the feedback channel. Under this double attack strategy, the stability of networked control system with predictive control is analyzed using a switched system method. By comparing three types of attack models, advantages of the double attacks are discussed to illustrate the necessity of this research. A numerical simulation is given to demonstrate effectiveness of the proposed methods on a networked control system under double attacks.

Collusion or Not: The optimal choice of competing retailers in a closed-loop supply chain

While previous studies overlook the collusive behavior of retailers under bidirectional competition, we study a closed-loop supply chain (CLSC) consisting of one manufacturer and two competing retailers whose competition exists in the forward and reverse channels. Considering the retailers' potential collusive behavior and the upstream manufacturer's interactive decisions, we build three two-tier game models: Stackelberg-collusion model, Stackelberg-Nash model, and Stackelberg-Stackelberg model. We first obtain the equilibrium decisions of the manufacturer and the retailers in the three models. Furthermore, we investigate whether collusion is beneficial to the two retailers. We find that the retailers' collusion always brings remarkable profit improvement to them as a whole, while the smaller retailers may suffer severe profit loss. A profit-sharing contract is, therefore, designed to guarantee that each retailer can gain more profit by collusion. We also compare the environmental benefit and social welfare among the three models and find that collusion may do harm to the environment or social welfare compared with other models.

Performance Comparison of Linear Precoders for TDD Large Scale MIMO System with Imperfect Reciprocity and Channel Estimations

Channel estimation is an essential component, in which channel state information playing very important role in wireless communications. But acquiring CSI in practice is a challenging issue for massive MIMO systems. To reduce the over burden for obtaining channel impulse response of huge Multi input multi output system channel reciprocity in TDD domain is suggested, because the forward link channel data can be derived from the reverse link signal without any feedback involvement. Because of mismatches at uplink, downlink channels maintaining reciprocity in TDD systems is impractical. We study the impact of multiplicative reciprocity error for precoders (Zero forcing, MMSE and MRT) performance along with channel estimation error. In this paper effect of RF mismatches impact on linear precoders is analyzed and simulated in terms of SINR versus SNR under additive white Gaussian noise.

The Estimation and Compensation of the Loop-Parameter-Drifting in the Digital Close-Loop Quartz Flexible Accelerometers

There have been increasing demands for the long-term performance retention of the Quartz Flexible Accelerometers (QFA), extensively employed in the Inertial Navigation System (INS). Considering the convenience of conducting the parameter identification and control algorithm, the Digital Close-Loop QFA (Digital-QFA) is established to improve the long-term performance. Based on the model of the entire close-loop system, the interfering factors relating to time are analyzed in detail, both in the forward channel and the feedback channel. Two schedules are proposed to estimate the gain variation, utilizing the modulating signal and the feedback signal separately. According to the reference gain settings in ideal conditions, the forward and the feedback gain drifting of the system are calibrated online through the adjustment of the digital controller and the reference voltage of the DA-chip, separately. The simulation experiments show that about 90.26% of the gain-drifting could be estimated and about 87.56% of the output error of the accelerate could be restrained. Consequently, the proposed schedules could promote the long-term stability of the Digital-QFA significantly.

Secrecy Capacity of Colored Gaussian Noise Channels With Feedback

In this paper, the finite-order autoregressive moving average (ARMA) Gaussian wiretap channel with noiseless causal feedback is considered, in which an eavesdropper receives noisy observations of signals in both forward and feedback channels. It is shown that the generalized Schalkwijk–Kailath scheme, a capacity-achieving coding scheme for the Gaussian feedback channel, achieves the same maximum rate for the same channel even with the presence of an eavesdropper. Therefore, the secrecy capacity is equal to the feedback capacity without the presence of an eavesdropper for the Gaussian feedback channel. Furthermore, the results are extended to the additive white Gaussian noise (AWGN) channel with quantized feedback. It is shown that the proposed coding scheme achieves a positive secrecy rate. Our result implies that as the amplitude of the quantization noise decreases to zero, the secrecy rate converges to the capacity of the AWGN channel.

Recursive Identification Algorithms for a Class of Linear Closed-loop Systems

This paper focuses on the identification problems for a class of linear closed-loop systems. On one hand, the identifiability condition is investigated for the case where the controller is in series with the plant on the forward channel. On the other hand, the identification model is derived after parametrization, in which the parameter vector only contains the parameters of the controlled plant instead of the whole closed-loop system, and a recursive least squares algorithm and a stochastic gradient algorithm are proposed for closed-loop systems. In order to improve the parameter estimation accuracy, a forgetting factor and a convergence index are introduced into the proposed stochastic gradient algorithm. The simulation results demonstrate the effectiveness of the proposed algorithms.

Predictive cloud control for multiagent systems with stochastic event-triggered schedule

This paper addresses a predictive cloud control problem for a linear multiagent system with random network delays and noises. To reduce communication cost, a stochastic event-triggered schedule is introduced to decide whether current measurements need to be transmitted. An optimal state estimation algorithm is designed to compensate random network delays in the feedback channel. Subsequently, a predictive cloud control scheme is proposed for the multiagent system to achieve both stability and consensus. Simultaneously, random network delays in the forward channel is compensated actively. Sufficient and necessary conditions of stability and consensus for the closed-loop multiagent system are derived. Finally, a numerical example is provided to verify correctness and effectiveness of the proposed methods.

Single-End Adaptive Optics Compensation for Emulated Turbulence in a Bi-Directional 10-Mbit/s per Channel Free-Space Quantum Communication Link Using Orbital-Angular-Momentum Encoding

A single-end adaptive-optics (AO) module is experimentally demonstrated to mitigate the emulated atmospheric turbulence effects in a bi-directional quantum communication link, which employs orbital angular momentum (OAM) for data encoding. A classical Gaussian beam is used as a probe to detect the turbulence-induced wavefront distortion in the forward direction of the link. Based on the detected wavefront distortion, an AO system located on one end of the link is used to simultaneously compensate for the forward and backward channels. Specifically, with emulated turbulence and when the probe is turned on, the mode purity of photons carrying OAM l=1 is improved by ~ 21 % with AO mitigation. We also measured the performance when encoding data using OAM {l=-1,+2} and {l=-2,+1} in the forward and backward channels, respectively, at 10 Mbit/s per channel with one photon per pulse on average. For this case, we found that the AO system could reduce the turbulence effects increased quantum-symbol-error-rate (QSER) by ~ 76 % and ~ 74 %, for both channels in the uni-directional and bi-directional cases, respectively. Similar QSER improvement is observed for the opposite direction channels in the bi-directional case.

Robust Guaranteed-Cost Preview Repetitive Control for Polytopic Uncertain Discrete-Time Systems

In this paper, a robust guaranteed-cost preview repetitive controller is proposed for a class of polytopic uncertain discrete-time systems. In order to improve the tracking performance, a repetitive controller, combined with preview compensator, is inserted in the forward channel. By using the L-order forward difference operator, an augmented dynamic system is constructed. Then, the guaranteed-cost preview repetitive control problem is transformed into a guaranteed-cost control problem for the augmented dynamic system. For a given performance index, the sufficient condition of asymptotic stability for the closed-loop system is derived by using a parameter-dependent Lyapunov function method and linear matrix inequality (LMI) techniques. Incorporating the controller obtained into the original system, the guaranteed-cost preview repetitive controller is derived. A numerical example is also included, to show the effectiveness of the proposed method.

Single-End Adaptive Optics Compensation for Emulated Turbulence in a Bi-Directional 10-Mbit/s per Channel Free-Space Quantum Communication Link Using Orbital-Angular-Momentum Encoding.

A single-end adaptive-optics (AO) module is experimentally demonstrated to mitigate the emulated atmospheric turbulence effects in a bi-directional quantum communication link, which employs orbital angular momentum (OAM) for data encoding. A classical Gaussian beam is used as a probe to detect the turbulence-induced wavefront distortion in the forward direction of the link. Based on the detected wavefront distortion, an AO system located on one end of the link is used to simultaneously compensate for the forward and backward channels. Specifically, with emulated turbulence and when the probe is turned on, the mode purity of photons carrying OAM ℓ = 1 is improved by ~ 21 % with AO mitigation. We also measured the performance when encoding data using OAM {ℓ = −1, + 2} and {ℓ = −2, + 1} in the forward and backward channels, respectively, at 10 Mbit/s per channel with one photon per pulse on average. For this case, we found that the AO system could reduce the turbulence effects increased quantum-symbol-error-rate (QSER) by ~ 76 % and ~ 74 %, for both channels in the uni-directional and bi-directional cases, respectively. Similar QSER improvement is observed for the opposite direction channels in the bi-directional case.

Stabilization of Linear Systems Over Networks With Limited Communication Capacity

In this paper, we discuss the modeling and control problem for networked systems with access constraints and packet dropouts. Due to the limitation of communication capacity, only the limited number of sensors and actuators are allowed to gain access to network medium according to a stochastic access protocol, and packet dropouts may happen in both backward and forward channels, which can be described by i.i.d Bernoulli processes. Under consideration of the access constraints and packet dropouts, the networked control system can be modelled as a Markov jump system. In such a framework, to solve the controller synthesis problem, the time-varying Kalman filter is first designed. Then, by using the theory of Markovian jump systems and dynamic programming, an optimal controller is designed such that the networked system is exponentially mean-square stable while minimizing the quadratic cost. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed results.

Recursive least squares algorithm and stochastic gradient algorithm for feedback nonlinear equation-error systems

Many industrial systems exhibit the nonlinear characteristics. Generally, the structure of the system is taken by feedback closed-loop for the purpose of realising the automatic control of industrial processes. Therefore, the industrial systems are the closed-loop feedback nonlinear systems which have complicated structures. The mathematical models of systems provide the support and basis for the design of the control system and the better control performance. However, it is hard to determine the models of closed-loop feedback nonlinear systems due to the complex structures. The goal of this study is to develop an identification way for a feedback nonlinear system including a forward channel and a feedback channel, where the forward channel is described by a controlled autoregressive model and the feedback channel takes the form of a static nonlinear function. By taking advantage of the least squares optimisation, a recursive least squares algorithm is established and shows its good performance to solve the identification problem for the feedback nonlinear system.

Recursive least squares algorithm and stochastic gradient algorithm for feedback nonlinear equation-error systems

Many industrial systems exhibit the nonlinear characteristics. Generally, the structure of the system is taken by feedback closed-loop for the purpose of realising the automatic control of industrial processes. Therefore, the industrial systems are the closed-loop feedback nonlinear systems which have complicated structures. The mathematical models of systems provide the support and basis for the design of the control system and the better control performance. However, it is hard to determine the models of closed-loop feedback nonlinear systems due to the complex structures. The goal of this study is to develop an identification way for a feedback nonlinear system including a forward channel and a feedback channel, where the forward channel is described by a controlled autoregressive model and the feedback channel takes the form of a static nonlinear function. By taking advantage of the least squares optimisation, a recursive least squares algorithm is established and shows its good performance to solve the identification problem for the feedback nonlinear system.

Design of Closed-Loop Parameters With High Dynamic Performance for Micro-Grating Accelerometer

A novel closed-loop parameter design scheme with timing sequence control method is proposed to obtain fast tracking ability of micro-grating accelerometer. Firstly, we investigate a timing sequence control method to achieve the minimum time-delay of signal processing only dependent on the response capability of sensing element, which is the same as half modulation period in the designed closed-loop accelerometer system. Considering optical sensing principle and time-delay of signal processing, we establish a dynamic equation for closed-loop micro-grating accelerometer. Then, we analyze the design principle of closed-loop parameters on the condition of system stability, which describes the relationship between time-delay and control parameters to guarantee fast tracking performance of micro-grating accelerometer system. And, through proposed parameter design principle, the closed-loop parameters of micro-grating accelerometer can be obtained with the gains of forward channel and feedback channel in closed-loop detection system. The conducted experiment results show that micro-grating accelerometer can achieve the nonlinearity within 0.28%, the fast step response time of 0.8ms and -3dB bandwidth up to 525Hz, which validate the effectiveness of our parameter design scheme and timing sequence control method.

Constrained Control for Cloud Robotic Under Time Delay Based on Command Governor With Interval Estimation

The constrained command tracking problem for the cloud robotic system with unknown bounded time-varying delays is considered. Based on a novel predictor-observer approach, a command governor is proposed to modify the received command in order to guarantee the constraint enforcement of remote robot. We firstly use a prediction algorithm in the forward channel to generate a virtual command, which is close to the original one as much as possible when the danger of constraint violation exists. Then, to deal with the measurement delay and disturbance in the backward channel, interval estimations of the system states are applied instead of delayed measurements in the prediction algorithm of the command governor. The constraints can be rigorously enforced with the upper and lower estimations. The efficiency of the proposed approach is demonstrated by simulations in the case of a single-degree-of-freedom manipulator.

Joint Relay and Eavesdropper Selection Strategy Against Multiple Eavesdroppers over Nakagami-$m$ Fading Channels in Cooperative Decode-and-Forward Relay Networks

Physical layer security (PLS) in the presence of multiple eavesdroppers over Nakagami-m fading channels for cooperative decode-and-forward (DF) relay network that consists of one source, one destination, and multiple relays is investigated. Different from the recent PLS system model that only considers one eavesdropper during eavesdropping attack, this paper extends the one-eavesdropper case to a multiple-eavesdropper scenario and investigates joint relay and eavesdropper selection (JRES) strategy against eavesdropping attack over Nakagami-m fading channels. In the proposed strategy, the best relay is selected via the maximum relay forward channel capacity. In addition, since eavesdroppers are noncooperative, the worst case is considered. Namely, the wiretap channel between the best relay and the chosen eavesdropper has the maximum capacity. Traditional direct transmission and opportunistic relay selection (ORS) scheme in the presence of one eavesdropper over Rayleigh channel are regarded as benchmarks. Moreover, a security-reliability tradeoff (SRT) performance is analyzed, where the reliability performance is expressed by outage probability (OP), while the security performance is measured by intercept probability (IP). Closed-form expressions of OP and IP are derived. The numerical results show that the proposed JRES scheme outperforms the traditional direct transmission and the ORS scheme in the presence of one eavesdropper over Rayleigh channel. The SRT performance is enhanced obviously with the increasing of relay numbers and Nakagami channel fading factor m for a given number of eavesdroppers, which extends the PLS and SRT performance analysis to a more general case in a cooperative DF relay network.

Performance limitation of networked control systems with networked delay and two-channel noises constraints

ABSTRACTThe performance limitation of networked control systems (NCSs) with networked delay and two-channel noises constraints are studied in this paper. The networked parameters mainly consider the networked delay in the forward channel and white Gaussian noise constraint existing in forward channel and feedback channel. The tracking performance limitation expression is achieved by using the spectral decomposition technique and selecting the optimal one-parameter structure. The obtained result shows that the tracking performance limitation of NCSs is related to the position of the non-minimum phase zeroes, the position of the unstable poles, networked delay, two-channel noises and input signal. We can also know that the networked delay and white Gaussian noise have influence on the tracking performance limitation of NCSs. Finally, a simulation example is given to demonstrate effectiveness of the theoretical results.

Discrete-Time MIMO Reset Controller and Its Application to Networked Control Systems

Reset control has been shown to have advantages over linear time-invariant controllers, especially, for control loops with time-delays. In this paper, in order to adapt reset control to networked control systems (NCS), multi-input multi-output discrete-time reset control model is first established by decomposing the controller output and defining appropriate flow set and jump sets. Then, we apply discrete-time reset controllers to NCS with time-varying delays in both forward and feedback channels, the modeling framework of networked reset control systems is given based on switched linear parameter-varying systems, and stability conditions are derived in terms of linear matrix inequalities. Finally, experimental and simulation examples are presented to illustrate the superior performance of the proposed approaches.