261,633 research outputs found

    Coded Kalman Filtering Over Gaussian Channels with Feedback

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    This paper investigates the problem of zero-delay joint source-channel coding of a vector Gauss-Markov source over a multiple-input multiple-output (MIMO) additive white Gaussian noise (AWGN) channel with feedback. In contrast to the classical problem of causal estimation using noisy observations, we examine a system where the source can be encoded before transmission. An encoder, equipped with feedback of past channel outputs, observes the source state and encodes the information in a causal manner as inputs to the channel while adhering to a power constraint. The objective of the code is to estimate the source state with minimum mean square error at the infinite horizon. This work shows a fundamental theorem for two scenarios: for the transmission of an unstable vector Gauss-Markov source over either a multiple-input single-output (MISO) or a single-input multiple-output (SIMO) AWGN channel, finite estimation error is achievable if and only if the sum of logs of the unstable eigenvalues of the state gain matrix is less than the Shannon channel capacity. We prove these results by showing an optimal linear innovations encoder that can be applied to sources and channels of any dimension and analyzing it together with the corresponding Kalman filter decoder.Comment: Presented at 59th Allerton Conference on Communication, Control, and Computin

    Wide Bandwidth, Distributed, Digital Teleoperation

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    Teleoperation means to perform a task at a distance. The task is performed by a manipulator located at a remote site, controlled by the master manipulator located in the control room. The loop between the master and the slave manipulator is closed by the human operator. The dexterity and manipulability of the overall system has to be high such that the actions can be easily carried out by the operator. A visual display provides the operator a view of the slave arm and the task environment, kinesthetic feedback provides a sense of physically performing the task. Kinesthetic feedback is direct feedback to the operator, while visual, audio, and other feedback are indirect in nature. The displays generated from the video data are very useful even when the quality of the image is degraded. Changes in the camera position and orientation can cause severe strain on the operator when interpreting the viewed image. The corrections are applied to the position and force transformations to reduce the strain on the operator. The position and force data are communicated over a communication channel from one station to the other. The use of communication channel basically not designed for real time processes can introduce significant delays leading to operator induced instability of the teleoperator system. In the presence of such delays the force reflection as a non-reactive feedback can help in maintaining the stability of the system. The forces encountered by the slave manipulator is transformed into audio range signals. The audio signal to the operator is a reflection of force in a non-reactive manner. Advances in high speed networks with increased bandwidth and decreased error rates provide an opportunity to implement teleoperator systems for long distance and distributed teleoperation. A single operator from a control station can interact physically with a system situated anywhere in the world and perform the tasks as though he or she was present at the remote site. A step by step implementation procedure of a direct teleoperator system with communication between master and slave stations through a computer network is described. The corrections to the transforms to nullify the effect of change in viewing parameters are discussed. The experimental results showing the effectiveness of the change in camera orientations and the comparison of active force reflection to the non-reactive force reflection in the form of auditory signal is presented

    Progressive Source-Channel Coding for Multimedia Transmission over Noisy and Lossy Channels with and without Feedback

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    Rate-scalable or layered lossy source-coding is useful for progressive transmission of multimedia sources, where the receiver can reconstruct the source incrementally. This thesis considers ``joint source-channel'' schemes for such a progressive transmission, in the presence of noise or loss, with and without the use of a feedback link. First we design image communication schemes for memoryless and finite state channels using limited and explicitly constrained use of the feedback channel in the form of a variable incremental redundancy Hybrid ARQ protocol. Constraining feedback allows a direct comparison with schemes without feedback. Optimized feedback based systems are shown to have useful gains. Second, we develop a controlled Markov chain approach for constrained feedback Hybrid ARQ protocol design. The proposed methodology allows the protocol to be chosen from a collection of signal flow graphs, and also allows explicit control over the tradeoffs in throughput, reliability and complexity. Next we consider progressive image transmission in the absence of feedback. We assign unequal error protection to the bits of a rate-scalable source-coder using rate compatible channel codes. We show that, under the framework, the source and channel bits can be ``scheduled'' in a single bitstream in such a way that operational optimality is retained for different transmission budgets, creating a rate-scalable joint source-channel coder. Next we undertake the design of a joint source-channel decoder that uses ``distortion aware'' ACK/NACK feedback generation. For memoryless channels, and Type-I HARQ, the design of optimal ACK/NACK generation and decoding by packet combining is cast and solved as a sequential decision problem. We obtain dynamic programming based optimal solutions and also propose suboptimal, lower complexity distortion-aware decoders and feedback generation rules which outperform conventional BER based rules such as CRC-check. Finally we design operational rate-distortion optimal ACK/NACK feedback generation rules for transmitting a tree structured quantizer over a memoryless channel. We show that the optimal feedback generation rules are embedded, that is, they allow incremental switching to higher rates during the transmission. Also, we obtain the structure of the feedback generation rules in terms of a feedback threshold function that simplifies the implementation

    An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication

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    The attitude regulation of spacecraft using continuous time execution of the control law is not always affordable for the low-cost satellites with limited wireless resources. Of late, within the ambit of control of systems over networks, event-triggered control has proved to be instrumental in ensuring acceptable closed-loop performance while respecting bandwidth constraints of the underlying network. Aligned with these design objectives, a robust event-triggered attitude control algorithm is proposed to regulate the orientation of a flexible spacecraft subjected to parametric uncertainties, external disturbances, and vibrations due to flexible appendages. The control law is developed using a state-dependent single feedback vector, which further assists in obeying the constrained network. The current information of this vector is updated to the onboard controller only when the predefined triggering condition is satisfied. Thus, the control input is updated through communication channel only when there is a need, which ultimately helps in saving the communication resources. The system trajectories, under the proposed approach, are guaranteed to be uniformly ultimately bounded (UUB) in a small neighborhood of origin by using a high gain. Moreover, the practical applicability of the proposed scheme is also proved by showing the Zeno free behavior in the proposed control, i.e., it avoids the accumulation of the triggering sequence. The numerical simulations results are indeed encouraging and illustrate the effectiveness of the designed controller. Moreover, the numerical comparative analysis shows that the proposed approach performs better than periodically sampled data technique and sliding mode-based event-triggered technique.Qatar UniversityScopu

    Information Theory and Cooperative Control in Networked Multi-Agent Systems with Applications to Smart Grid

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    This dissertation focuses on information theoretic aspects of and cooperative control techniques in networked multi-agent systems (NMAS) with communication constraints. In the first part of the dissertation, information theoretic limitations of tracking problems in networked control systems, especially leader-follower systems with communication constraints, are studied. Necessary conditions on the data rate of each communication link for tracking of the leader-follower systems are provided. By considering the forward and feedback channels as one cascade channel, we also provide a lower bound for the data rate of the cascade channel for the system to track a reference signal such that the tracking error has finite second moment. Finally, the aforementioned results are extended to the case in which the leader system and follower system have different system models. In the second part, we propose an easily scalable hierarchical decision-making and control architecture for smart grid with communication constraints in which distributed customers equipped with renewable distributed generation (RDG) interact and trade energy in the grid. We introduce the key components and their interactions in the proposed control architecture and discuss the design of distributed controllers which deal with short-term and long-term grid stability, power load balancing and energy routing. At microgrid level, under the assumption of user cooperation and inter-user communications, we propose a distributed networked control strategy to solve the demand-side management problem in microgrids. Moreover, by considering communication delays between users and microgrid central controller, we propose a distributed networked control strategy with prediction to solve the demand-side management problem with communication delays. In the third part, we consider the disturbance attenuation and stabilization problem in networked control systems. To be specific, we consider the string stability in a large group of interconnected systems over a communication network. Its potential applications could be found in formation tracking control in groups of robots, as well as uncertainty reduction and disturbance attenuation in smart grid. We propose a leader-following consensus protocol for such interconnected systems and derive the sufficient conditions, in terms of communication topology and control parameters, for string stability. Simulation results and performance in terms of disturbance propagation are also given. In the fourth part, we consider distributed tracking and consensus in networked multi-agent systems with noisy time-varying graphs and incomplete data. In particular, a distributed tracking with consensus algorithm is developed for the space-object tracking with a satellite surveillance network. We also intend to investigate the possible application of such methods in smart grid networks. Later, conditions for achieving distributed consensus are discussed and the rate of convergence is quantified for noisy time-varying graphs with incomplete data. We also provide detailed simulation results and performance comparison of the proposed distributed tracking with consensus algorithm in the case of space-object tracking problem and that of distributed local Kalman filtering with centralized fusion and centralized Kalman filter. The information theoretic limitations developed in the first part of this dissertation provide guildlines for design and analysis of tracking problems in networked control systems. The results reveal the mutual interaction and joint application of information theory and control theory in networked control systems. Second, the proposed architectures and approaches enable scalability in smart grid design and allow resource pooling among distributed energy resources (DER) so that the grid stability and optimality is maintained. The proposed distributed networked control strategy with prediction provides an approach for cooperative control at RDG-equipped customers within a self-contained microgrid with different feedback delays. Our string stability analysis in the third part of this dissertation allows a single networked control system to be extended to a large group of interconnected subsystems while system stability is still maintained. It also reveals the disturbance propagation through the network and the effect of disturbance in one subsystem on other subsystems. The proposed leader-following consensus protocol in the constrained communication among users reveals the effect of communication in stabilization of networked control systems and the interaction between communication and control over a network. Finally, the distributed tracking and consensus in networked multi-agent systems problem shows that information sharing among users improves the quality of local estimates and helps avoid conflicting and inefficient distributed decisions. It also reveals the effect of the graph topologies and incomplete node measurements on the speed of achieving distributed decision and final consensus accuracy

    On feedback-based rateless codes for data collection in vehicular networks

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    The ability to transfer data reliably and with low delay over an unreliable service is intrinsic to a number of emerging technologies, including digital video broadcasting, over-the-air software updates, public/private cloud storage, and, recently, wireless vehicular networks. In particular, modern vehicles incorporate tens of sensors to provide vital sensor information to electronic control units (ECUs). In the current architecture, vehicle sensors are connected to ECUs via physical wires, which increase the cost, weight and maintenance effort of the car, especially as the number of electronic components keeps increasing. To mitigate the issues with physical wires, wireless sensor networks (WSN) have been contemplated for replacing the current wires with wireless links, making modern cars cheaper, lighter, and more efficient. However, the ability to reliably communicate with the ECUs is complicated by the dynamic channel properties that the car experiences as it travels through areas with different radio interference patterns, such as urban versus highway driving, or even different road quality, which may physically perturb the wireless sensors. This thesis develops a suite of reliable and efficient communication schemes built upon feedback-based rateless codes, and with a target application of vehicular networks. In particular, we first investigate the feasibility of multi-hop networking for intra-car WSN, and illustrate the potential gains of using the Collection Tree Protocol (CTP), the current state of the art in multi-hop data aggregation. Our results demonstrate, for example, that the packet delivery rate of a node using a single-hop topology protocol can be below 80% in practical scenarios, whereas CTP improves reliability performance beyond 95% across all nodes while simultaneously reducing radio energy consumption. Next, in order to migrate from a wired intra-car network to a wireless system, we consider an intermediate step to deploy a hybrid communication structure, wherein wired and wireless networks coexist. Towards this goal, we design a hybrid link scheduling algorithm that guarantees reliability and robustness under harsh vehicular environments. We further enhance the hybrid link scheduler with the rateless codes such that information leakage to an eavesdropper is almost zero for finite block lengths. In addition to reliability, one key requirement for coded communication schemes is to achieve a fast decoding rate. This feature is vital in a wide spectrum of communication systems, including multimedia and streaming applications (possibly inside vehicles) with real-time playback requirements, and delay-sensitive services, where the receiver needs to recover some data symbols before the recovery of entire frame. To address this issue, we develop feedback-based rateless codes with dynamically-adjusted nonuniform symbol selection distributions. Our simulation results, backed by analysis, show that feedback information paired with a nonuniform distribution significantly improves the decoding rate compared with the state of the art algorithms. We further demonstrate that amount of feedback sent can be tuned to the specific transmission properties of a given feedback channel

    Control-theoretic Approach to Communication with Feedback: Fundamental Limits and Code Design

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    Feedback communication is studied from a control-theoretic perspective, mapping the communication problem to a control problem in which the control signal is received through the same noisy channel as in the communication problem, and the (nonlinear and time-varying) dynamics of the system determine a subclass of encoders available at the transmitter. The MMSE capacity is defined to be the supremum exponential decay rate of the mean square decoding error. This is upper bounded by the information-theoretic feedback capacity, which is the supremum of the achievable rates. A sufficient condition is provided under which the upper bound holds with equality. For the special class of stationary Gaussian channels, a simple application of Bode's integral formula shows that the feedback capacity, recently characterized by Kim, is equal to the maximum instability that can be tolerated by the controller under a given power constraint. Finally, the control mapping is generalized to the N-sender AWGN multiple access channel. It is shown that Kramer's code for this channel, which is known to be sum rate optimal in the class of generalized linear feedback codes, can be obtained by solving a linear quadratic Gaussian control problem.Comment: Submitted to IEEE Transactions on Automatic Contro
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