State-of-the-art in Power Line Communications: from the Applications to the Medium

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201

Magnetic Actuators and Suspension for Space Vibration Control

The research on microgravity vibration isolation performed at the University of Virginia is summarized. This research on microgravity vibration isolation was focused in three areas: (1) the development of new actuators for use in microgravity isolation; (2) the design of controllers for multiple-degree-of-freedom active isolation; and (3) the construction of a single-degree-of-freedom test rig with umbilicals. Described are the design and testing of a large stroke linear actuator; the conceptual design and analysis of a redundant coarse-fine six-degree-of-freedom actuator; an investigation of the control issues of active microgravity isolation; a methodology for the design of multiple-degree-of-freedom isolation control systems using modern control theory; and the design and testing of a single-degree-of-freedom test rig with umbilicals

Identification of the contribution of the ankle and hip joints to multi-segmental balance control

Background\ud \ud Human stance involves multiple segments, including the legs and trunk, and requires coordinated actions of both. A novel method was developed that reliably estimates the contribution of the left and right leg (i.e., the ankle and hip joints) to the balance control of individual subjects. \ud \ud Methods\ud \ud The method was evaluated using simulations of a double-inverted pendulum model and the applicability was demonstrated with an experiment with seven healthy and one Parkinsonian participant. Model simulations indicated that two perturbations are required to reliably estimate the dynamics of a double-inverted pendulum balance control system. In the experiment, two multisine perturbation signals were applied simultaneously. The balance control system dynamic behaviour of the participants was estimated by Frequency Response Functions (FRFs), which relate ankle and hip joint angles to joint torques, using a multivariate closed-loop system identification technique. \ud \ud Results\ud \ud In the model simulations, the FRFs were reliably estimated, also in the presence of realistic levels of noise. In the experiment, the participants responded consistently to the perturbations, indicated by low noise-to-signal ratios of the ankle angle (0.24), hip angle (0.28), ankle torque (0.07), and hip torque (0.33). The developed method could detect that the Parkinson patient controlled his balance asymmetrically, that is, the right ankle and hip joints produced more corrective torque. \ud \ud Conclusion\ud \ud The method allows for a reliable estimate of the multisegmental feedback mechanism that stabilizes stance, of individual participants and of separate leg

Control oriented concentrating solar power (CSP) plant model and its applications

Solar receivers in concentrating solar thermal power plants (CSP) undergo over 10,000 start-ups and shutdowns, and over 25,000 rapid rate of change in temperature on receivers due to cloud transients resulting in performance degradation and material fatigue in their expected lifetime of over 30 years. The research proposes to develop a three-level controller that uses multi-input-multi-output (MIMO) control technology to minimize the effect of these disturbances, improve plant performance, and extend plant life. The controller can be readily installed on any vendor supplied state-of-the-art control hardware.^ We propose a three-level controller architecture using multi-input-multi-output (MIMO) control for CSP plants that can be implemented on existing plants to improve performance, reliability, and extend the life of the plant. This architecture optimizes the performance on multiple time scalesreactive level (regulation to temperature set points), tactical level (adaptation of temperature set points), and strategic level (trading off fatigue life due to thermal cycling and current production). This controller unique to CSP plants operating at temperatures greater than 550°C, will make CSPs competitive with conventional power plants and contribute significantly towards the Sunshot goal of 0.06/kWh(e), while responding with agility to both market dynamics and changes in solar irradiance such as due to passing clouds. Moreover, our development of control software with performance guarantees will avoid early stage failures and permit smooth grid integration of the CSP power plants. The proposed controller can be implemented with existing control hardware infrastructure with little or no additional equipment.^ In the thesis, we demonstrate a dynamics model of CSP, of which different components are modelled with different time scales. We also show a real time control strategy of CSP control oriented model in steady state. Furthermore, we shown different controllers design for disturbance rejection and reference tracking to handle complex receiver dynamics under system disturbance and measurement noise. At last, we show different applications of this control oriented CSP model including life cycle enhancement and electricity load forecasting using both neural network and regression tree

Recursive search-based identification algorithms for the exponential autoregressive time series model with coloured noise

This study focuses on the recursive parameter estimation problems for the non-linear exponential autoregressive model with moving average noise (the ExpARMA model for short). By means of the gradient search, an extended stochastic gradient (ESG) algorithm is derived. Considering the difficulty of determining the step-size in the ESG algorithm, a numerical approach is proposed to obtain the optimal step-size. In order to improve the parameter estimation accuracy, the authors employ the multi-innovation identification theory to develop a multi-innovation ESG (MI-ESG) algorithm for the ExpARMA model. Introducing a forgetting factor into the MI-ESG algorithm, the parameter estimation accuracy can be further improved. With an appropriate innovation length and forgetting factor, the variant of the MI-ESG algorithm is effective to identify all the unknown parameters of the ExpARMA model. A simulation example is provided to test the proposed algorithms

Fault tolerant control for nonlinear aircraft based on feedback linearization

The thesis concerns the fault tolerant flight control (FTFC) problem for nonlinear aircraft by making use of analytical redundancy. Considering initially fault-free flight, the feedback linearization theory plays an important role to provide a baseline control approach for de-coupling and stabilizing a non-linear statically unstable aircraft system. Then several reconfigurable control strategies are studied to provide further robust control performance:- A neural network (NN)-based adaption mechanism is used to develop reconfigurable FTFC performance through the combination of a concurrent updated learninglaw. - The combined feedback linearization and NN adaptor FTFC system is further improved through the use of a sliding mode control (SMC) strategy to enhance the convergence of the NN learning adaptor. - An approach to simultaneous estimation of both state and fault signals is incorporated within an active FTFC system.The faults acting independently on the three primary actuators of the nonlinear aircraft are compensated in the control system.The theoretical ideas developed in the thesis have been applied to the nonlinear Machan Unmanned Aerial Vehicle (UAV) system. The simulation results obtained from a tracking control system demonstrate the improved fault tolerant performance for all the presented control schemes, validated under various faults and disturbance scenarios.A Boeing 747 nonlinear benchmark model, developed within the framework of the GARTEUR FM-AG 16 project “fault tolerant flight control systems”,is used for the purpose of further simulation study and testing of the FTFC scheme developed by making the combined use of concurrent learning NN and SMC theory. The simulation results under the given fault scenario show a promising reconfiguration performance

Loop Interaction Analysis and Control Structure Selection: Application to a Fluid Catalytic Cracking Unit

A simulation approach for the assessment of variables interaction and consequent control structure selection of a fluid catalytic cracking unit (FCCU) is presented in this paper. The simulator which was implemented in Matlab draws from an earlier mathematical model of the FCCU, was used as a virtual FCCU for studying the dynamic response of the riser temperature (Trx), the regenerator temperature (Trg) and the regenerator flue gas oxygen concentration (Od) to step changes in air flow rate (Fa), regenerated catalyst flow rate (Frc), gas oil feed rate (Fgr). The results show strong interaction in FCCU variables, with Fa affecting Trg and Od; Frc affecting Trx, Trg and Od; Fgr affecting Trx, Trg and Od. A linearised state-space model based on the first-principle model was deduced and transformed to a 3x3 input-output model. Three channel interaction measures: Relative Gain Array (RGA), Effective Relative Gain Array (ERGA) and the Normalized Relative Gain Array (RNGA) were applied to the selection of FCCU control structure. All the measures point to a diagonal scheme with the following pairings: (Trx/Fgr), (Trg/Fa) and (Od/Frc) ,for the decentralized control of the riser temperature, the regenerator temperature and the flue gas oxygen concentration respectively. The suggested control structure offers a high promise of stability, with a Niederlinski index (NI) of 101.79. DOI: 10.7176/CTI/8-0

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version