H∞ dynamic output feedback control of power systems with electric vehicles

This paper presents a H∞ dynamic output feedback control scheme for load frequency control (LFC) of interconnected power systems with multiple input timedelays. In this study, electric vehicles (EVs) are participated in the LFC to support reheated thermal power units to rapidly suppress load and frequency fluctuations. A mathematical model of an interconnected power system is first introduced. This model takes into consideration of the different time delays in control inputs; specifically the communication/information delays between the control center and the fleet of EVs. We then derive stabilization conditions in terms of feasible linear matrix inequalities (LMIs) for the proposed system and develop an effective algorithm to parameterize H∞ controllers ensuring stability of the closed-loop system with H∞ performance. Extensive simulations are given to show the effectiveness of the proposed control method.

A diamond-based electrode for detection of neurochemicals in the human brain

Deep brain stimulation (DBS), a surgical technique to treat certain neurologic and psychiatric conditions, relies on pre-determined stimulation parameters in an open-loop configuration. The major advancement in DBS devices is a closed-loop system that uses neurophysiologic feedback to dynamically adjust stimulation frequency and amplitude. Stimulation-driven neurochemical release can be measured by fast-scan cyclic voltammetry (FSCV), but existing FSCV electrodes rely on carbon fiber, which degrades quickly during use and is therefore unsuitable for chronic neurochemical recording. To address this issue, we developed durable, synthetic boron-doped diamond-based electrodes capable of measuring neurochemical release in humans. Compared to carbon fiber electrodes, they were more than two orders-of-magnitude more physically-robust and demonstrated longevity in vitro without deterioration. Applied for the first time in humans, diamond electrode recordings from thalamic targets in patients (n = 4) undergoing DBS for tremor produced signals consistent with adenosine release at a sensitivity comparable to carbon fiber electrodes. (Clinical trials # NCT01705301).

The role of serious games in robot exoskeleton-assisted rehabilitation of stroke patients

his chapter describes how serious games can be used to improve the rehabilitation of stroke patients. Determining ideal training conditions for rehabilitation is difficult, as no objective measures exist and the psychological state of patients during therapy is often neglected. What is missing is a way to vary the difficulty of the tasks during a therapy session in response to the patient needs, in order to adapt the training specifically to the individual. In this chapter, we describe such a method. A serious game is used to present challenges to the patient, including motor and cognitive tasks. The psychological state of the patient is inferred from measures computed from heart rate variability (HRV) as well as breathing frequency, skin conductance response, and skin temperature. Once the psychological state of the patient can be determined from these measures, it is possible to vary the tasks in real time by adjusting parameters of the game. The serious game aspect of the training allows the virtual environment to become adaptive in real time, leading to improved matching of the activity to the needs of the patient. This is likely to lead to improved training outcomes and has the potential to lead to faster and more complete recovery, as it enables training that is challenging yet does not overstress the patient.

Integration of electric vehicles for load frequency output feedback H ∞ control of smart grids

This study considers a novel application of electric vehicles (EVs) to quickly help reheated thermal turbine units to provide the stability fluctuated by load demands. A mathematical model of a power system with EVs is first derived. This model contains the dynamic interactions of EVs and multiple network-induced time delays. Then, a dynamic output feedback H∞ controller for load frequency control of power systems with multiple time delays in the control input is proposed. To address the multiple time delays issue, a refined Jensen-based inequality, which encompasses the Jensen inequality, is used to derive less conservative synthesis conditions in terms of tractable linear matrix inequalities. A procedure is given to parameterise an output feedback controller to guarantee stability and H∞ performance of the closed-loop system. Extensive simulations are conducted to validate the proposed control method.

Exponential stabilization of non-autonomous delayed neural networks via Riccati equations

This paper concerns with the problem of exponential stabilization for a class of non-autonomous neural networks with mixed discrete and distributed time-varying delays. Two cases of discrete time-varying delay, namely (i) slowly time-varying; and (ii) fast time-varying, are considered. By constructing an appropriate Lyapunov-Krasovskii functional in case (i) and utilizing the Razumikhin technique in case (ii), we establish some new delay-dependent conditions for designing a memoryless state feedback controller which stabilizes the system with an exponential convergence of the resulting closed-loop system. The proposed conditions are derived through solutions of some types of Riccati differential equations. Applications to control a class of autonomous neural networks with mixed time-varying delays are also discussed in this paper. Some numerical examples are provided to illustrate the effectiveness of the obtained results.

Static output feedback frequency stabilization of time-delay power systems with coordinated electric vehicles state of charge control

In this paper, for the first time, electric vehicles are used for both the primary and secondary frequency controls to support power plants to rapidly suppress fluctuations in the system frequency due to load disturbances. Via networked control and wide-area communication infrastructures, multiple interval time-varying delays exist in the communication channels between the control center, power plant, and an aggregation of electric vehicles. By coordinating batteries’ state of charge control, the behaviors of the vehicle owners and the uncertainties imposed by the changes of the batteries’ state of charge are taken intoconsideration. A power system model incorporating multiple time-varying delays and uncertainties is first proposed. Then, a robust static output feedback frequency controller is designed to guarantee the resulting closed-loop system stable with an H∞ attenuation level. By utilizing a novel integral inequality, namely refined-Jensen inequality, and an improved reciprocally convex combination, the design conditions are formulated in terms of tractable linear matrix inequalities which can be efficiently solved by various computational tools. The effectiveness of the proposed control scheme is verified by extensive simulations.

A game-theoretic resource allocation approach for intercell device-to-device communications in cellular networks

Device-to-Device (D2D) communication is a recently emerged disruptive technology for enhancing the performance of current cellular systems. To successfully implement D2D communications underlaying cellular networks, resource allocation to D2D links is a critical issue, which is far from trivial due to the mutual interference between D2D users and cellular users. Most of the existing resource allocation research for D2D communications has primarily focused on the intracell scenario while leaving the intercell settings not considered. In this paper, we investigate the resource allocation issue for intercell scenarios where a D2D link is located in the overlapping area of two neighboring cells. Specifically, We present three intercell D2D scenarios regarding the resource allocation problem. To address the problem, we develop a repeated game model under these scenarios. Distinct from existing works, we characterize the communication infrastructure, namely Base Stations (BSs), as players competing resource allocation quota from D2D demand, and we define the utility of each player as the payoff from both cellular and D2D communications using radio resources. We also propose a resource allocation algorithm and protocol based on the Nash equilibrium derivations. Numerical results indicate that the developed model not only significantly enhances the system performance including sum rate and sum rate gain, but also sheds lights on resource configurations for intercell D2D scenarios.

Nash Demand Game and the Kalai-Smorodinsky Solution

We introduce two new variations on the Nash demand game. One, like all known Nash-like demand games so far, has the Nash solution outcome as its equilibrium outcome. In the other, the range of solutions depends on an exogenous breakdown probability; surprisingly, the Kalai-Smorodinsky outcome proves to be the most robust equilibrium outcome. While the Kalai- Smorodinsky solution always finishes on top, there is no possible general ranking among the remaining solution concepts considered; in fact, the rest of the solution concepts take their turns at the bottom at various bargaining problems, depending on the specifics of the bargaining setup.