비만아 부모의 돌봄 경험: q 방법론

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their performances and efficiencies in recent decades. EVs have already been widely accepted in the automotive industries considering the most promising replacements in reducing CO2 emissions and global environmental issues. Lithium-ion batteries have attained huge attention in EVs application due to their lucrative features such as lightweight, fast charging, high energy density, low self-discharge and long lifespan. This paper comprehensively reviews the lithium-ion battery state of charge (SOC) estimation and its management system towards the sustainable future EV applications. The significance of battery management system (BMS) employing lithium-ion batteries is presented, which can guarantee a reliable and safe operation and assess the battery SOC. The review identifies that the SOC is a crucial parameter as it signifies the remaining available energy in a battery that provides an idea about charging/discharging strategies and protect the battery from overcharging/over discharging. It is also observed that the SOC of the existing lithium-ion batteries have a good contribution to run the EVs safely and efficiently with their charging/discharging capabilities. However, they still have some challenges due to their complex electro-chemical reactions, performance degradation and lack of accuracy towards the enhancement of battery performance and life. The classification of the estimation methodologies to estimate SOC focusing with the estimation model/algorithm, benefits, drawbacks and estimation error are extensively reviewed. The review highlights many factors and challenges with possible recommendations for the development of BMS and estimation of SOC in next-generation EV applications. All the highlighted insights of this review will widen the increasing efforts towards the development of the advanced SOC estimation method and energy management system of lithium-ion battery for the future high-tech EV applications.

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

This paper develops a sliding-mode control (SMC) approach for systems with mismatched uncertainties via a nonlinear disturbance observer (DOB). By designing a novel sliding surface based on the disturbance estimation, a DOB-based SMC method is developed in this paper to counteract the mismatched disturbance. The newly proposed method exhibits the following two attractive features. First, the switching gain is only required to be designed greater than the bound of the disturbance estimation error rather than that of the disturbance; thus, the chattering problem is substantially alleviated. Second, the proposed method retains its nominal performance, which means the proposed method acts the same as the baseline sliding-mode controller in the absence of uncertainties. Simulation results of both the numerical and application examples show that the proposed method exhibits much better control performance than the baseline SMC and the integral SMC (I-SMC) methods, such as reduced chattering and nominal performance recovery.

Sliding-Mode Control for Systems With Mismatched Uncertainties via a Disturbance Observer

The article presents results for distributed model predictive control (MPC), focusing on i) the coordination of the optimization computations using iterative exchange of information and ii) the stability of the closed-loop system when information is exchanged only after each iteration. Current research is focusing on general methods for decomposing large-scale problems for distributed MPC and methods for guaranteeing stability when multiple agents are controlling systems subject to abrupt changes.

Distributed model predictive control

https://www.cs.ucf.edu/~yguo/paper/guoy_automatica.pdf

Nonlinear decentralized control of large-scale power systems

Robust decentralized nonlinear controller design for multimachine power systems

Summary form only given as follows. This paper is concerned with the global control of power systems. It arises from the practical concern that transient stability and voltage regulation are both important properties of power system control, but they are ascribed to different model descriptions and relate to different stages of system operation (i.e. transient period and post-transient period respectively). Earlier control results deal with the two problems separately, or employ a switching strategy of two different kinds of controllers, which causes a discontinuity of system behavior. We design in this paper a global controller to co-ordinate the transient stabilizer and voltage regulator. The designed controller is smooth and robust with respect to different transient faults. Simulations on a single-machine infinite bus power system have demonstrated better performances compared with existing controllers.

Global Transient Stability and Voltage Regulation for Power Systems

In this paper, we investigate the problem of stabilization for sampled-data fuzzy systems under variable sampling. A novel Lyapunov-Krasovskii functional (LKF) is defined to capture the characteristic of sampled-data systems, and an improved input delay approach is proposed. By the use of an appropriate enlargement scheme, new stability and stabilization criteria are obtained in terms of linear matrix inequalities (LMIs). Compared with the existing results, the newly obtained ones contain less conservatism. Some illustrative examples are given to show the effectiveness of the proposed method and the significant improvement on the existing results.

An Improved Input Delay Approach to Stabilization of Fuzzy Systems Under Variable Sampling

In this paper, a robust decentralized nonlinear control scheme is proposed for multimachine power system stability enhancement. The nonlinear controller consists of a novel dynamic direct feedback linearization (DFL) compensator through the excitation loop to cancel the nonlinearities and interactions among generators and a robust feedback controller to guarantee the asymptotic stability of the DFL compensated system considering the effects of dynamic output feedback and plant parametric uncertainties. The decentralized controller for each generator in the multimachine system is obtained by solving an algebraic Riccati equation. The nonlinear controller can guarantee the stability of the multimachine nonlinear power system within a whole operating region for all admissible parameters. The design procedure is tested on a three-machine power system. Simulation results show that the proposed control scheme can greatly enhance the stability of the system, regardless of the network parameters, operating points, and fault locations.

Youyi Wang

Papers

Nonlinear decentralized control of large-scale power systems

Robust decentralized nonlinear controller design for multimachine power systems

Global Transient Stability and Voltage Regulation for Power Systems

An Improved Input Delay Approach to Stabilization of Fuzzy Systems Under Variable Sampling

Nonlinear output stabilization control for multimachine power systems