S. M. Mahdi Alavi

Robust active queue management design: A loop-shaping approach

In this paper, a novel systematic design procedure is presented for robust active queue management (AQM). The congestion control law is obtained through an interactive loop-shaping process that manipulates the system frequency response to meet robust stability and performance requirements in the presence of uncertain network conditions. A sufficient condition leading to a satisfactory level of robust performance against high-frequency parasitics that naturally affect the desired requirements is then derived. A feature of the technique is that the uncertain phase information and round-trip time-delay that are inherent to the system dynamics are fully addressed in the design equations, resulting in minimal conservatism and/or over-design. Simulation results using the ns2 simulator are provided to illustrate the effectiveness of the proposed method.

Online state and parameter estimation of the Li-ion battery in a Bayesian framework

Due to an ever-growing role of lithium-ion batteries in industry, particularly automotive industry, an effective battery management system (BMS) is of critical importance. A reliable battery state estimation scheme is an integral part of such a BMS. Complicated nature of battery dynamics, weak observability, lack of knowledge about the degradation mechanisms of these batteries, etc has made their state estimation a challenging task. Among the published works on Li-ion battery estimation, a subject that has not received a great deal of attention is parameter estimation of the battery. Parameter estimation has a direct impact on both state of charge and state of health estimation of the battery. Most of the works in the field of battery estimation are built upon the known parameters of the battery whereas in reality these parameters change over-time and may not be known a priori, particularly for aged batteries. This work tackles the problem of parameter and state estimation of lithium-ion batteries from a model-based perspective using a multi-rate particle filter. This filter is applicable to the full-electrochemical of the battery without any restrictive assumption or simplification of the model equations. The filter is proposed in a multi-rate structure in order to address the run-time of the process and computational load of the algorithm. The simulation studies demonstrate the effectiveness of the proposed algorithm.

Diagnostics in Lithium-Ion Batteries: Challenging Issues and Recent Achievements

This paper highlights some of the issues which have made diagnostics of Lithiumion (Li-ion) battery energy storage systems very challenging from the both chemical and control engineering perspectives. The application of standard observers, Kalman, and particle filters in state estimation of Li-ion batteries are fully reviewed. Recent achievements in this field, pros and cons of various approaches, and future direction for research are outlined.

Pre-Filter Design for Tracking Error Specifications in MIMO-QFT

This paper presents a novel approach to solve the MIMO-QFT problem for tracking error specification through a method of obtaining exact bounds for the design of individual elements of pre-filter. The paper specifically deals with the appropriate transformation of the MIMO system to the equivalent SISO problems, which allows easy design to find the feedback compensator and pre-filter. A linearized model of quadruple-tank process is used to show the effectiveness of the proposed method.

Accurate state estimation in DC-DC converters using a Proportional-Integral Observer (PIO)

This paper focuses on state estimation of DC-DC converters in the presences of a biased duty-cycle which is very common in practice. It is shown that the commonly used Proportional (P-) observer fails to estimate the state of the converter when an unknown biased duty-cycle is present. To address this issue, a Proportional-Integral (PI-) observer is proposed, and its design is formulated as a H∞/L2 problem. A sufficient condition is derived by using the Lyapunov stability theorem and linear-matrix-inequality (LMI) design tool, guaranteeing the convergence of the observers estimation error. The effectiveness and robustness of the proposed technique is verified and is compared with the P-observer observer through an experimental test on a step-down buck converter.

A decentralized technique for robust simultaneous fault detection and control of uncertain systems

A novel practically implementable methodology is proposed for design of closed-loop systems in order to achieve a satisfactory level of Simultaneous Fault Detection and Control (SFDC) specifications. The desired feedback law is obtained through a loop-shaping technique which is worthwhile for making a trade-off between fault detection and control objectives. The proposed SFDC strategy is experimentally applied to the Three-Tank, Amira DTS200, benchmark system and the results are discussed.

Inversion-free decentralised quantitative feedback design of large-scale systems

In this paper, a new method for robust decentralised control of multi-input multi-output (MIMO) systems using quantitative feedback theory (QFT) is suggested. The proposed method does not need inversion of the plant transfer function matrix in the design process. For a given system, an equivalent descriptor system representation is defined. By using this representation, sufficient conditions for closed-loop diagonal dominance over the uncertainty space are obtained. These conditions transform the original MIMO system into a set of isolated multi-input single-output (MISO) subsystems. Then, the local controllers are designed by using the typical MISO QFT technique for each isolated subsystem to satisfy the predefined desired specifications and the closed-loop diagonal dominance sufficient conditions. The proposed technique is less conservative in comparison to the approaches using the over-bounding concept in the design procedure. The effectiveness of the proposed technique is finally assessed on a MIMO Scara robot.

Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems

This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.

Estimation of Lithium Transport Rate in Lithium-ion Batteries - A Particle Filtering Approach

Abstract Measurement of Lithium (Li) transport plays an important role in a general study of degradation mechanisms, and significantly simplifies diagnostics in Lithium-ion (Li-ion) batteries. This paper presents a particle-filter based approach for an estimation of Li transport in Li-ion batteries, by using an electrochemical model. Simulation results are provided to show the effectiveness of the proposed estimation technique.

Networked fault detection of nonlinear systems

This paper addresses Fault Detection (FD) problem of a class of nonlinear systems which are monitored via the communications networks. A sufficient condition is derived which guarantees exponential mean-square stability of the proposed nonlinear NFD systems in the presence of packet drop, quantization error and unwanted exogenous inputs such as disturbance and noise. A Linear Matrix Inequality (LMI) is obtained for the design of the fault detection filter parameters. Finally, the effectiveness of the proposed NFD technique is extensively assessed by using an experimental testbed that has been built for performance evaluation of such systems with the use of IEEE 802.15.4 Wireless Sensor Networks (WSNs) technology. An algorithm is presented to handle floating point calculus when connecting the WSNs to the engineering design softwares such as Matlab.