Abdulla Ismail

Robust filtering for jumping systems with mode-dependent delays

In this paper, the filtering problem for a class of linear uncertain systems with Markovian jump parameters and functional time delay is examined. The uncertainties are time-varying and norm-bounded parametric uncertainties and the delay factor depends on the mode of operation. We provide complete results for robust weak-dependent stochastic stability and robust linear filter design. Then we extend the theoretical development to the case when a prescribed performance measure is desired. All the results are cast into convenient linear matrix inequality (LMI) forms.

New results on delay-dependent control of time-delay systems

This note presents new results pertaining to the delay-dependent stability and control design of a class of linear time-delay systems. A new state transformation is introduced to exhibit the delay-dependent dynamics. For stability, we construct an appropriate Lyapunov functional to derive delay-dependent linear matrix inequality-based sufficient condition. For the feedback control design, we establish schemes based on quadratic H/sub 2/ performance, H/sub /spl infin//, criteria and simultaneous H/sub 2//H/sub /spl infin// synthesis. Under the developed transformation, both the instantaneous and delayed feedback control yield identical results. Numerical examples are presented to illustrate the analytical development.

Improved results on robust exponential stability criteria for neutral-type delayed neural networks

Abstract In this paper, we investigate the problem of robust global exponential stability analysis for a class of neutral-type neural networks. The interval time-varying delays allow for both slow and fast time-varying delays. The values of the time-varying uncertain parameters are assumed to be bounded within given compact sets. Improved global exponential stability condition is derived by employing new Lyapunov–Krasovskii functional and the integral inequality. The developed nominal and robust stability criteria is delay-dependent and characterized by linear-matrix inequalities (LMIs). The developed results are less conservative than previous published ones in the literature, which are illustrated by representative numerical examples.

Role of delays in networked control systems

The purpose of this paper is to provide a complete diagnostic profile of the role of delays in networked control systems (NCS). It analyzes the impact of delay sources on the stability and performance of NCS. With focus on the network induced delay, it is shown that the relationship between the sampling rate and the network induced delay can only be determined by simulation. An upper bound on the network delays using dynamic controllers is developed in terms of an LMI-feasibility problem that can be readily solved using semi-definite programming tools.

Resilient control of non-linear discrete-time state-delay systems

A class of non-linear discrete-time systems with state-delay is considered. We develop an LMI-based analysis and design procedures to check primarily into the robust stability of discrete-time systems with state-delay and bounded non-linearities. Then we address the robust stabilization using nominal and resilient feedback designs. In both cases the trade-off between the size of the controller gains and the bounding factors is illuminated and incorporated into the design formalism. Seeking computational convenience, all the developed results are cast in the format of linear matrix inequalities (LMIs) and several numerical examples are presented throughout the paper to illustrate the feasibility of the theoretical developments.

Fuzzy model reference learning control of multi-stage flash desalination plants

The large scale process control of highly complex desalination plants has been largely dealt with conventional proportional-integral-derivative (PID) controllers. Although these conventional techniques may provide a minimum performance requirement, they fall short of the increasing control performance demand of robustness, optimality and adaptation to external disturbances. However, in the last few years, new emerging intelligent control techniques have been gaining acceptance for their attractive design and implementation advantages. These new control methods provides solutions for problems where no mathematical model of the system may exit and where uncertainties in the operating environment are significant. Among the widely spread desalination plants in need of efficient and reliable control mechanism are the distillation-based multi-stage flash (MSF). These complex non-linear systems with inter-coupled control loops have not been studied satisfactorily for their efficient performance during different operating conditions and under changing loads. While fuzzy control can provide effective practical solutions to complex industrial problems, as an alternative to conventional control methods, there are several drawbacks that may limit its use for some problems. One main drawback being the inability of the fuzzy controller, designed for the nominal plant, to perform adequately if significant and unpredictable plant variations may occur. Introducing the capability of a progressively learning mechanism into the system, along with basic ideas of fuzzy sets and control theory, will improve the performance of the overall controlled system when interacting with the environment. The fuzzy reference learning controller (FMRLC) utilises a learning mechanism which observes the plant outputs and adjusts accordingly the rules in a direct fuzzy controller such that the overall system performs satisfactorily. In this paper we would discuss the advantages of using FMRLC in controlling the top brine temperature (TBT) of the brine heater in an 18th stage MSF desalination plant. Comparisons with classical as well as direct fuzzy control of the same plant are investigated. Furthermore, some practical implementation issues of the proposed controller are discussed.

Control of multi-stage flash desalination plants: A survey

Abstract Scarcity of water resources along with population increase, industrialization, and agricultural expansion, in many regions of the world mandates the use of modern technology to supply the increasing demands for potable water. Multi-stage flash (MSF) desalination, a distillation process of removing dissolved minerals from seawater or brackish water, is well known for its large scale potable water production and it has been in existence since the early fiftieth. Among the different desalination methods used in industry, MSF plants account for over 70% of the total world installations. This necessitates the utilization of modern computer controlled automation in the design and operation of these expensive plants. Due to the complexity and large scale nature of these plants, improving their reliability of operation under continuous and heavy loads and their efficiency compared to other well known processes have bot been studied thoroughly. However, there have been some simple preliminary efforts based on limited static simulation cases. Recently, some rigorous control and automation applications of MSF plants have been treated in the literature which showed some promising results in the cultivation of modern control techniques to the problem. In this paper, a comprehensive survey is conducted on the efforts made in applying automation and control techniques to MSF Desalination processes and plants. The survey includes well established classical control methods as well as modern more promising ones. Furthermore, some proposed new intelligent control approaches are outlined and their benefits are illustrated.

A photovoltaic utilization system with bang-bang self-adjusting maximum energy tracking controller

The paper presents an error driven controller for maximum energy utilization of photovoltaic PV renewable energy interface schemes. The error driven comprises of regulation loops ensuring on-line dynamic tracking of the maximum power point under different variations in solar insulation levels or sudden mechanical load excursions. The bang–bang regulator limiter block is self-adjusting as it is driven by the error excursion vector magnitude. This ensures that the control signal is modulated in magnitude by the distance of error deviation in the error hyper plane. The paper details a digital simulation MATLAB/SIMULINK model of a PV−PMDC motor utilization system driving a ventilation, pumping or air-conditioning mechanical load.

Robust load frequency control

A technique for the control of frequency deviation in interconnected power systems is introduced. The technique is based on the application of linear feedback H-infinity robust controllers in the power system model. The controller response should be fast enough to offset the frequency errors due to load variations. Simulation results show the superior performance of the proposed controllers compared with other classical as well as LQR controllers.<<ETX>>

Field oriented motion control of a 3-phase permanent magnet synchronous motor

The recent extensive application of permanent magnet synchronous motors (PMSM) in industry has been stimulated by the worldwide energy-saving mission. In this study, the assessment of the dynamic performance of a traditional cascaded PI field oriented motion control of a PMSM drive system is presented in both simulation and a real time implementation of the control strategy. The tuning of the cascaded position, velocity, and current controllers was carried out experimentally and the results demonstrated the feasibility and effectiveness of the used control scheme for velocity and position loops. Finally, the motion command tracking performance of the cascaded PI field oriented control algorithm of SMPM system was found satisfactory.