By Topic

Control Systems, IEEE

Issue 4 • Date Aug. 2002

Filter Results

Displaying Results 1 - 9 of 9
  • 2002 IEEE Fellows

    Publication Year: 2002 , Page(s): 81 - 89
    Save to Project icon | Request Permissions | PDF file iconPDF (637 KB)  
    Freely Available from IEEE
  • A short history of hydropower control

    Publication Year: 2002 , Page(s): 68 - 76
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1097 KB) |  | HTML iconHTML  

    Today's control systems have their roots, to a great extent, in the speed control of driving engines (prime movers) and particularly in the speed control of water turbines. The first turbines with automatic speed control appeared sometime in the mid-19th century. I discuss the history of water-turbine control systems, noting the older inventions and techniques that made possible the very first attempts to control the speed of hydraulic machinery and recognizing the key engineers and scientists who contributed to the further development. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • My Berkeley years: Control at Cal, 1955-1961

    Publication Year: 2002 , Page(s): 77 - 80
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB) |  | HTML iconHTML  

    The author was an undergraduate and graduate student at the University of California at Berkeley (Cal for short) during the initial period of the modern control theory revolution. In this paper he recounts some of the events that took place at Cal during that time and reminisce about his teachers and colleagues in the early days of optimal control theory. He attempts to interlace his personal experiences with the educational, research, and social atmosphere at Cal, so as to present a "readable tale". View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • What makes some control problems hard?

    Publication Year: 2002 , Page(s): 8 - 19
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (842 KB) |  | HTML iconHTML  

    The goal of this article is to suggest a framework for viewing control applications that will help the control practitioner understand and articulate the nature of the engineering challenge. The author hopes that this framework will provide a useful guide to approaching new control applications while increasing the chances of success. He explores the question in five phases: control strategy, control physics, control architecture, control hardware, and control tuning. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A linear matrix inequality approach for the control of uncertain fuzzy systems

    Publication Year: 2002 , Page(s): 20 - 25
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    This article proposes a linear controller to tackle nonlinear plants represented by a fuzzy plant model whose membership functions depend on some unknown parameters of the nonlinear plant. The unknown parameters are within known bounds. The stability of the closed-loop system is analyzed based on the Lyapunov stability theory. We show that the stability condition derived is the same as that of the relaxed stability condition given by Wang et al. (1996), in which the fuzzy controller depends on membership functions of the fuzzy plant model. However, the structure of the proposed linear controller is much simpler than that of the nonlinear fuzzy controller. The derived stability condition is formulated into a linear matrix inequality (LMI) problem. By solving the LMIs, the parameters of the linear controller can be obtained. The LMIs can be solved readily by using software tools such as MATLAB. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Constrained predictive control in continuous time

    Publication Year: 2002 , Page(s): 57 - 67
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (623 KB) |  | HTML iconHTML  

    In this study, the constrained generalised predictive control method is applied in an adaptive form, that is , the system parameters are estimated first and then the control input is calculated based on the estimated system model at each sampling instant. The well known continuous time least squares estimator is used to retain the continuous time nature of the algorithm. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Frequency selective feedback for active noise control

    Publication Year: 2002 , Page(s): 32 - 41
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1277 KB) |  | HTML iconHTML  

    Active noise control has moved from the laboratory to industrial applications. This article presents a frequency-selective, filter-based adaptive feedback solution in the frequency domain for periodic noise attenuation. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cell-state-space-based search

    Publication Year: 2002 , Page(s): 42 - 56
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1110 KB) |  | HTML iconHTML  

    The cell-state-space concept is a promising computational method for designing, evaluating, training, adapting, and tuning digital control systems. Over the last decade, we have continually improved and refined some of these cell-state-space methods. This effort has culminated in an automated controller optimization algorithm called incremental best estimate directed search (IBEDS). IBEDS starts from an initial training set obtained through the sampling of the control surface of a controller with poor performance. IBEDS is based on the assumption that if the training data set is optimized, the fuzzy logic controller trained therefrom will also be optimized. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Convoluted double trouble

    Publication Year: 2002 , Page(s): 26 - 31
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (329 KB) |  | HTML iconHTML  

    The analysis of explicit conditions for the existence and uniqueness of closed-loop solutions for double-sided time axis setups in the presence of unstable convolution models has remained an elusive problem for several decades. For our purposes, we consider the strictly causal, noise-corrupted, discrete time first order convolution system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IEEE Control Systems Magazine is the largest circulation technical periodical worldwide devoted to all aspects of control systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Jonathan P. How
jhow@mit.edu