There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

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A Survey of Recent Results in Networked Control Systems

1. Introduction. 2. Linear Algebra. 3. Linear Systems. 4. H2 and Ha Spaces. 5. Internal Stability. 6. Performance Specifications and Limitations. 7. Balanced Model Reduction. 8. Uncertainty and Robustness. 9. Linear Fractional Transformation. 10. m and m- Synthesis. 11. Controller Parameterization. 12. Algebraic Riccati Equations. 13. H2 Optimal Control. 14. Ha Control. 15. Controller Reduction. 16. Ha Loop Shaping. 17. Gap Metric and ...u- Gap Metric. 18. Miscellaneous Topics. Bibliography. Index.

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Essentials of Robust Control

This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material. The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the engineering properties of the regulator. Topics include degree of stability, phase and gain margin, tolerance of time delay, effect of nonlinearities, asymptotic properties, and various sensitivity problems. The third section explores state estimation and robust controller design using state-estimate feedback. Numerous examples emphasize the issues related to consistent and accurate system design. Key topics include loop-recovery techniques, frequency shaping, and controller reduction, for both scalar and multivariable systems. Self-contained appendixes cover matrix theory, linear systems, the Pontryagin minimum principle, Lyapunov stability, and the Riccati equation. Newly added to this Dover edition is a complete solutions manual for the problems appearing at the conclusion of each section.

Optimal Control: Linear Quadratic Methods

https://www.control.utoronto.ca/people/profs/francis/dft.pdf

Feedback Control Theory

A modular controller structure for automotive powertrains has certain benefits. These include improved productivity through module reuse, seamless integration of new features, transparent removal of obsolete features, and module sharing across powertrain platforms. Modular architecture also potentially reduces the complexity in the design and calibration process, in that controller modules for different subsystems are developed independently. Due to the fact that the automotive powertrain system contains many highly interactive sub-systems, it is not clear that a modular controller development process can yield acceptable feedback controller performance with respect to emissions, fuel economy, and drivability. In this paper, we describe the engineering design issues associated with a decentralized development process, and the impact that the resulting decentralized controller has upon the dynamic response of the feedback system. We describe the possible detrimental consequences of subsystem interaction, and the potential of coordinated, multivariable feedback for alleviating these limitations. Control of a spark ignition engine incorporating variable camshaft timing is used as a case study.

Consequences of modular controller development for automotive powertrains: a case study

Feedforward A/F control in turbocharged gasoline engines with variable valve timing requires knowledge of exhaust manifold pressure, Pe . Physical conditions in the manifold make measurement costly, compelling manufacturers to implement some form of on-line estimation. Processor limitations and the calibration process, however, put constraints on estimator complexity. This paper assesses the feasibility of estimating Pe with an algorithm that is computationally efficient and relatively simple to calibrate. A traditional reduced order linear observer is found to perform well but has too many calibration parameters for practical implementation. Using the performance of the observer as a benchmark, static estimation is explored by parameterizing the equilibrium values of Pe with both the inputs and the outputs of the system. This nonlinear static estimate, combined with simple lead compensation, yields a practical observer implementation.Copyright © 2008 by ASME

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Estimation of Exhaust Manifold Pressure in Turbocharged Gasoline Engines With Variable Valve Timing

The extension of loop transfer recovery (LTR) design technique to non-minimum phase (NMP) systems has been studied. Explicit expressions are given for the asymptotic behavior of the sensitivity function resulting from application of the LTR procedure to NMP plants. It is observed that the limitations imposed by the NMP zeros upon feedback properties manifest themselves as a tradeoff between the feedback properties of the state feedback loop and our ability to recover those properties using the LTR procedure.

Loop transfer recovery with non-minimum phase zeros

This paper expresses limitations imposed by non-minimum phase zeros of the open loop system directly in terms of the sensitivity function of the closed loop system. The limitations are determined by integral relationships which must be satisfied by the sensitivity function. The integral relationships are interpreted in the context of feedback design.

Sensitivity reduction, nonminimum phase zeros, and design tradeoffs in single loop feedback systems

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James S. Freudenberg

Papers

Consequences of modular controller development for automotive powertrains: a case study

Estimation of Exhaust Manifold Pressure in Turbocharged Gasoline Engines With Variable Valve Timing

Loop transfer recovery with non-minimum phase zeros

Sensitivity reduction, nonminimum phase zeros, and design tradeoffs in single loop feedback systems

A fundamental tradeoff between performance and sensitivity within haptic rendering