By George M. Siouris
A much-awaited consultant to real-world difficulties in smooth keep watch over and estimation
This mixed textual content and reference bargains with the layout of recent keep an eye on platforms. it's the first e-book during this speedily turning out to be box to strategy optimum keep watch over and optimum estimation from a strictly pragmatic viewpoint. Sidestepping the world of theoretical arithmetic, An Engineering method of optimum keep watch over and Estimation concept bargains sensible and attainable suggestions that may be positioned to rapid use via electric and mechanical engineers in aerospace and in lots of different applications.
The writer attracts on his vast adventure in learn and improvement from undefined, govt, and academia to give systematic, obtainable insurance of all very important themes, together with:
* All easy arithmetic had to follow next details
* A old standpoint at the evolution of recent regulate and estimation idea
* All significant innovations appropriate to the layout of recent keep watch over systems--from the Kalman clear out, to linear regulators, to decentralized Kalman filters
* useful examples helpful in employing the foundations lower than dialogue
* difficulties on the finish of every bankruptcy
* rigorously chosen references from the massive variety of books released in this topic
* Appendixes reviewing matrix algebra that's vital to fashionable keep watch over concept, in addition to matrix subroutines, precious to either scholars and training engineers
Optimal keep watch over and Estimation Theory
Optimal regulate and optimum estimation have visible super progress during the last 3 many years, because of significant advances in aerospace and different different types of engineering. optimum keep watch over and estimation idea is important to the layout of contemporary keep an eye on platforms; for example, navigation, cellular robotics, or automatic autos and plane. It guarantees that variables reminiscent of temperatures or strain are saved in payment, whatever the disturbance the method undergoes.
Despite the proliferation of books at the topic, lots of the fabric released during this region is very theoretical, and ways the topic in a "theorem-proof" style, that is extra applicable to arithmetic than to an engineering textual content. As its identify indicates, An Engineering method of optimum keep watch over and Estimation concept offers a pragmatic and available consultant, targeting purposes and implementation, and answering real-world questions confronted via keep watch over engineers.
In its hugely geared up evaluation of all components, the e-book examines the layout of recent optimum controllers requiring the choice of a functionality criterion, demonstrates optimization of linear structures with bounded controls and constrained regulate attempt, and considers nonlinearities and their impact on numerous forms of signals.
Covering the entire fundamentals, the ebook offers with the evolution of optimum keep watch over and estimation thought, and provides the required mathematical historical past wanted for this learn. It additionally lists references and difficulties, and offers appendixes for these wishing to delve into matrix algebra. all through, it bargains possibilities for experimentation, whereas discussing research, a number of filtering tools, and plenty of different pertinent topics.
An Engineering method of optimum keep an eye on and Estimation idea is a useful, self-contained reference for practising engineers, an invaluable textual content for graduate scholars and certified senior undergraduates, and a big source for somebody attracted to the way forward for sleek keep watch over know-how.
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Additional resources for An Engineering Approach to Optimal Control and Estimation Theory
The random measurement noise is represented by v(k) for k ~ 1. It should be pointed out that the observation equation contributes no dynamics to the model. 17) represents the covariance propagation. 2 we discussed the importance of the Kalman gain K(k) in connection with the continuous-time case. Consider now Eq. 18).
For example, a radar is often used in a pulsed, and thus sampled, mode. The recursive nature of the discrete-time case implies that there is no need to 112 THE KALMAN FILTER store past measurements and older estimates for the purpose of computing present estimates. The recursive characteristic is important because the burden on the onboard computer memory capacity is considerably reduced. Since in practice the Kalman filter algorithm is implemented in a digital computer, and since the digital computer cannot perform the differentiation and integration operations required for solution of the continuous-time equations, a differenceequation formulation of the filter is appropriate.
It provides clues to better design of the optimal (or suboptimal) 3. It relies on the linearity of the covariance analysis formulation. 4. It can be used to assess the theoretical limits of the system under design. or technological 5. It can be considered filter. performance as a special form of sensitivity analysis. 3 THE DISCRETE-TIME KALMAN FILTER 1. At a given time t, the filter generates an unbiased estimate x of the state vector x; that is, the expected value of the estimate is the value of the state vector at time t.