By Howard Kaufman
Suitable both as a reference for practising engineers or as a textual content for a graduate direction in adaptive regulate platforms, this booklet is a self -contained compendium of conveniently implementable adaptive keep an eye on algorithms which were built and utilized by means of the authors for over fifteen years. those algorithms, which don't require the consumer to spot the method parameters explicitly, were effectively utilized to a large choice of engineering difficulties together with versatile constitution keep watch over, blood strain keep watch over, and robotics; they're compatible for a large choice of a number of input-output keep an eye on structures with uncertainity and exterior disturbances. The textual content is meant to let a person with wisdom of easy linear multivariable structures to evolve the algorithms to difficulties in a wide selection of disciplines. therefore, as well as constructing the theoretical info of the algorithms awarded, the textual content supplies significant emphasis to layout of algorithms and to consultant functions in flight keep watch over, versatile constitution keep an eye on, robotics, and drug-infusion keep an eye on. Engineers can hence use and attempt those algorithms in functional difficulties. This moment variation has been corrected and up to date all through. It uses MATLAB courses for the various illustrative examples; those courses are defined within the textual content and will be got from the MathWorks dossier server.
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Additional info for Direct Adaptive Control Algorithms: Theory and Applications
Response for Time-varying Gain K 1600 1800 = (1. 95 sin 2000 t) linearized approximation of a nonlinear generator-voltage control system  augmented with a feedforward compensator, which will be described in Chapter 3. 5) . 4, the nominal closed loop plant is stable for gain values greater than some minimal values. Variations of plant parameters from the assumed nominal values affect the performance and stability of the plant. For convenience of the presentation in this example, the plant uncertainty is represented by an unknown and arbitrarily time-varying gain, Kplant.
9. 3 10 8 time Kpl ant Defined in Background on Adaptive Control Algorithms Closed loop adaptive control methods may be divided into the two broad categories of direct or implicit control and indirect or explicit controL Indirect control methods utilize separate parameter identification and control schemes. Direct methods merge the identification and control functions into one scheme. In such direct methods, the control gains are computed directly without an explicit identification of the system parameters.
117) - ApXxm(t) - BpKxxm(t) - BpKuum(t). 119) This implies that the ideal trajectories can be plant trajectories, and that perfect tracking is possible if E(t) = (ApX - XAm + BpKx)xm + (BpKu - XBm)um = O. 120) 36 Chapter 2. 122), which must be satisfied by the matrices Kx and Ku , in general, contain more equations than variables. The ideal trajectories therefore remain as reference target trajectories that the plant attempts to reach. The linear analysis of this section will be used in the next chapters, where adaptive algorithms are used to compute the control gains.