By Jacek Kabziński
This contributed quantity is written via key experts operating in multidisciplinary fields in electric engineering, linking regulate idea, energy electronics, man made neural networks, embedded controllers and sign processing. The authors of every bankruptcy record the state-of-the-art of a number of the subject matters addressed and current result of their very own study, laboratory experiments and profitable purposes. The awarded ideas pay attention to 3 major components of interest:
· movement regulate in complicated electromechanical platforms, together with sensorless control;
· fault prognosis and fault tolerant regulate of electrical drives;
· new regulate algorithms for energy electronics converters.
The chapters and the full ebook own powerful monograph attributes. very important functional and theoretical difficulties are deeply and appropriately provided at the historical past of an exhaustive state-of the artwork overview. Many effects are thoroughly new and have been by no means released earlier than. famous keep watch over tools like box orientated regulate (FOC) or direct torque regulate (DTC) are referred as a place to begin for adjustments or are used for comparability. between a variety of keep an eye on theories used to unravel specific difficulties are: nonlinear keep an eye on, strong regulate, adaptive keep an eye on, Lyapunov innovations, observer layout, version predictive keep an eye on, neural keep watch over, sliding mode regulate, sign filtration and processing, fault prognosis, and fault tolerant control.
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Additional info for Advanced Control of Electrical Drives and Power Electronic Converters
The ‘gain’ of ex À Á 1 þ tan2 ðke2 Þ equals KQLF ¼ 1; Kx ¼ 1 þ tan2 ke2x and Kxv ¼ 1 þ tan2 Kex2 respectively. The ð vÞ gains are plotted in Fig. 3. If the position tracking error is the only constrained variable, the control effort increases illimitably if the error approaches the constraint boundary. If both errors are restricted, the current increase is moderated if the velocity error is large. In Fig. 4 the state trajectories of the tracking error system under all discussed control strategies are compared for the same control gains kx ; kv .
The machine torque is controlled by the variable u12ðnÞ or by the variable m12ðnÞ if nonlinear usα usβ Sensorless Control of Polyphase Induction Machines Fig. 4 Synchronizing system for angles of main fluxes determined in virtual machines Speed observer ^ ω 21 ^ ψ mα(1) Calculation ^ ψ mβ(1) of angle 3 ^ ϕ ψm(1) r ^ ψ mα(3) Luenberger ^ ψmβ(3) Calculation observer of angle ^ 3ϕ ψ m(1) ^ ω ψm(3) ^ (-) ϕ ψm(3) feedback is applied. In this way some inertia appears in the control loop for angular velocity of the rotor flux.
Lemma 1 yields that jex ðtÞj\Dex and jev ðtÞj\DÀev . Another constraint Á V2 ð0Þ and thus for the tracking error may be obtained noticing that 2k1 tan ke2x qﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ À 2Á l 2 ð0ÞÞ . Similarly, and so V2 ð0Þ jex j Dex 2atanð2kV 2K tan Kev p qﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ 2 ð0Þ=lÞ . Using analogical reasoning, it can be derived that jev j Dev 2atanð2KV p Adaptive Position Tracking with Hard Constraints … 39 rﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ 2V2 ð0Þ , where kmin ðÃÞ denotes the smallest eigenvalue of the symkmin ðCÀ1 Þ metric matrix Ã.