Adaptive Harmonic Steady-State Control for Disturbance Rejection

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57793/1/HSSTCSTNov2006.pd

Multivariable Adaptive Harmonic Steady-State Control for Rejection of Sinusoidal Disturbances Acting on an Unknown System

This paper presents an adaptive harmonic steady-state (AHSS) controller, which addresses the problem of rejecting sinusoids with known frequencies that act on a completely unknown multi-input multi-output linear time-invariant system. We analyze the stability and closed-loop performance of AHSS for single-input single-output systems. In this case, we show that AHSS asymptotically rejects disturbances.Comment: 6 pages, 2016 American Control Conference (ACC). IEEE, 201

Switching-based Sinusoidal Disturbance Rejection for Uncertain Stable Linear Systems

The problem of rejection of sinusoidal disturbances with known frequencies acting on an unknown singleinput single-output linear system is addressed in this note. We present a new approach that does not require knowledge of the frequency response of the transfer function over the frequency of interest. The proposed methodology reposes upon the combination of the classic feedforward control algorithm and logic-based switching. The use of three different switching logics is proposed in this paper, namely: pre-routed, dwell-time and hysteresis switching. A comparative evaluation of the three switching strategies is performed via a simulation study

EXPERIMENTAL COMPARISON OF TWO SAMPLED-DATA ADAPTIVE CONTROL ALGORITHMS FOR REJECTING SINUSOIDAL DISTURBANCES

We review two adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. We present modifications to the algorithms that address the problems of sensor noise and actuator saturation. We demonstrate the effectiveness of the algorithms and compare the performance of the algorithms via numerical simulation and experimental testing

Doctor of Philosophy

dissertationThe dissertation is concerned with the development and analysis of adaptive algorithms for the rejection of unknown periodic disturbances acting on an unknown system. The rejection of periodic disturbances is a problem frequently encountered in control engineering, and in active noise and vibration control in particular. A new adaptive algorithm is presented for situations where the plant is unknown and may be time-varying. Known as the adaptive harmonic steady-state or ADHSS algorithm, the approach consists in obtaining on-line estimates of the plant frequency response and of the disturbance parameters. The estimates are used to continuously update control parameters and cancel or minimize the effect of the disturbance. The dynamic behavior of the algorithm is analyzed using averaging theory. Averaging theory allows the nonlinear time-varying closed-loop system to be approximated by a nonlinear time-invariant system. Extensions of the algorithm to systems with multiple inputs/outputs and disturbances consisting of multiple frequency components are provided. After considering the rejection of sinusoidal disturbances of known frequency, the rejection of disturbances of unknown frequency acting on an unknown and time-varying plant is considered. This involves the addition of frequency estimation to the ADHSS algorithm. It is shown that when magnitude phase-locked loop (MPLL) frequency estimation is integrated with the ADHSS algorithm, the two components work together in such a way that the control input does not prevent frequency tracking by the frequency estimator and so that the order of the ADHSS can be reduced. While MPLL frequency estimation can be combined favorably with ADHSS disturbance rejection, stability is limited due to the local convergence properties of the MPLL. Thus, a new frequency estimation algorithm with semiglobal stability properties is introduced. Based on the theory of asynchronous electric machines, the induction motor frequency estimator, or IMFE, is shown to be appropriate for disturbance cancellation and, with modification, is shown to increase stability of the combined ADHSS/MPLL algorithm. Extensive active noise control experiments demonstrate the performance of the algorithms presented in the dissertation when disturbance and plant parameters are changing

Disturbance Suppression in PMSM Drives Physical Investigation, Algorithm Design and Implementation

The work of this Ph.D. focuses on the investigation of advanced control algorithms for the control of constant and periodic disturbances in Permanent Magnet Synchronous Machines (PMSMs), with the discussion of different methods for improving their negative influence on the machine current and the torque produced at the shaft. The discussion of the disturbances from a control perspective starts with the study of the parameter uncertainties effect on the dynamical performances of the current control and after the detailed analysis in the frequency domain, simple methods for improving the state-of-art decoupling network are given and validated on the testbench. Thanks to the feature of the introduced estimator, the transient behavior of the proposed strategy results in a consistent fast and precise performance. The control scheme allows to avoid the implementation of anti-windup mechanisms in the current control, making the overall controller less sensitive to parameter mismatch. Further, due to the low computational burden, the algorithm is suitable for low cost hardware. Subsequently, the more complex issue of periodic disturbances has been deeply investigated. The theoretical model proposed is validated by comparing the real measured torque with an estimation based on the recovered disturbance affecting the observed voltages and currents. The results are clearly acceptable and further, the experimental validation stresses out the fact that few terms have a predominant role in producing the harmonic disturbances, compared to the others. This consideration lets develop two strategies for suppressing the different harmonic orders present in the machine torque at low-speed operation. One strategy relies on on-line adaptive policies, where the estimated information is passed through a sequence of optimization algorithms with different objectives. In this context, hints on the guaranteed stability are also provided in order to confirm the practical feasibility of the algorithm. The other strategy is based on the off-line generation of some pre-determined functions, limiting the on-line burden to the computation of look-up tables. Both methods brought satisfactory results during the experimental validation, confirming the validity of our approximations made on the original complex model. Although the hardware testbed setup limited the opportunity to validate the methodologies at low speed, this represents a realistic scenario, in fact at higher speed the artificial injection of harmonics within the machine current becomes challenging due to the high electrical rotational speed and it brings more negative effects, in terms of losses and audible noise than benefits on the shaft stress, in fact, the machine inertia acts as a natural filter for the high frequencies harmonics. In summary, it can be said that the research work on advanced control algorithms for the disturbance suppression in PMSM drives has produced affordable and reliable methodologies, which can be of practical implementation for various industrial drives