Centralised and decentralised configurations for panels with piezoelectric actuators

This paper discusses configurations for controlling broadband noise using piezoelectrically excited panels. The configurations can be distinguished by the physical layout and by the control structure. The physical layout of the system has some influence on the complexity of the control algorithms. For particular actuator/sensor combinations and a particular control objective, the control architecture can be decentralized, using very simple feedback or feedforward controllers, at small performance loss when compared to a centralized architecture. For some applications that require a different control objective, an additional centralized or possibly distributed architecture could be beneficial. A hardware realization with an associated control framework that allows the implementation of such a combined centralized-decentralized architecture is shown. Examples that are given are an embedded central control unit with all electronics in a single module and a centralized-decentralized architecture with partly decentralized hardware that is integrated with structural parts

Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the \ud amount of reduction, and stability of the algorithm. Nevertheless, if the error in the model of the relevant transfer functions becomes too large then the system may become unstable or lose performance. On-line adaptation of the model is possible in principle but, for rapid changes in the model, necessitates \ud a large amount of additional noise to be injected in the system. It has been known for decades that a combination of high-authority control (HAC) and low-authority control (LAC) could lead to improvements with respect to parametric uncertainties and unmodeled dynamics. In this paper a full digital implementation of such a control system is presented in which the HAC (adaptive MIMO control) is implemented on a CPU and in which the LAC (decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given in which it is demonstrated that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal

Active vibration control applied to a vacuum pump for high precision equipment

This paper presents results of a system for active vibration reduction on a setup with a vacuum pump that is tightly coupled with high-precision equipment. The precision of this equipment is critically dependent on the level of the vibrations that are introduced by the vacuum pump. The vibrations were reduced by a recently developed adaptive control scheme in a multi-input multi-output feedback configuration using a sampling rate of 12 kHz. The convergence properties of this algorithm allowed effective tracking of the varying excitation spectrum. Programmable digital minimum-phase reconstruction and anti-aliasing filters at a sampling rate of 100 kHz were used for an optimal tradeoff between sampling errors and phase shift. Effective broadband control was obtained in the frequency range of 100 Hz to 5 kHz, leading to 11.3 dB average broadband reduction on the error sensors

Implementation issues of a High-Speed distributed Multi-Channel ADDA System

A multi-channel ADDA controller is used in many active noise cancellation and active vibration control problems. Such a con- troller is able to yield good performance, however it also requires a lot of hardware on a centralized place and a lot of sensitive wiring. A practical work around for this problem would be to use a local single channel controller. However such a controller would reduce the overall system performance and may introduce instability. In this paper a system will be presented that acts as a hybrid form and combines the performance of a local feedback loop with a large multi-channel controller. To reduce the wiring and the influence of disturbances on this wiring a local analog to digital and digital to analog converter will be used. These systems will be interconnected using a high-speed serial com- munication system. To reduce the sample rate for the overall system, a local decimation and interpolation filter will be imple- mented. Further performance improvements will be realized by means of a simple local feedback system. The implementation issues concerning such a system are the subject of this paper

Rapidly converging adaptive state-space-based multichannel active noise control algorithm for reduction of broadband noise

Rapidly changing spectra may lead to performance limitations in adaptive systems for broadband active noise control, especially in multichannel systems. This paper presents techniques to address the negative consequences of two main causes. First, the dynamics of the transfer paths between the noise control sources and the error microphones is compensated for by using a regularized state-space based adaptive filtered-error scheme. Second, for the reference signals a modified adaptive scheme is used, taking into account the nonwhiteness of these signals as well as the correlation between the individual signals. Examples are given for simulated data and for real-time implementations. This work was partly supported by EC Contract 501084 (InMAR)

Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control(HAC)and low-authority control (LAC)is considered for improved performance in case of such model errors. A digital implementation of a control system is presented in which the HAC (adaptive MIMO control)is implemented on a CPU and in which the LAC(decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given which demonstrate that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal

Multichannel active noise control systems and algorithms for reduction on broadband noise

Active noise contral systems for braadband noise reduction require substantial computing power, especially for multichannel systems and adaptive controllers. Furthermore, speed of convergence can be an issue as weil. In this paper, methods and techniques are described that are able to reduce the computational complexity and to improve the speed of convergence. The latter is accomplished by using a control implementation running at multiple sample rates. Decentralised control loops running at high sample rates are efficiently implemented on reconfigurable hardware. For the low to medium sample rates, a full multichannel adaptive control algorithm has been developed that leads to subtantially improved convergence rates at reasonable computational complexity

Fast affine projections and the regularized modified filtered-error algorithm in multichannel active noise control

In this paper, real-time results are given for broadband multichannel active noise control using the regularized modified filtered-error algorithm. As compared to the standard filtered-error algorithm, the improved convergence rate and stability of the algorithm are obtained by using an inner–outer factorization of the transfer path between the actuators and the error sensors, combined with a delay compensation technique using double control filters and a regularization technique that preserves the factorization properties. The latter techniques allow the use of relatively simple and efficient adaptation schemes in which filtering of the reference signals is unnecessary. Results are given for a multichannel adaptive feedback implementation based on the internal model control principle. In feedforward systems based on this algorithm, colored reference signals may lead to reduced convergence rates. An adaptive extension based on the use of affine projections is presented, for which real-time results and simulations are given, showing the improved convergence rates of the regularized modified filtered-error algorithm for colored reference signals