| With the development of society, the topic of noise control has been paid much attention. Either in civil or military domain, noise is polluting the environment, doing harm to our health. Even our lives are badly endangered, so the noise control is becoming important and urgent The works in this domain have been widely investigated all over the world.In this domain, active noise control is developed greatly. However, the conventional adaptive control also is not perfect in many aspects; for instance, the deficiencies in many adaptive algorithms are extraordinarily distinct Consequently it is promising and significant to improve the performance of adaptive algorithm by means of new methods. Aimed at this matter, the control algorithm and the controller hardware and software are investigated in this paper.The paper consists of the following parts:The adaptive algorithms, such as LMS (Least Mean Square, LMS), are analyzed and their performance is addressed theoretically, which offer gist for the improvement of algorithm. Because the control system is usually MIMO, the LMS algorithm with multi-inputs is studied in the details. According to the idea of forward control, the corresponding weights of this algorithm are given.Because, in adaptive control, the precision and real-time of system identification can have direct effect on control quality, the method of system identification is vital. Base on the adaptive algorithm, the system identification is discussed first. In order to obtain the stability and real time response of the control system, the parallel on-line system identification is applied in control system, which effectively solves the problem in system identification.The controller with TMS320F2812 is explored. The hardware and software are completed based on this controller. The experiment setup is constructed with the vehicle model and this controller, which makes preparations for the real-time control experiment. |
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