In this paper, we propose a new adaptive IMC scheme based on adaptive finite impulse response filters, which can be designed for both minimum and non-minimum phase systems in the same fashion. The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. The closed-loop is designed such that the system from the reference input to the plant output can be approximately represented by a pure delay. The effect of the process zeros on the output is compensated by using adaptive finite impulse response filters. The incorporation of adaptive finite impulse response filters avoid the cancellation of non-cancellable zeros of the plant. Ultimately, the plant output is forced to track the reference input with a delay. The stability of the closedloop for both minimum and non-minimum phase systems is guaranteed. Computer simulation results and the outcomes of real-time experiment are included in the paper to show the effectiveness of the proposed method. 1. INTRODUCTION Internal model control (IMC) structure controllers have long been successfully used for open-loop stable plants. The IMC structure is composed of the explicit model of the plant and a stable feed-forward controller. The IMC controller guarantees the internal stability of the closed-loop and parameters of the controller can be tuned online easily without disturbing stability of the system [1]. Most of the industrial processes are open-loop stable.The incorporation of the inverse of plant model in the feed-forward path can be implemented to achieve asymptotic tracking in IMC structure. The inverse of non-minimum phase plant is unstable. The use of this inverse in IMC control-loop gives rise to the unstability in the system. There are many plants that have a non-minimum phase behavior, such as dc motors with field regulation, blast furnaces, hydraulic pumps, distillation columns and so on. In this situation it becomes very important to obtain a stable inverse of the plant model to use in the IMC scheme for accomplishing the tracking objective.When the plant is represented by a discrete-time model the effect of the numerator polynomial can be compensated by approximate inverse systems [2]. These approximate inverse systems are implemented as finite impulse response filters (FIR) filters [3]. When plant is not known exactly or the plant parameters are changing slowly, then IMC controllers can be designed online using adaptive control strategies [4]. Most often discrete-time models of plants are identified online and
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