ﯾ اﯾﺮان ﻓﺎزي ﺳﯿﺴﺘﻤﻬﺎي ﮐﻨﻔﺮاﻧﺲ ﺎزدﻫﻤﯿﻦ ﺑﻠﻮﭼﺴﺘﺎن و ﺳﯿﺴﺘﺎن داﻧﺸﮕﺎه زاﻫﺪان اﯾﺮان،14 ﻟﻐﺎﯾﺖ16 ﺗﯿﺮﻣﺎه1390 Adaptive Control of Twin Rotor MIMO System Using Fuzzy Logic Maryam Jahed and Mohammad Farrokhi Department of Electrical Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran farrokhi@iust.ac.ir Abstract In this paper, an intelligent adaptive controller is designed to position the yaw and pitch angles of a twin rotor MIMO system (TRMS) in two degrees of freedom, based on fuzzy logic. The control objective is to make the TRMS move quickly and accurately to the desired attitudes. Gradient descent algorithm has been used for updating parameters of fuzzy controller in order to increase its robustness against external disturbances and changes of system parameters. Experimental results is compared with the PID controller to show the effectiveness of the proposed method, especially when it encounters system uncertainties and external disturbances. Keywords: Adaptive fuzzy controller, Twin rotor MIMO system, Gradient descent algorithm. 1. INTRODUCTION The twin rotor MIMO system (TRMS) is a laboratory set-up designed for control experiments [1]. Due to the complicated nonlinearity and the high coupling effect between two propellers (Fig.1), the control problem of the TRMS has been considered as a challenging research topic [2, 3]. Among different control strategies, fuzzy logic has been widely used with different control schemes to cope with difficult control objectives in nonlinear system such as the TRMS. It has been shown that Fuzzy Logic Controller (FLC) can improve the response of TRMS in terms of tracking and transient responses [4, 5]. In [3] a novel fuzzy-sliding and fuzzy-integral-sliding controller has been designed to position the yaw and pitch angles. Adaptive neural fuzzy inference system (ANFIS) and fuzzy subtractive clustering method (FSCM) have been used in [6, 7] to solve non-linearity, trajectory, and interaction problems of TRMS. FLC has been utilized in many different hybrid schemes to cope with TRMS control objectives. Hybrid schemes could be implemented with the use of classical and/or intelligent control. In [8- 14] fuzzy logic has been proposed in different schemes with the use of Genetic Algorithms (GA) and conventional PID controller. Another use of fuzzy logic based on switching grey prediction has been proposed in [15, 16]. In most of the aforementioned works, a simple fuzzy control system was investigated, whose advantage was simple and easy to use. However, a major limitation is the lack of a systematic methodology for developing fuzzy rules. A set of fuzzy rules often needs to be manually adjusted by trial-and-error before it reaches the desired level of performance. Hence, it is desirable to develop an adaptive fuzzy controller, which can improve its performances based on adaptation of its parameters in relation to variations in the system dynamic [7]. Fig. 1. The twin rotor MIMO system The remainder of the paper is organized as follows. Description of the system is presented in Section 2. Section 3 comprehensively discusses the process of designing the adaptive fuzzy controller. Experimental results to demonstrate the effectiveness of the proposed controller are presented in Section 4. And finally, concluding remarks are provided in Section 5. 2. TWIN ROTOR MIMO SYSTEM The TRMS, as shown in Fig. 1, is characterized by complexity, high nonlinearity and inaccessibility of some states and outputs for measurements, and hence can be considered as a challenging engineering problem. The control objective is to make the beam of the TRMS move quickly and accurately to the desired attitudes, both the pitch angle and the yaw angle. The TRMS is driven by two DC motors. Its two propellers are perpendicular to each other and joined by a beam pivoted on its base that can rotate freely on the horizontal and vertical planes. The joined beam can be moved by changing the input voltage to control the rotational speed of these two propellers. There is a