Adaptive Interval Type-2 Fuzzy Logic Control of a Three Degree-of-Freedom Helicopter

Abstract

This paper combines interval type-2 fuzzy logic with adaptive control theory for the control of a three degree-of-freedom (DOF) helicopter. This strategy yields robustness to various kinds of uncertainties and guaranteed stability of the closed-loop control system. Thus, precise trajectory tracking is maintained under various operational conditions with the presence of various types of uncertainties. Unlike other controllers, the proposed controller approximates the helicopter’s inverse dynamic model and assumes no a priori knowledge of the helicopter’s dynamics or parameters. The proposed controller is applied to a 3-DOF helicopter model and compared against three other controllers, i.e., PID control, adaptive control, and adaptive sliding-mode control. Numerical results show its high performance and robustness under the presence of uncertainties. To better assess the performance of the control system, two quantitative tracking performance metrics are introduced, i.e., the integral of the tracking errors and the integral of the control signals. Comparative numerical results reveal the superiority of the proposed method by achieving the highest tracking accuracy with the lowest control effort.

Optimizing an Adaptive Fuzzy Logic Controller of a 3-DOF Helicopter with a Modified PSO Algorithm

“…2 shows the block diagram of the control structure of the helicopter system. In the control structure, two virtual inputs v 1 and v 2 are defined to achieve decoupling [4]:…”

“…where σ is the fuzzy logic output error, and Φ ∈ R n is an n-dimensional vector representing known functions of the fuzzy logic antecedent part [4]. Φ is defined as follows:…”

“…These control strategies perform well in the presence of parametric uncertainties. However, they may underperform in real-life applications with uncertainties, such as external disturbances, noises, and unmodeled dynamics of the machine, mainly because the methods are developed and based on the exact mathematical model of the system [4,3].…”

“…In [10], the design and experimental validation of an adaptive fuzzy PID controller is presented for a 3-DOF helicopter. The interval type-2 fuzzy logic is combined with adaptive control theory to control a 3-DOF helicopter in [4], which is robust to various types of uncertainties. However, using higher types of fuzzy systems increases the computational loads.…”

“…The adaptive type-2 fuzzy logic controller for the 3-DOF helicopter is presented in [4]. Since the membership functions are fixed in the conventional type-1 fuzzy systems, which may lead to weak performance in the presence of uncertainties, the authors of [4] proposed using type-2 fuzzy controllers for the highly nonlinear helicopter system. However, they did not present the results of the type-1 fuzzy logic controller.…”