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In this study, four adaptive neural network based fuzzy logic controllers (ANNFL) are designed and used as two controllers in terms of interval type-2 fuzzy logic control. The new controllers are called as adaptive neural network based interval type-2 fuzzy logic controller (ANNIT2FL) and applied to a rigid-flexible robot manipulator. Initially dynamic model of the manipulator is obtained by using...
A novel sub-optimal control algorithm based on fuzzy logic system (FLS) to design continuous sliding mode control (CSMC) for uncertain nonlinear systems is presented. By means of combining a fuzzy logic system into sliding mode control, continuous sliding mode control (SMC) can be designed on the derivative of the control signal. The realization of the controller is easier and more convenient than...
Ball and plate system is a high-order, uncertainty, nonlinear systems. Aiming at this system, a cascade control strategy with low-order active disturbance rejection controller (ADRC) is proposed in this paper. After the nonlinear system is converted into cascade system of several low-order nonlinear subsystems, the controller can be designed. This strategy solves the difficulties of structure design...
A wooden game board named Shoot-the-Moon has interesting dynamics properties despite its simple structure of one steel ball rolling on two cylindrical rods. In this paper, we derive the equations of motion for Shoot-the-moon using an Eular-Lagrangian approach and explore its underactuated, nonlinear, nonholonomic dynamics. Two positon controllers are designed, one for a local linearization and another...
In this work we focus on iterative learning control (ILC) for iteratively varying reference trajectories which are described by a high-order internal model. The high-order internal model (HOIM) is formulated as a polynomial between two consecutive iterations. The classical ILC with iteratively invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders...
A very successful scheme to accomplish trajectory tracking of unknown nonlinear systems consists of identifying the unknown dynamics using differential neural networks and on the basis of the so obtained mathematical model to develop an appropriate control law. The purpose of this paper is to present some new results in this sense. In particular, for the neural identifier, a new online learning law...
This paper presents a new approach to the design of a fuzzy logic control scheme for a general class of nonlinear systems. For practical consideration, we firstly define two generalized errors as inputs to form a novel two-input single-output fuzzy PD controller. Then, a supervisor is incorporated into the control scheme to help achieve its closed-loop stability. The supervisor is derived based on...
The problem of designing global robust sliding mode controller is considered for position tracking of DC motors with nonlinearities. Fast, the exact linearization technique is used to transform the nonlinear system into a linear one, and then global robust sliding mode control strategy is adopted to solve the system uncertainty problems. The integral sliding surface can effectively remove reaching...
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