This paper proposes the adaptive fuzzy total sliding-mode control systems with integral (I-AFTSMC) and proportional-integral (PI-AFTSMC) learning algorithms for the unknown nonlinear systems. These AFTSMC systems are comprised of a fuzzy total sliding-mode controller and a robust controller. The fuzzy total sliding-mode controller is utilized to approximate an ideal controller and the robust co...

The severe low-speed creep phenomenon occurs in the telescopic boom system of a heavy-load transfer robot with a long telescopic boom as a result of nonlinear friction. In order to improve control precision and operation performance at low speeds, we built a three-loop control nonlinear model of an AC servo motor with Stribeck friction disturbance. Traditional proportional-integralderivative co...

This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...

to many temperature analyses as a result of its simplicity. In [2], a PID controller is used for temperature control of a 20 KW industrial electric resistance furnace where the plant is modeled by a first-order transfer function with a time delay. Temperature control of a heated barrel with electric heaters and water coolers was proposed in [3] which used the discrete-time variable structure sy...

A robust self-organizing fuzzy-neural control (RSOFNC) system is proposed in this paper. The RSOFNC system is comprised of a self-structuring fuzzy neural network (SFNN) controller and a robust controller. The SFNN controller is the principal controller and the robust controller is designed to achieve tracking performance. In the SFNN controller design, a SFNN with the asymmetric Gaussian membe...

In this paper, a sliding mode fuzzy controller for a nonholonomic wheeled mobile robot is proposed for tracking desired trajectories. We know that sliding mode control can deal with non linearities of control system and is robust. However, it has drawbacks such as a chattering. So, we introduce a fuzzy logic in order to reduce this phenomenon. Two sliding mode fuzzy controllers (SMFC) are descr...

Neural network has good nonlinear function approximation ability. It can be widely used to identify the model of controlled plant. In this chapter, the theories of modeling uncertain plant by using two kinds of neural networks: feed-forward neural network and recurrent neural network are introduced. And two adaptive control strategies for robotic tracking control are developed. One is recurrent...

This paper is concerned with the problem of adaptive fuzzy output tracking for a class of perturbed strict-feedback nonlinear systems with time delays and unknown virtual control coefficients. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinear functions, then the adaptive fuzzy tracking controller is designed by using the backstepping technique and Lyapunov–Krasov...

Time-varying sliding mode controller(TVSMC) with fuzzy algorithm for an unmanned automatic excavator system is proposed in this paper. Proposed control system is induced from dynamics of 3-link excavator that is boom, arm and bucket. To design the proposed control system, the main structure of controller is based on sliding mode controller(SMC) with time varying sliding surface. In case of TVSM...

This paper presents a System on Chip (SoC) for the path following task of autonomous non-holonomic mobile robots. The SoC consists of a parameterized Digital Fuzzy Logic Controller (DFLC) core and a flow control algorithm that runs under the XilinxMicroblaze soft processor core. The fuzzy controller supports a fuzzy path tracking algorithm introduced by the authors. The FPGA board hosting the S...