Anti-Swing Adaptive Fuzzy Controller for an Overhead Crane With Hoisting

The objective of this study is to design a new anti-swing control scheme for overhead cranes, the performance of which equals or possibly surpasses the performance of a skilled crane operator. In this study, the anti-swing control problem is solved as a trajectory-tracking control problem. An anti-swing trajectory control scheme is designed based on the Lyapunov stability theorem, and then extended to an adaptive scheme to cope with parametric uncertainties, in which sufficient damping of load swing is achieved by modifying the reference trajectory of the trolley. The proposed control consists of a feed forward control and a non-linear PID control with gravity compensation, which guarantees asymptotic stability while keeping all internal signals bounded. The proposed control, allowing high-speed load hoisting, also guarantees accurate control of trolley position and rope length with optimum damping. In summary, the proposed control realizes a typical crane operation in practice, maintains its control performance in the presence of parametric uncertainties, and has a simple structure for easy implementation and gain tuning. The performance of the proposed control is shown with computer simulations.

In this paper, a fault diagnosis method is presented in order to detection the inter-turn short circuit fault in permanent magnet synchronous motor (PMSM) based on the comparative analysis of two types of controllers. This study consists in the sliding mode control (SMC) of the (PMSM) and the two controllers (fuzzy logic controller (FLC) and Adaptive fuzzy logic controller (AFLC) by taking account of the presence of inter-turn short circuit fault. This study aims to select the most robust controller against the stator faults, load torque variation and reversing rotation speed. Tests regarding these two controllers associated with the sliding mode control were carried on a PMSM 5KW under to different loads, speed and severity degrees of failures for a functioning in healthy and degraded state. The obtained simulation results confirm the superiority and robustness of AFLC-SMC (insensitive to the load torque and the rotation direction, faster response time, decrease the oscillations, and minimization of THD) compared to FLC-SMC.

Research on A Fuzzy Adaptive PID Control Method for Four Rotor UAV Control System With the continuous improvement of national living standards, people have higher and higher requirements for the reliability of power supply. The emergence of unmanned aerial vehicle inspection technology provides a new idea to solve the contradiction between the increasing equipment scale and the increasing inspection requirements. However, at present, the stability of the traditional proportion integration differentiation (PID) control system of the four rotor unmanned aerial vehicle (UAV) is not high enough. During the inspection, there are accidents of drones hitting power equipment from time to time. In view of the above problems, this paper studies the fuzzy adaptive PID control method to support the stable flight of four rotor UAV. The principle of fuzzy control is analyzed. The fuzzy control method and PID control method are deeply integrated. A fuzzy adaptive PID control system is designed. The universe and membership function of the relevant control parameters of the system are formulated. The tuning rules of fuzzy adaptive PID control system are formulated. Finally, the improved control system is simulated. The simulation results show that the fuzzy adaptive PID control algorithm can effectively improve the stability, reliability and emergency ability of UAV. This method can effectively improve the adaptability of UAV to perform complex missions in complex environments. The research results have guiding significance for expanding the application field of UAV.

This paper demonstrates tracking control of a class of feedback linearizable unknown nonlinear dynamical systems, such as a robotic systems, using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLC's are implemented on digital computers. A repeatable design algorithm and a stability proof are examined for an adaptive fuzzy logic controller that uses fuzzy basis functions based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant. An /spl epsiv/-modification sort of approach to adapt the fuzzy system parameters is examined. Using this adaptive fuzzy logic controller, uniform ultimate boundedness of the closed-loop signals is presented and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that works for any system in the given class of systems.

One of the common industrial structures that are used widely in many harbors and factories and buildings is overhead crane. Overhead cranes are usually operated manually or by some conventional control methods. In this paper, we propose a hybrid controller includes both position regulation and anti-swing control. According to Takagi-Sugeno fuzzy model of an overhead crane, a fuzzy controller designed with parallel distributed compensation and Linear Quadratic Regulation. With the Takagi-Sugeno fuzzy modeling, the nonlinear system is approximated by the combination of several linear subsystems in the corresponding fuzzy state space region. Then by constructing a linear quadratic regulation subcontroller according to each linear subsystem, a parallel distributed fuzzy LQR controller is designed. Further, the stability of the overhead crane with the parallel distributed fuzzy LQR controller is discussed. Simulation results illustrated the validity of the proposed control algorithm and it is compared with a similar method parallel distributed fuzzy controller.

In this paper, temperature monitoring of sterilizing equipment system was established with the help of fuzzy and self tuning Adaptive fuzzy logic controller designed in Lab VIEW software. It combines the advantages of both fuzzy logic and self tuning Adaptive fuzzy logic controller. The implementation attempts to rectify the errors between the measured value and the set point which helps to achieve efficient temperature control. The Adaptive fuzzy controller uses defined rules to control the system based on the current values of input variables and temperature errors. The simulation results presented in order to evaluate the proposed method. The result shows that self tuning Adaptive fuzzy logic controller was tolerant to disturbance and the temperature control is most accurate.

Sensor is an indispensable component in feedback control. In anti-swing feedback control of automatic gantry crane system, sensors are normally employed to detect trolley position and payload swing angle. However, sensing the payload motion of a real gantry crane, in particular, is troublesome and often costly since there is hoisting mechanism on parallel flexible cable. Therefore, sensorless anti-swing control method for automatic gantry crane system is proposed in this study. The anti-swing control is performed in feedback control scheme without using real swing angle sensor. Instead, soft sensor approach is used to substitute the real swing angle sensor. The soft sensor is designed based on Dynamic Recurrent Neural Network (DRNN) as a state estimator. Thus, a DRNN is trained using input-output data to estimate payload swing angle from trolley acceleration and input voltage of trolley actuator. An experimental study using lab-scale automatic gantry crane is carried out to evaluate the effectiveness of the proposed sensorless anti-swing control. The results show that the proposed sensorless method is effective for payload swing suppression since similar performance to the sensor-based feedback anti-swing control is obtained.

The present paper describes the development of a new adaptive fuzzy logic controller (AFLC), which can directly employ an adaptive fuzzy/neuro/neuro-fuzzy function approximator to develop a desired controller, based on an ideal controller input-outpu

An adaptive fuzzy controller has been designed to develop a high-performance fault-tolerant SRM drive. The fuzzy controller continuously adapts its properties to regulate the machine torque as desired by the drive system even under fault conditions. The adaptation of the fuzzy membership functions results in extended conduction period and increased peak current of the healthy phases to deliver the commanded torque, as much as possible. The adaptive fuzzy controller provides smooth torque output with minimum ripple, even under fault conditions, yielding a high-performance SRM drive with fault-tolerant capability.

Harmony search algorithm and Lyapunov theory based hybrid adaptive fuzzy controller for temperature control of air heater system with transport-delay

Adaptive type-2 fuzzy logic control of a bioreactor

This paper addresses adaptive fuzzy logic controller for load frequency control of a multi-source two area power system with different power generation sources viz hydro gas & thermal power plant. Expert knowledge is required for conventional fuzzy logic control in developing parameters. Whereas in this method rules are tuned online by adaptation algorithm according to operating condition. The robustness of adaptive fuzzy logic controller has been shown by comparing with conventional fuzzy logic controller and integral controller. The comparison is done based on various performance indices like settling times and peak overshoots for 1 percent step load perturbation.

In this paper, real-type tabu search (RTS) is proposed, which adaptively changes the range of the neighbor solution to be searched each iteration according to an objective function. We design-the adaptive fuzzy logic controller (AFLC) for speed control of DC servomotor using RTS and neural network (NN). In this paper, the operation of the AFLC for speed control of a DC servomotor is composed of two steps. The first step is for optimizing the weighting value of NN and the initial value of input/output gain needed in real-time adjusting input/output gain of a fuzzy logic controller using a NN using the improved RTS. The second step is for real-time changing of the input/output gain of FLC using NN. We apply the proposed AFLC to the speed control of an actual DC servomotor system. Experimental results show that AFLC has the better control performance than a PI controller in terms of settling time, rise time and overshoot.

Fuzzy logic-based algorithms are widely employed in variable-speed drives. However, although they provide an excellent speed-control performance, they may result in significant current harmonics. These may be reduced by employing a non-linear distribution of fuzzy sets in the membership function of the output variable, albeit with some deterioration in the speed-control performance. A simple adaptive fuzzy logic control algorithm, in which the speed-error threshold may be either fixed or self-tuned, is proposed. Simulations and measurements on vector-controlled permanent-magnet brushless AC drives confirm that the proposed adaptive fuzzy logic control results in an excellent speed-control performance and robustness to parameter variations, while current harmonics are reduced. Its performance is compared with that which is achieved when conventional fuzzy logic and PI speed control are employed.

This paper proposes a new trajectory-generation scheme for a high-performance anti-swing control of overhead cranes, where the trajectory-generation problem is solved as a kinematic problem. First, a new anti-swing control law is designed based on the load-swing dynamics, for which the Lyapunov stability theorem is used as a mathematical tool. Then a new trajectory-generation scheme is proposed based on the anti-swing control law and typical crane operation in practice. For g iven hoisting motions, trolley-traveling trajectory references are computed based on the concept of minimum-time control, and then anti-swing trajectories are generated based on the trajectory references through the anti-swing control law. The new trajectory-generation scheme generates a typical anti-swing trajectory in industry with high-speed load hoisting. The effectiveness of the proposed trajectory-generation scheme is shown by generating high-performance anti-swing trajectories with high hoisting speed and hoisting ratio.