Simulation analysis of cooperative motion fuzzy control of distributed lifting units

In the technology of hydraulic lifting system, it is not only necessary to ensure that the displacement and velocity accuracy of each hoist reach a certain value, but also to ensure that under the control of load balance to make each hoist smooth lift. In the conventional method, the PID control method can realize the synchronization of the function. However, the system cannot be controlled and adjusted in real time during the control parameter period, resulting in instability and uncertainty of the system. Aiming at this problem, this paper adds the fuzzy adaptive controller to carry out the master-slave control of the system. AMESim and MATLAB co-simulation were used to model the overall model of the hydraulic system. At the same time, the pressure compensator and variable throttle port model in the hydraulic reservoir were selected to build. The pressure compensator is used to keep the pressure difference of the throttle orifice constant, so as to complete the control and design of the hydraulic lifting system. Finally, the simulation results obtained not only can effectively improve the instability of the hydraulic lifting process, but also greatly improve the operation speed of the system.

Real-time control and application with self-tuning PID-type fuzzy adaptive controller of an inverted pendulum

PurposeThis paper aims to keep the pendulum on the linear moving car vertically balanced and to bring the car to the equilibrium position with the designed controllers.Design/methodology/approachAs inverted pendulum systems are structurally unstable and nonlinear dynamic systems, they are important mechanisms used in engineering and technological developments to apply control techniques on these systems and to develop control algorithms, thus ensuring that the controllers designed for real-time balancing of these systems have certain performance criteria and the selection of each controller method according to performance criteria in the presence of destructive effects is very helpful in getting information about applying the methods to other systems.FindingsAs a result, the designed controllers are implemented on a real-time and real system, and the performance results of the system are obtained graphically, compared and analyzed.Originality/valueIn this study, motion equations of a linear inverted pendulum system are obtained, and classical and artificial intelligence adaptive control algorithms are designed and implemented for real-time control. Classic proportional-integral-derivative (PID) controller, fuzzy logic controller and PID-type Fuzzy adaptive controller methods are used to control the system. Self-tuning PID-type fuzzy adaptive controller was used first in the literature search and success results have been obtained. In this regard, the authors have the idea that this work is an innovative aspect of real-time with self-tuning PID-type fuzzy adaptive controller.

Fuzzy Adaptive Controller for Synchronization of Uncertain Fractional-Order Chaotic Systems

In this chapter, the projective synchronization problem of different multivariable fractional-order chaotic systems with both uncertain dynamics and external disturbances is studied. More specifically, a fuzzy adaptive controller is investigated for achieving a projective synchronization of uncertain fractional-order chaotic systems. The adaptive fuzzy-logic system is used to online estimate the uncertain nonlinear functions. The latter is augmented by a robust control term to efficiently compensate for the unavoidable fuzzy approximation errors, external disturbances as well as residual error due to the use of the so-called e-modification in the adaptive laws. A Lyapunov approach is employed to derive the parameter adaptation laws and to prove the boundedness of all signals of the closed-loop system. Numerical simulations are performed to verify the effectiveness of the proposed synchronization scheme.