Online self-adaptive proportional-integral-derivative control for brushless DC motor based on variable universe fuzzy inference system optimized by genetic algorithm

In this study, we propose a novel robust online self-adaptive Proportional-Integral-Derivative (PID) control design for Brushless DC Motor (BLDCM) speed system under different operating conditions. The online adaptive tuning for PID parameters is realized accurately by optimizing the control rules of variable universe fuzzy inference with a modified genetic algorithm (GA). Based on the variable fuzzy inference theory, the method of solving contraction–expansion factor in real-time through fuzzy inference is proposed. Furthermore, the process to optimize two inference rules by GA is improved to get optimal control rules for adjusting PID parameters. Finally, multiple sets of simulations and experiments are conducted to validate the proposed controller in different conditions by building Simulink models and setting up experiment platforms. The results of this study not only demonstrate the effectiveness of the proposed controller but also provide technical suggestions for the speed control of BLDCM.

Variable universe adaptive fuzzy sliding mode projective synchronization of hyperjerk system based on disturbance observer

In this paper, a sliding mode projective synchronization strategy based on disturbance observer and fuzzy system is presented to implement projective synchronization of hyperjerk system with low time-varying disturbance and white noise. Theoretical analysis and numerical calculation show that the disturbance observer can approach the low time-varying disturbance very well. The application of disturbance observer reduces the chattering of the controller. Variable universe adaptive fuzzy control (VUAFC) method is utilized to further reduce the chattering phenomenon. The simulation results demonstrate the effectiveness of the proposed controller.

GPS Path Tracking Control of Military Unmanned Vehicle Based on Preview Variable Universe Fuzzy Sliding Mode Control

In the process of the continuous development and improvement of modern military systems, military unmanned vehicles play an important role in field reconnaissance and strategic deployment. In this paper, the precise tracking algorithm of a military unmanned vehicle, based on GPS navigation, is studied. Firstly, the optimal preview point is obtained according to the data points of a differential GPS signal. Secondly, the pure tracking algorithm is used to calculate the demand steering angle, and a variable universe fuzzy sliding mode controller is designed to control the lateral motion of the vehicle, which is verified by the joint simulation platform of Simulink and CarSim, under multiple working conditions. Finally, the actual vehicle is verified by using the Autobox platform. The results show that the lateral motion control of path tracking designed in this paper can achieve an accurate and effective control effect, and has real-time performance for engineering applications.

Research on Variable-Universe Fuzzy Control Technology of an Electro-Hydraulic Hitch System

To improve the quality and control accuracy of the farming tractor electro-hydraulic hitch system, a variable-universe fuzzy control algorithm is introduced herein based on force–position mixed adjustment. (1) Background: This research sought to improve the operation quality and control precision of the tractor electro-hydraulic suspension operation system by solving the slow response and low precision problems in the target value control of the system. (2) Methods: According to the characteristics of the operating system, the working principle is discussed. The variable-universe fuzzy controller and the control module were designed based on MC9S12XS128. At the same time, we used Matlab/Simulink to study the step response, and field tests were carried out based on the existing test conditions. (3) Results: In the response stage, the variable-universe fuzzy control only needs 5.85 s, and there is no overshoot problem; in the normal tillage stage, the maximum tillage depth difference is only 1.6 cm, and the traction force is 428 N, which is closer to the expected value. (4) Conclusions: The farming quality and efficiency of the operating system were improved. Additionally, the operating system can also provide technical support for intelligent agricultural machinery and the field management mode in the future.

Variable universe fuzzy control of the wheel loader semi-active cab suspension with multimode switching shock absorber

The aim of this work is to design a variable universe fuzzy control of a wheel loader semi-active cab suspension with damping multimode switching shock absorber. Considering the cost and reliability, a new type of shock absorber, whose adjustable damping characteristics are achieved by just changing the on–off statuses of two solenoid valves, is applied to the wheel loader cab suspension. The vibration model of the wheel loader, which considers the vibration characteristics of the working device, the four-wheel correlated random road excitation, and the engine vibration excitation simultaneously, is established first. Based on the working principle of the target shock absorber, the damping multi-state switching model is also established to reflect the relationship between the damping coefficients and the on–off statuses of two solenoid valves. Then, a variable universe fuzzy damping control strategy, which can determine the optimal switching sequences of the damping modes according to the cab suspension performance indexes, is designed. Finally, simulation analyses were conducted to verify the effectiveness of the proposed control approach of the wheel loader semi-active cab suspension with multimode switching shock absorber.

Variable universe fuzzy control of the lateral stability of forklift trucks based on roll grading

Based on the structural analysis and the roll mechanisms of counterbalanced forklift truck, a novel type of 3-link hydraulic supporting mechanism is designed as an actuator for forklift anti-rollover control. A rollover grading control strategy of the lateral stability of counterbalanced forklift truck is proposed, which is used to design a variable universe fuzzy controller. The variable universe fuzzy control of the first-order roll is utilized when the forklift is in the first-order roll, whereas the variable universe fuzzy control of the second-order is used when the forklift is in the second-order roll. A virtual prototype model of forklift is built in Automatic Dynamic Analysis of Mechanical Systems (ADAMS). The co-simulations and vehicle tests are implemented, the results indicate that the lateral stability and active security of the forklift could be improved effectively by using the variable universe fuzzy control strategy of the lateral stability of forklift truck based on roll grading.