Journal of Control Science and Engineering

In order to provide accurate image information for the analysis and treatment of dangerous rocks and rockfalls during the early investigation, a UAV tilt photography control method for numerical simulation of high and steep rock slopes is proposed. Based on the UAV tilting photography technology, the slope section was obtained through a real 3D modeling and poststage point cloud data processing. Numerical simulation is used to study the motion characteristics of dangerous rock falling in a high and steep slope of a railway station. This essay introduces the application of a UAV tilting photography and real 3D modeling technology in the process of rock fall analysis and realizes the real scene restoration of the site. The point cloud data of the site is obtained, and the processing process of the point cloud is introduced in detail. The slope section of the site was obtained based on the point cloud, and RocFall software was used to obtain the motion characteristics of dangerous rock falling (falling trajectory, bouncing height impact energy, and impact velocity). The simulation results show that because of the rugged slope, the falling rocks collide and rebound on the slope for many times. In addition, near the bottom of the slope, there is a steep cliff with a height of 136.21 m, which is approximately 54° from the horizontal line, causing the falling rock to bounce and eventually fall at a higher height. It moves to the bottom of the slope and bounces off the level of the railway line before finally settling on the railway road. The maximum bounce height of falling rock in the process of slope rolling motion reaches 30 m. When falling rock moves near the railway line (coordinate is on the right side of zero), the bounce height is 15∼25 m, which threatens the safety of the railway operation. Conclusion. The UAV tilt photography technology can be well applied to the analysis of rockfall motion characteristics of dangerous rocks, and provide an accurate cross-section data information for the study of rockfall motion characteristics of dangerous rocks.

In order to improve the reliability of robot electrical fault detection and diagnosis, the author proposes a robot electrical fault detection and diagnosis method based on deep learning. Taking the return power and active power as constraints, the electrical fault data collection of the robot is carried out. Taking the resonant inductance and resonant capacitance of the robot electrical equipment as identification parameters, we conduct electrical fault differential feature mining. The fault features are extracted according to the time-delay distribution sequence of the electrical fault data of the robot, and the electrical fault detection and diagnosis results are output by using the deep learning function. Simulation results show that the author's method has a high accuracy probability for robot electrical fault diagnosis. The author's method is on average 14.7% higher than the neural network-based method and 24.5% higher than the expert system-based method. The accuracy rate of the author's method for robot electrical fault diagnosis is high. The author’s method is 16.6% higher than the neural network-based method on average and 34.2% higher than the expert system-based method. It is proved that the robot electrical fault detection and diagnosis based on deep learning has high accuracy and short time.

In order to solve the problems of unstable motion and large trajectory tracking error of the manipulator when it is disturbed by the outside world, the author proposes an adaptive neural network manipulator motion trajectory error method. The author gives the dynamic equation of the manipulator and uses the positive feedback neural network to study the dynamic characteristics of the manipulator. An adaptive neural network control system is designed, and the stability and convergence of the closed-loop system are proved by the Lyapunov function. A schematic diagram of the manipulator model is established, and MATLAB/Simulink software is used to simulate the dynamic parameters of the manipulator. At the same time, it is compared and analyzed with the simulation results of the PID control system. Simulation results show that in robot arm 3, the expected motion trajectory is θ₃ = 0.4cos(2πt), the initial condition θ(0) = [000]^τ, the control parameter K = diag(40,40),40), the disturbance parameter τ’ = 20cos(πt), robot arm link parameters l₁ = 0.62 m, l₂ = 0.41 m, l₃ = 0.34 m, m₁ = 3.5, m₂ = 2.5 kg, m₃ = 2 kg, g = 9.82 m/s², under t = 2_s, the motion trajectory of the robotic arm is disturbed by the outside world, and the adaptive neural network is used to control the motion trajectory with a small tracking error, input torque ripple is small. Conclusion. The manipulator adopts the adaptive neural network control method, which can improve the control accuracy of the motion trajectory and weaken the jitter phenomenon of the manipulator motion.

In order to solve the problems of low power factor and large harmonic pollution of some electrical equipment connected to the power grid, such as electric vehicle charger system, the author proposes a high-performance control simulation study of a PFC converter for electric vehicle charger. Using the staggered parallel boost power factor correction circuit topology of electric vehicle chargers as the front stage, its high power factor and low harmonic current characteristics can reduce the pollution to the power grid, and the detailed design process and loss analysis of the circuit are given. Through the digital control method and hardware optimization design, the loss is reduced, and the conversion efficiency of the power factor correction converter in the full power range is high, which meets the efficiency requirements of the platinum version and achieves the goal of energy saving and environmental protection. The test results show that the actual efficiency of the experimental prototype is 97.43%, 97.55%, and 97.36%, which are far higher than the efficiency requirements of the platinum version. Conclusion. The high-performance control of the PFC converter of the electric vehicle charger has certain guiding significance for the application in the electric vehicle.

Minimal power loss is highly desired for an efficient and economical operation in distributed systems. This paper presents an improved symbiotic organisms search (ISOS) for system reconfiguration (SR) and distributed generation placement (SR-DGP) simultaneously. The proposed ISOS combined the simple quadratic interpolation (SQI) strategy into SOS to improve the search process. The ISOS was adopted to define the optimal system topology, location, and capacity of distributed generators (DGs) to minimize power losses. The proposed ISOS was evaluated on the 33-node and 69-node systems. The proposed ISOS successfully reduced the power losses by 73.1206% and 84.2861% for the 33-bus and 69-bus. Moreover, ISOS was also compared with other approaches, where ISOS obtained better results than other approaches for all test systems. Hence, ISOS showed its effectiveness in dealing with the SR-DGP problem.

This article deals with the analysis of the effects of passive control on the complex dynamics of a nonlinear damping gyroscope. After modeling the gyroscope dynamics under the influence of the control force, using the harmonic balance method, the amplitudes of the harmonic oscillations are determined. Subsequently, the Routh–Hurwitz criterion is used to analyze and determine the stability domains of the oscillations. The influence of the control force parameters on the amplitude of the oscillations is studied. The control of chaotic dynamics and the coexistence of gyroscope attractors are performed through bifurcation diagrams, Lyapunov exponents, phase portraits, and time series. Numerical simulations are used to confirm the effectiveness of the control force. This article revealed that the amplitude of the harmonic oscillations, the chaotic dynamics, and the coexistence of the attractors of the rotating gyroscope are better controlled when the latter vibrates in the opposite direction to the passive control force.