[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown motion. Its main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic noise. In traditional ways, the coupling weights depending on the communication structure are static. A new distributed controller is designed based on Riccati inequalities, while updating the coupling weights associated with the gain matrix by state errors between adjacent agents. By introducing time-varying coupling weights into this novel control law, the state errors between leader and followers asymptotically converge to the minimum value utilizing the local interaction. Through the Lyapunov directed method and Ito formula, the stability of the closed-loop system with the proposed control law is analyzed. Two simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

Consensus Control of Leader-Following Multi-Agent Systems in Directed Topology With Heterogeneous Disturbances

Adaptive odd impulsive consensus of multi-agent systems via comparison system method

Motivated by the increasing concerns over environmental challenges such as global warming and exhaustion of fossil-fuel reserves, the renewable energy industry has become the most sought-after source of electrical energy production worldwide. In this context, wind energy conversion systems (WECS) are one of the most dominant and fastest-growing technologies, playing an increasingly vital role in renewable power generation. To meet this growing demand and mitigate the vulnerability of WECS to various sets of internal/external faults, the cost-effectiveness and efficient power production of WECS must be ensured, which highlights the critical role of the control system. This topic has been intensively studied in the literature, and many control approaches have been developed to deal with the simultaneous enhancement of efficiency and reliability of WECS. However, sliding mode control (SMC) has proved its reliable and superior performance among most control strategies due to its inherent robustness to parametric uncertainties and disturbances and ease of design and implementation. Accordingly, this paper provides a comprehensive survey of existing literature on the application of SMC and its emerging modifications to address different control design problems for WECS. 

Sliding mode control of wind energy conversion systems: Trends and applications

A finite-time control strategy is proposed to solve the problem of position tracking control for a permanent magnet synchronous motor servo system. It can guarantee that the motor’s desired positio...

Position control for permanent magnet synchronous motor based on neural network and terminal sliding mode control

Robust consensus control for a class of second-order multi-agent systems with uncertain topology and disturbances

In the actual industrial production process, the method of adaptively tuning proportional–integral–derivative (PID) parameters online by neural network can adapt to different characteristics of different controlled objects better than the controller with PID. However, the commonly used microcontroller unit (MCU) cannot meet the application scenarios of real time and high reliability. Therefore, in this paper, a closed-loop motion control system based on BP neural network (BPNN) PID controller by using a Xilinx field programmable gate array (FPGA) solution is proposed. In the design of the controller, it is divided into several sub-modules according to the modular design idea. The forward propagation module is used to complete the forward propagation operation from the input layer to the output layer. The PID module implements the mapping of PID arithmetic to register transfer level (RTL) and is responsible for completing the output of control amount. The main state machine module generates enable signals that control the sequential execution of each sub-module. The error backpropagation and weight update module completes the update of the weights of each layer of the network. The peripheral modules of the control system are divided into two main parts. The speed measurement module completes the acquisition of the output pulse signal of the encoder and the measurement of the motor speed. The pulse width modulation (PWM) signal generation module generates PWM waves with different duty cycles to control the rotation speed of the motor. A co-simulation of Modelsim and Simulink is used to simulate and verify the system, and a test analysis is also performed on the development platform. The results show that the proposed system can realize the self-tuning of PID control parameters, and also has the characteristics of reliable performance, high real-time performance, and strong anti-interference. Compared with MCU, the convergence speed is far more than three orders of magnitude, which proves its superiority.

/pdf/a-design-of-fpga-based-neural-network-pid-controller-for-39s1m3hw.pdf

A Design of FPGA-Based Neural Network PID Controller for Motion Control System

Considering the non-rigid transmission connection between the wind turbine and the generator, their angular velocity is inconsistent. A DC-link voltage control model with uncertainties is established by a two-mass inertial model. The system uncertainties increase greatly compared with the single-mass inertial model, which aggravates a DC-link voltage accuracy. To suppress the uncertainties, the complementary sliding mode control (CSMC) is proposed to regulate the DC-link voltage since it has strong robustness. The equivalent controller for the voltage loop is obtained by the conservation principle of AC and DC side power, and the compensation controller for the uncertainties is designed by the saturation function. The CSMC system is analyzed to be asymptotic stability. The simulation and experiment results show that the CSMC system can suppress the system uncertainties, and obtain a more little steady-state error of the DC-link voltage, compared with PI control system.

/pdf/dc-link-voltage-regulation-for-wind-power-system-by-279ccfc42c.pdf

DC-Link Voltage Regulation for Wind Power System by Complementary Sliding Mode Control

Since the control system in a permanent magnet synchronous motor (PMSM) has uncertainties and disturbances, the switching gain is a key factor in effecting chattering in sliding mode control. An ad...

Yanwei Huang

Papers

Robust consensus control for a class of second-order multi-agent systems with uncertain topology and disturbances

A Design of FPGA-Based Neural Network PID Controller for Motion Control System

DC-Link Voltage Regulation for Wind Power System by Complementary Sliding Mode Control

Complementary sliding mode control with adaptive switching gain for PMSM

On reachable set estimation of multi-agent systems