scholarly journals A Controller Design Researh Based on the Cloud Model

2015 ◽  
Vol 16 (3) ◽  
pp. 531
Author(s):  
Feng Jie ◽  
Jingfang Wang
Keyword(s):  
Nonlinear Model ◽  
Control Structure ◽  
Controller Design ◽  
Design Method ◽  
Cloud Model ◽  
Uncertain Reasoning ◽  
Structure Model ◽  
Intelligent Controller

A novel control structure model is proposed based on cloud model for the first time．The structure model is a nonlinear model in nature, and it can be composed of a group of uncertain reasoning rules easily．NonIinear mapping characteristics of cloud model is analysed in this sudy, and the design method of the intelligent controller is presented based on the structure model, and some simulation examples are showed．

The Intelligent Controller Design of Parallel Online Mixing and Supplying Glue System

2010 ◽  
Vol 44-47 ◽  
pp. 4089-4093 ◽  
Author(s):  
Fan Hu Meng ◽  
Li Ping Sun ◽  
Liang Kuan Zhu
Keyword(s):  
Neural Network ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Favorable Effect ◽  
Intelligent Controller ◽  
Advantages And Disadvantages ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller

In this paper, a novel control method by using parallel online mixing and supplying technology for glue system with multi-input, strong coupling and nonlinear was provided. The neural network controller design method is adopted to design the intelligent controller, in which one as the main controller and the other one as the identifier to revise main controller. Both advantages and disadvantages of the two neural network controllers were analyzed. Simulation results showed that both methods obtained a more favorable effect than the traditional control method.

Neural Networks L2-Gain Controller Design for Nonlinear System

2011 ◽  
Vol 467-469 ◽  
pp. 1505-1510
Author(s):  
Dan Liu ◽  
Ni Hong Wang ◽  
Gui Ying Li
Keyword(s):  
Neural Network ◽  
Disturbance Rejection ◽  
Differential Inequality ◽  
Controller Design ◽  
Design Method ◽  
General Structure ◽  
The Neural Network ◽  
Network Weight ◽  
Finite Gain ◽  
L2 Gain

This paper proposes a new method that it uses the neural network to construct the solution of the Hamiltion-Jacobi inequality (HJ), and it carries on the optimization of the neural network weight using the genetic algorithm. This method causes the Lyapunov function to satisfy the HJ, avoides solving the HJ parital differential inequality, and overcomes the difficulty which the HJ parital differential inequality analysis. Beside this, it proposes a design method of a nonlinear state feedback L2-gain disturbance rejection controller based on HJ, and introduces general structure of L2-gain disturbance rejection controller in the form of neural network. The simulation demonstrates the design of controller is feasible and the closed-loop system ensures a finite gain between the disturbance and the output.

scholarly journals Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Actuator Saturation ◽  
Design Method ◽  
Fuzzy Model ◽  
The Stability ◽  
Interval Type ◽  
Takagi Sugeno

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

Study on Intelligent Controller Design of Flow Metrological Calibration System

2020 ◽  
Author(s):  
Xiong Yin ◽  
Kai Wen ◽  
Yan Wu ◽  
Lei Zhou ◽  
Jing Gong
Keyword(s):  
Neural Network ◽  
Natural Gas ◽  
Pid Controller ◽  
Controller Design ◽  
Calibration System ◽  
Calibration Process ◽  
Intelligent Controller ◽  
Flow Adjustment ◽  
Precise Adjustment ◽  
Valve Opening

Abstract In recent years, China ramped up imports of natural gas to satisfy the growing demand, which has increased the number of trade meters. Natural gas flowmeters need to be calibrated regularly at calibration stations to ensure their accuracy. Nowadays, the flow metrological calibration process is done by the operator manually in China, which is easy to be affected by personnel experience and proficiency. China is vigorously developing industry 4.0 and AI(artificial intelligence) technologies. In order to improve the calibration efficiency, a design scheme of intelligent controller for flow metrological calibration system is first proposed in this paper. The intelligent controller can replace the operator for process switching and flow adjustment. First, the controller selects the standard flowmeter according to the type of the calibrated flowmeter, and switches the calibration process. To accurately control the calibration flow for 180 seconds, the controller continuously adjusts the regulating valve with a sequence of commands to the actuator. These commands are generated by intelligent algorithm which is predefined in the controller. Process switching is operated automatically according to flowmeter calibration specifications. In order to reach the required flow point quickly, the flow adjustment is divided into two steps: preliminary adjustment and precise adjustment. For preliminary adjustment, a BP neural network will be built first using the field historical data and simulation results. This neural network describes the relationship between the valve-opening scheme and the calibration flow. Therefore, it could give a calibration flow as close as possible to the expected value during calibration. For precise adjustment, an adaptive PID controller is used. It could adjust the valve opening degree automatically to make sure the flow deviation meet the calibration requirements. Since the PID controller is a self-adaptive PID controller, the process of adjustment is very quick, which can reduce the calibration time largely. After each calibration, both the original neural network and the adaptive function of the controller will be updated to achieve the self-growth. With the information of the calibrated flowmeter, the entire calibration system can run automatically. The experiment in a calibration station shows that the intelligent controller can control the deviation of the flow value within 5% during 4∼5 minutes.

Altitude Controller Design for Quadcopter UAV

2015 ◽  
Vol 74 (1) ◽  
Author(s):  
Muhammad Zaki Mustapa
Keyword(s):  
Real Time ◽  
Attitude Control ◽  
Controller Design ◽  
Design Method ◽  
Time Windows ◽  
The Real ◽  
Data Acquisition Card ◽  
Aerial Vehicle ◽  
Hovering Control ◽  
Real Time Application

This paper discusses on attitude control of a quadcopter unmanned aerial vehicle (UAV) in real time application. Newton-Euler equation is used to derive the model of system and the model characteristic is analyzed. The paper describes the controller design method for the hovering control of UAV automatic vertical take-off system. In order to take-off the quadcopter and stable the altitude, PID controller has been designed. The scope of study is to develop an altitude controller of the vertical take-off as realistic as possible. The quadcopter flight system has nonlinear characteristics. A simulation is conducted to test and analyze the control performance of the quadcopter model. The simulation was conducted by using Mat-lab Simulink. On the other hand, for the real time application, the PCI-1711 data acquisition card is used as an interface for controller design which routes from Simulink to hardware. This study showed the controller designs are implemented and tuned to the real system using Real Time Windows Target approach by Mat-Lab Simulink.

Intelligent PD controller design for active suspension system based on robust model-free control strategy

2019 ◽  
Vol 233 (14) ◽  
pp. 4863-4880 ◽  
Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar
Keyword(s):  
Controller Design ◽  
Design Method ◽  
Active Suspension ◽  
Vehicle Speed ◽  
Pd Controller ◽  
Suspension Systems ◽  
Model Free ◽  
Robust Model ◽  
Road Disturbance ◽  
Model Free Control

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.

Multi Mode Vibration Control and Broder Band Motion Control of Three Dimensional Shaking Table

2005 ◽  
Author(s):  
Tsunehiro Wakasugi ◽  
Toru Watanabe ◽  
Kazuto Seto
Keyword(s):  
Vibration Control ◽  
Controller Design ◽  
Design Method ◽  
Three Dimensional ◽  
Design Procedure ◽  
Equation System ◽  
State Equation ◽  
Shaking Table ◽  
Mode Vibration ◽  
And Control

This paper deals with a new system design method for motion and vibration control of a three-dimensional flexible shaking table. An integrated modeling and controller design procedure for flexible shaking table system is presented. An experimental three-dimensional shaking table is built. “Reduced-Order Physical Model” procedure is adopted. A state equation system model is composed and a feedback controller is designed by applying LQI control law to achieve simultaneous motion and vibration control. Adding a feedforward, two-degree-of-freedom control system is designed. Computer simulations and control experiments are carried out and the effectiveness of the presented procedure is investigated. The robustness of the system is also investigated.

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