A nonlinear structural experiment platform with adjustable plastic hinges: analysis and vibration control

Li, Luyu,Song, Gangbing,Ou, Jinping Techno-Press 2013 Smart Structures and Systems, An International Jou Vol.11 No.3

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

A nonlinear structural experiment platform with adjustable plastic hinges: analysis and vibration control

Luyu Li,Gangbing Song,Jinping Ou 국제구조공학회 2013 Smart Structures and Systems, An International Jou Vol.11 No.3

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

Nonlinear robust control of a quadrotor for point tracking based on nonlinear disturbance observer

Young-Cheol Choi,Hyo-Sung Ahn 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10

In this paper, a nonlinear robust control problem is addressed for point tracking of quadrotor. The nonlinear robust controller is designed based on nonlinear disturbance observer which estimates external disturbances of quadrotor. Proposed controller can be divided into two parts which are nonlinear controller and robust controller. Basically, the nonlinear controller is designed to track the desired point and the robust controller is added to compensate external disturbances which estimated by the designed nonlinear disturbance observer. Simulation results show the performance of the designed nonlinear robust controller and disturbance observer.

자율무인잠수정의 비선형 PD심도제어

안종갑,고건,소명옥 한국수산해양교육학회 2019 水産海洋敎育硏究 Vol.31 No.4

The purpose of this research is to study AUV (Autonomous Underwater Vehicle) depth control using a nonlinear controller which is more adaptive and robust than existing linear controllers. For depth control of AUV, nonlinear P controller is designed as pitch controller in the outer loop and nonlinear PD controller is designed as pin controller in the inner loop. The parameter gains of each controllers are tuned through RCGAs (Real-Coded Genetic Algorithms), one of the optimization techniques, and ITAE (Integral of Time-weighted Absolute Error) is used as an evaluation function. By using the proposed nonlinear controller, depth control of AUV nonlinear model is performed through computer simulation. The designed nonlinear controller shows satisfied performance for target depth tracking, continuous disturbance, and noise.

Application of Nonlinear PID Controller in Superconducting Magnetic Energy Storage

Xiaotao Peng,Shijie Cheng,Jinyu Wen 대한전기학회 2005 International Journal of Control, Automation, and Vol.3 No.2

As a new control strategy, the Nonlinear PID (NLPTD) controller has been introduced successfully in power systems. The controller is free of planting model groundwork during the design procedure and is therefore able to be achieved quite simply. In this paper, a nonlinear PID controller used for a superconducting magnetic energy storage (SMES) unit connected to a power system is proposed. The purpose of designing such a controller is to improve the stability of the power system in a relatively wide operation range. The design procedure takes into account the active and reactive power cooperative control scheme as well as the simple structure so as to be more apt to practical utilization. Simulation is carried out to investigate the performance of the proposed controller in a high order nonlinear power system model under the MATLAB environment. The results show satisfactory performance and good robustness of the controller. The feasibility of the controller is testified as well.

비선형 시스템을 위한 적응슬라이딩모드제어기의 설계

이진국 忠州大學校 2007 한국교통대학교 논문집 Vol.42 No.-

In this paper, we proposed controller design method which is more proper to control nonlinear system, and that method is from sliding mode control theory which is one of the best nonlinear control theory. In this paper, we tried to design an adaptive sliding mode controller with self-tuning that computed the sliding mode gain and the thickness of the boundary layer for real time control. This method rejected the control signal chattering, guaranteed the robustness of system uncertainty, minimized the trajectory errors by appling the sliding mode gain and the thickness of the boundary layer at the same time. As so, the controller might have the learning ability of treatment technique and repeated operation for structured and unstructured uncertainties of control model such that variation of parameter, load, disturbance, and that became robustness controller that can apply in the nonlinear systems. Proposed control theory in this paper have proved by mathematical analysis, and have verified by computer simulation.

Multi Layer Perceptron을 이용한 See Saw System 균형제어

박동현(Park dong hyun),이충현(Lee chung hyun),공나경(Gong na gyeong),조홍기(Jo hong gi),김연호(Kim yeon ho),이인수(In soo Lee) 한국정보기술학회 2021 Proceedings of KIIT Conference Vol.2021 No.11

균형 제어는 선박, 항공, 로봇 등 많은 시스템에서 중요하게 다뤄지고 있다. 대부분의 균형 제어시스템은 비선형적이고 복잡하여 제어기를 설계하는 과정이 복잡하고 성능을 좋게 하기가 어렵다. 최근에 이러한 비선형 제어기에서 추출한 데이터를 가지고 인공신경망을 이용하여 지능제어기를 설계하는 연구가 진행되고 있다. 이 논문에서는 See Saw 시스템의 균형제어를 비선형 제어기를 통해 제어하고 그 데이터를 통하여 MLP(Multi Layer Perceptron) 제어기를 설계하여 두 제어기의 성능을 비교하고 개선된 성능을 확인한다. Balance control is important in many systems such as ships, aviation, and robots. Most balance control systems are nonlinear and complex, making the process of designing a controller complex and difficult to improve performance. Recently, research is being conducted to design an intelligent controller using an artificial neural network with data extracted from such a nonlinear controller. In this paper, we implement the balance control of the See Saw System through a nonlinear controller. And then, we design the MLP(Multi Layer Perceptron) controller with data which extract nonlinear controller. As a result We verify that performance of MLP controller is better than nonlinear controller.

Speed Control for the Pitching Axis of a Remote Sensing Camera Using an Improved Active Disturbance Rejection Controller

Bing-You Liu 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.9

This paper proposes the theoretical framework and the experimental application of an improved active disturbance rejection controller (ADRC) to speed control for the pitching axis of a remote sensing camera. Mechanical model of the pitching axis, mechatronics model of the speed control system for the pitching axis, and speed algorithm model of a permanent magnet synchronous motor are established. Control rates of the extended state observer (ESO) and the nonlinear state error feedback (NSEF) of the traditional ADRC are improved using a new nonlinear function. The nonlinear dynamics, model uncertainty, and external disturbances of the speed control system are extended to a new state, and the improved ESO is implemented to observe this state. The overtime variation of the speed control system is predicted and compensated for in real time using the improved ESO. The nonlinear integration method is adopted to nonlinearly combine the differential and the error differential by the improved NSEF. Subsequently, high-quality control is provided to the system. Simulation and experimental verification for the speed control system for the pitching axis of a remote sensing camera are conducted. Results show the effectiveness of the proposed controller.

Application of Nonlinear PID Controller in Superconducting Magnetic Energy Storage

Peng Xiaotao,Cheng Shijie,Wen Jinyu Institute of Control 2005 International Journal of Control, Automation, and Vol.3 No.S

As a new control strategy, the Nonlinear PID (NLPID) controller has been introduced successfully in power systems. The controller is free of planting model groundwork during the design procedure and is therefore able to be achieved quite simply. In this paper, a nonlinear PID controller used for a superconducting magnetic energy storage (SMES) unit connected to a power system is proposed. The purpose of designing such a controller is to improve the stability of the power system in a relatively wide operation range. The design procedure takes into account the active and reactive power cooperative control scheme as well as the simple structure so as to be more apt to practical utilization. Simulation is carried out to investigate the performance of the proposed controller in a high order nonlinear power system model under the. MATLAB environment. The results show satisfactory performance and good robustness of the controller. The feasibility of the controller is testified as well.

Double-command fuzzy control of a nonlinear CSTR

Morteza Mohammadzaheri,Lei Chen 한국화학공학회 2010 Korean Journal of Chemical Engineering Vol.27 No.1

In this research, double-command control of a nonlinear chemical system is addressed. The system is a stirred tank reactor; two flows of liquid with different concentrations enter the system through two valves and another flow exits the tank with a concentration between the two input concentrations. Fuzzy logic was employed to design a model-free double-command controller for this system in the simulation environment. In order to avoid output chattering and frequent change of control command (leading to frequent closing-opening of control valves, in practice) a damper rule is added to the fuzzy control system. A feedforward (steady state) control law is also derived from the nonlinear mathematical model of the system to be added to feedback (fuzzy) controller generating transient control command. The hybrid control system leads to a very smooth change of control input, which suits real applications. The proposed control system offers much lower error integral, control command change and processing time in comparison with neuro-predictive controllers.