The Control of Nonlinear Thermal System with Large Delay Time Using Feedback Linerarization Strategy

Seiyed Hamid Zareh,Ali-Fellah Jahromi,Amir Ali Khayyat 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

This paper first will describe the Feedback Linearization Method when the Proportional-Integral-Derivative (PID) controllers are inactive in procedures that have large delay time (LDT) in transfer stage. Therefore in those states, Feedback Linearization has a better performance with respect to PID controllers. Feedback linearization is a common approach used in controlling nonlinear systems by an equivalent linear system through a change of variables and a suitable control input. This nonlinear control strategy studies how to apply existing linear methods to these more general control systems. Eventually, a nonlinear thermal system, which circulates hot air to keep the temperature of a chamber constant have been linearized and control by Feedback Linearization theory and finally the results are analyzed and compared.

Nonlinear Dynamic Modeling and Control of a Small-Scale Helicopter

Baoquan Song,James K. Mills,Yunhui Liu,Caizhi Fan 제어·로봇·시스템학회 2010 International Journal of Control, Automation, and Vol.8 No.3

A test bench for experimental testing of the attitude control of a small-scale helicopter is constructed. A nonlinear model with 10 states is developed for this experimental setup. The unknown model parame-ters are estimated using the extended Kalman filter with flight test data of the helicopter operating on the test bench. In this work, it is proved that the nonlinear helicopter dynamic model may be globally feedback linearized using the dynamic feedback linearization technique. In order to satisfy multiple closed-loop performance specifications simultaneously, a controller is proposed by applying the Convex Integrated Design (CID) method to the feedback linearized model. Finally, the controller is tested in simulation demonstrating the closed-loop performance of the proposed controller.

Nonlinear Optimal Control of Three-Phase Inverter Based on State Feedback Exact Linearization Theory

Han Xiaoyan 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3

Due to the nonlinear and strongly coupled mathematical model of the three-phase inverter in the synchronously rotating dq coordinate system, it is difcult to deal with the design of controller. Herein, the precise linearization theory of state feedback is applied to construct an afne nonlinear model of the three-phase inverter. Although the dynamic response of the inverter can be improved by the state feedback control, the steady-state characteristics are not as satisfactory as expected. To solve this problem, an integral control plus state feedback scheme is proposed to build an augmented control system for the three-phase inverter. As for control parameter tuning, the linear quadratic regulator (LQR) method is usually not considered as the efective solution to voltage source inverter (VSI) systems because of its inability to ensure reference voltage command tracking. Although the linear quadratic tracker (LQT) method performs well in tracking, its control efect may be compromised by the nonlinear behavior of the system. The three-phase inverter augmented control system proposed in this paper not only addresses the disadvantages of the LQR method in command tracking, but also eliminates the steady-state error, which enables it to perform as well in tracking as the LQT method.

Distributed Robust Control for Nonlinear Systems using Wireless Neural Control

Wen Ren,Bugong Xu 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.5

This paper is concerned with the synthesis of a class of nonlinear system over the wireless neural control network (WNCN) which refers to a group of neuron nodes interacting with each other by radio connection. The nonlinear system is modeled by a standard neural network model (SNNM) which is the interconnection of a linear dynamic system and bounded static nonlinear operators. The WNCN treats itself as a fully distributed nonlinear dynamic controller. The unreliable wireless communication links within WNCN are modeled by fading channels. By constructing appropriate discrete-time Lyapunov function, the global asymptotic stability of the closed-loop system is discussed in particular for the cases with stochastic perturbations induced by packet losses. The connection weights among the neuron nodes that guarantee stability of the system can be obtained by solving a convex optimization problem with some linear matrix inequality (LMI) constraints. A numerical example is given to illustrate the correctness and effectiveness of the theoretical results.

Fast pulse current control of multiphase pulse power supply converters using feedback linearization

Zhibao Yuan,Pingping Wen,Haiping Xu,Zengquan Yuan 전력전자학회 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.12

To improve the performance of multiphase pulse power supply (MPPS) converters, a current control strategy based on feedback linearization (FL) is proposed for flat-top current control by using an average model of the MPPS converter in thisstudy. A nonlinear state function model of a MPPS converter is presented and transformed to a linearized and decoupled form with the input–output feedback linearization technique. Based on the linearized system, simple linear controllers are designed to regulate the current among different phases and output current of the MPPS, which significantly reduces the difficulty in controller design and tuning. Moreover, a pre-charge method is adopted to improve current rising edge, which improves the current response of the flat-top current control. To test its effectiveness, the proposed strategy is employed in a 10 kW MPPS prototype. When compared to the conventional PI-based current control for MPPS converters, the proposed strategy provides a better dynamic performance in terms of current regulation and its flexibility can be extended to any of the paralleled phases of a MPPS system.

Trajectory Linearization Control for a Miniature Unmanned Helicopter

Bing Zhu,Wei Huo 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.2

Trajectory linearization control (TLC) approach is applied to design a nonlinear trajectory tracking controller for a miniature unmanned helicopter. The controller is based on nonlinear model derived from Newton-Euler equations, with collective and cyclic pitches being regarded as actual controls. Via model simplifications, the nonlinear helicopter model can be transformed into a cascaded form including four subsystems. Corresponding with the simplified cascaded structure, the proposed controller is constructed by synthesizing TLC designs for subsystems. Each of them includes designs of a pseudo-inversion and an error regulator. A summarized TLC algorithm for the unmanned helicopter is listed briefly after the detailed controller design process. Simulation results are provided to demonstrate performances of the closed-loop system.

A Novel Discrete-time Nonlinear Model Predictive Control Based on State Space Model

Carlos Sotelo,Antonio Favela-Contreras,Francisco Beltrán-Carbajal,Graciano Dieck-Assad,Pedro Rodríguez-Cañedo,David Sotelo 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.6

This paper proposes a novel finite dimensional discrete-time Nonlinear Model Predictive Control. This technique is based on discrete-time state-space models, Taylor series expansion for prediction and performance index optimization. Furthermore, the technique extends the concept of the Lie derivative for the discrete time case using Euler backwards method. The performance validation for the discrete-time Nonlinear Model Predictive Control uses the simulation of a single-link flexible joint robot and the inverted pendulum. Comparison of the proposed finite dimensional discrete-time Nonlinear Model Predictive Control technique with Feedback Linearization Control is also discussed. Analytical and numerical results show excellent performances for both, the single-link flexible joint and inverted pendulum controllers using the proposed discrete-time Nonlinear Model Predictive Control technique.

Trajectory Tracking Control of Quadrotor UAV

Sang-hyun Lee,Seung Hoon Kang,Youdan Kim 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10

Quadrotor is an attractive flying subject in aerospace control fields since it has a simple structure, but complex dynamics. Control engineers have developed various algorithms to control this subtle vehicle. However, it is still very difficult to control quadrotor because of its high nonlinearities. In this paper, the new controller is proposed for the guidance and control of the quadrotor. An attitude controller and position controller are designed based on feedback linearization. In this way, the under-actuated system is divided into two fully-actuated subsystems. Furthermore, 1-2-3 type Euler angles are used so that the quadrotor position can be controlled freely regardless of the yaw angle. As a result, the quadrotor system can be exactly linearized reflecting most of the information that original dynamics has. To show the performance of this controller, numerical simulation is performed for the position tracking.

Output-Feedback Stabilization for Fuzzy Descriptor Systems with Neutral Time Delays

Min Kook Song,Jin Bae Park,Wei Jang,Young Hoon Joo 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10

This paper investigates the stability and stabilization problem for nonlinear systems with neutral time delays represented by the Takagi-Sugeno (T.S) fuzzy model. First, the T-S fuzzy models with neutral time-delay are present and the stability conditions are derived in form of linear matrix inequalities (LMIs). Then a stabilization approach for nonlinear neutral systems through fuzzy output feedback controller is proposed. It shows that the analysis results provide an efficient technique for the design for fuzzy output feedback controllers. Sufficient conditions for the existence of fuzzy output feedback gain of the neutral time-delay systems are derived through the numerical solution of derived LMIs.

A Discrete-time Integral Sliding Mode Predictive Control Using Iterative Dynamic Linearization Data Model

Mingdong Hou,Weigang Pan,Yaozhen Han 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.7

The current study presents a data-driven integral sliding mode predictive control method for a category of discrete-time repetitive nonlinear systems. At first, a compact form of iterative dynamic linearization (IDL) technology is utilized to establish an IDL data model. Then, considering the time and iterative domain simultaneously, an iterative integral sliding mode surface is constructed to establish an iterative integral sliding mode controller. The stability of the presented control strategy is then demonstrated through a precise mathematical analysis. Furthermore, to further reduce the control error, an iterative integral sliding mode predictive control strategy is established using the model predictive control. Since the proposed method is a data-driven control scheme, it only employs the online I/O data for parameter estimation and controller design. The effectiveness and monotonic convergence of the proposed schemes are evaluated through simulations. Comparative results with the data-driven optimal iterative learning controller (DDOILC) and the enhanced DDOILC indicate that the presented controller can provide a faster convergence and less tracking error.