LPV Control of an Electronic Throttle

2013 ◽  
Author(s):  
Shupeng Zhang ◽  
Andrew White ◽  
Guoming Zhu ◽  
Jie J. Yang
Keyword(s):  
Gain Scheduling ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Battery Voltage ◽  
Electronic Throttle ◽  
Linear Parameter Varying ◽  
Time Varying Parameters ◽  
Linear Friction ◽  
Lpv Control ◽  
Improved Performance

In this paper, a discrete-time electronic throttle model was developed based upon the parameters obtained through system identification. To design gain-scheduling controllers using LPV (linear parameter varying) scheme, the throttle was modeled as an LPV system, where the vehicle battery voltage and the non-linear friction coefficient are the measurable time-varying parameters. Gain-scheduling H 2 controller was designed for the LPV throttle system using the linear matrix inequality (LMI) convex optimization approach. The designed controller is validated through simulations and show that the proposed controller provides improved performance over the baseline fixed gain controller.

Mixed H2/H∞ Observer-Based LPV Control of a Hydraulic Engine Cam Phasing Actuator

2011 ◽  
Author(s):  
Andrew White ◽  
Zhen Ren ◽  
Guoming Zhu ◽  
Jongeun Choi
Keyword(s):  
Engine Speed ◽  
Test Bench ◽  
Linear Models ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Linear Parameter Varying ◽  
The Family ◽  
Lpv Control ◽  
Lpv System ◽  
Variable Valve

In this paper, a series of closed-loop system identification tests was performed for a variable valve timing cam phaser system on a test bench to obtain a family of linear models for an array of engine speeds and oil pressures. Using engine speed and oil pressure as the system parameters, the family of linear models was translated into a linear parameter varying (LPV) system. The engine speed and oil pressure can be measured in real-time by these sensors equipped on the engine, thus allowing their use as scheduling parameters. An observer-based gain-scheduling controller for the obtained LPV system is then designed based on the numerically efficient convex optimization or linear matrix inequality (LMI) technique. Test bench results show the effectiveness of the proposed scheme.

Experimental Study on an Electric Variable Valve Timing Actuator: Linear Parameter Varying Modeling and Control

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Ali Khudhair Al-Jiboory ◽  
Guoming G. Zhu ◽  
Shupeng Zhang
Keyword(s):  
System Identification ◽  
Engine Speed ◽  
Gain Scheduling ◽  
Variable Valve Timing ◽  
Linear Parameter ◽  
Valve Timing ◽  
Battery Voltage ◽  
Linear Parameter Varying ◽  
Variable Valve ◽  
And Control

This paper presents experimental investigation results of an electric variable valve timing (EVVT) actuator using linear parameter varying (LPV) system identification and control. For the LPV system identification, a number of local system identification tests were carried out to obtain a family of linear time-invariant (LTI) models at fixed engine speed and battery voltage. Using engine speed and battery voltage as time-varying scheduling parameters, the family of local LTI models is translated into a single LPV model. Then, a robust gain-scheduling (RGS) dynamic output-feedback (DOF) controller with guaranteed H∞ performance was synthesized and validated experimentally. In contrast to the vast majority of gain-scheduling literature, scheduling parameters are assumed to be polluted by measurement noises and the engine speed and battery voltage are modeled as noisy scheduling parameters. Experimental and simulation results show the effectiveness of the developed approach.

A Nonlinear Gain-Scheduling Compensation Approach Using Parameter-Dependent Lyapunov Functions

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Fen Wu ◽  
Xun Song ◽  
Zhang Ren
Keyword(s):  
Lyapunov Functions ◽  
Gain Scheduling ◽  
Control Synthesis ◽  
Linear Matrix ◽  
Nonlinear Gain ◽  
Control Approach ◽  
Lpv Control ◽  
Gain Scheduling Control ◽  
Output Information ◽  
Parameter Dependent

This paper addresses the gain-scheduling control design for nonlinear systems to achieve output regulation. For gain-scheduling control, the linear parameter-varying (LPV) model is obtained by linearizing the plant about zero-error trajectories upon which an LPV controller is based. A key in this process is to find a nonlinear output feedback compensator such that its linearization matches with the designed LPV controller. Then, the stability and performance properties of LPV control about the zero-error trajectories can be inherited when the nonlinear compensator is implemented. By incorporating the exosystem, nominal input, and measured output information into the LPV model, the LPV control synthesis problem is formulated as linear matrix inequalities (LMIs) using parameter-dependent Lyapunov functions (PDLFs). Moreover, explicit formulae for the construction of the nonlinear gain-scheduled compensator have been derived to meet the linearization requirement. Finally, the validity of the proposed nonlinear gain-scheduling control approach is demonstrated through a ball and beam example.

scholarly journals Quadratic Stabilization of LPV System by an LTI Controller Based on ILMI Algorithm

2007 ◽  
Vol 2007 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Xie
Keyword(s):  
Controller Design ◽  
Linear Time ◽  
Admissible Solution ◽  
Linear Matrix ◽  
Linear Parameter Varying ◽  
Linear Time Invariant ◽  
Lpv Control ◽  
Lpv System ◽  
Time Invariant ◽  
Iterative Linear Matrix Inequality

A linear time-invariant (LTI) output feedback controller is designed for a linear parameter-varying (LPV) control system to achieve quadratic stability. The LPV system includes immeasurable dependent parameters that are assumed to vary in a polytopic space. To solve this control problem, a heuristic algorithm is proposed in the form of an iterative linear matrix inequality (ILMI) formulation. Furthermore, an effective method of setting an initial value of the ILMI algorithm is also proposed to increase the probability of getting an admissible solution for the controller design problem.

Linear Matrix Inequalities Approach to Input Covariance Constraint Control With Application to Electronic Throttle

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Ali Khudhair Al-Jiboory ◽  
Andrew White ◽  
Shupeng Zhang ◽  
Guoming Zhu ◽  
Jongeun Choi
Keyword(s):  
Convex Optimization ◽  
Control Problem ◽  
Linear Matrix Inequalities ◽  
Control Synthesis ◽  
Linear Matrix ◽  
Base Line ◽  
Optimization Approach ◽  
Matrix Inequalities ◽  
Electronic Throttle ◽  
Comparison Results

In this paper, the input covariance constraint (ICC) control problem is solved by convex optimization subject to linear matrix inequalities (LMIs) constraints. The ICC control problem is an optimal control problem that is concerned to obtain the best output performance subject to multiple constraints on the input covariance matrices. The contribution of this paper is the characterization of the control synthesis LMIs used to solve the ICC control problem. Both continuous- and discrete-time problems are considered. To validate our scheme in real-world systems, ICC control based on convex optimization approach was used to control the position of an electronic throttle plate. The controller performance compared experimentally with a well-tuned base-line proportional-integral-derivative (PID) controller. Comparison results showed that not only better performance has been achieved but also the required control energy for the ICC controller is lower than that of the base-line controller.

scholarly journals Gain Scheduling Controller Design for Two-Rotor Hovering System and its Experimental Verification

2006 ◽  
Vol 18 (5) ◽  
pp. 589-597
Author(s):  
Makoto Yamashita ◽  
◽  
Masami Saeki ◽  
Nobutaka Wada ◽  
Izumi Masubuchi ◽  
...  
Keyword(s):  
Flight Control ◽  
State Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Gain Scheduling ◽  
Linear Matrix ◽  
Feedback Gain ◽  
Convex Optimization Problem ◽  
Linear Parameter Varying ◽  
Lpv System

We propose two design methods of a gain scheduling controller for flight control of two-rotor hovering system. We first propose a method of converting whole dynamics of the hovering system to a linear parameter-varying (LPV) system at once. Secondly, we propose a method of linearizing longitudinal dynamics of the system exactly and converting remaining dynamics to an LPV system. In both cases, the state feedback gain scheduling controller is designed for the obtained LPV system by solving a convex optimization problem with linear matrix inequality (LMI) constraints. Experimental results show the effectiveness of the proposed methods.

scholarly journals An Improved Integral Inequality for Delay-Dependent Gain-Scheduled LPV Control

2021 ◽  
Vol 2 ◽  
Author(s):  
Shahin Tasoujian ◽  
Karolos Grigoriadis ◽  
Matthew Franchek
Keyword(s):  
Output Feedback ◽  
Closed Loop ◽  
Sufficient Conditions ◽  
Control Design ◽  
Gain Scheduling ◽  
Linear Matrix ◽  
Drug Infusion ◽  
Arterial Blood ◽  
Lpv Control ◽  
Delay Dependent

The present work examines the delay-dependent gain-scheduling feedback control with guaranteed closed-loop stability and induced L2 norm performance for continuous-time linear parameter-varying (LPV) systems with arbitrary time-varying delay. An extension of Lyapunov stability utilizing Krasovskii functionals is considered to derive stability analysis and synthesis conditions for delay-dependent dynamic output feedback LPV control design. The main challenges associated with this approach are selecting appropriate Lyapunov-Krasovskii functionals (LKFs) and finding efficient integral inequalities to bound the derivative of the LKF. Accordingly, a novel modified parameter-dependent LKF candidate along with an affine version of Jensen’s inequality bounding technique are employed leading to the derivation of less conservative sufficient conditions expressed in terms of convex linear matrix inequalities (LMIs). The proposed methodology is compared with past work in the literature in terms of conservatism reduction and performance improvement through a numerical example. Finally, the application of the proposed output-feedback LPV control design is evaluated on the automated mean arterial blood pressure (MAP) regulation in critical patient resuscitation via vasoactive drug infusion. Closed-loop simulation results are presented to illustrate the potential of the introduced LPV gain-scheduling design to provide MAP set-point tracking in the presence of disturbances and varying input delays.

Active Rejection of Harmonic Disturbances with Nonstationary Harmonically Related Frequencies Using Varying-Sampling-Time LPV Control

2016 ◽  
Vol 248 ◽  
pp. 19-26
Author(s):  
Xin Yu Shu ◽  
Pablo Ballesteros ◽  
Christian Bohn
Keyword(s):  
Vibration Control ◽  
Fundamental Frequency ◽  
Sampling Time ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Noise And Vibration ◽  
Active Noise ◽  
Lpv Control ◽  
Parameter Varying ◽  
Time Linear

This paper presents a method for the active noise and vibration control (ANC/AVC) of harmonically related nonstationary disturbances using varying-sampling-time linear parameter-varying (LPV) controller. The frequencies are assumed to be known and varying within given ranges and they are multiples of one fundamental frequency.

scholarly journals Fault Tolerant Control Design For Polytopic LPV Systems

2007 ◽  
Vol 17 (1) ◽  
pp. 27-37 ◽  
Author(s):  
Mickael Rodrigues ◽  
Didier Theilliol ◽  
Samir Aberkane ◽  
Dominique Sauter
Keyword(s):  
Output Feedback ◽  
Fault Tolerant ◽  
Output Feedback Control ◽  
Control Design ◽  
Fault Tolerant Control ◽  
Necessary Condition ◽  
Linear Matrix ◽  
Linear Parameter Varying ◽  
Lpv Systems ◽  
Static Output

Fault Tolerant Control Design For Polytopic LPV SystemsThis paper deals with a Fault Tolerant Control (FTC) strategy for polytopic Linear Parameter Varying (LPV) systems. The main contribution consists in the design of a Static Output Feedback (SOF) dedicated to such systems in the presence of multiple actuator faults/failures. The controllers are synthesized through Linear Matrix Inequalities (LMIs) in both fault-free and faulty cases in order to preserve the system closed-loop stability. Hence, this paper provides a new sufficient (but not necessary) condition for the solvability of the stabilizing output feedback control problem. An example illustrates the effectiveness and performances of the proposed FTC method.

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