scholarly journals Robust Gain-Scheduled PID Control: A Parameter Dependent BMI Solution

2020 ◽  
Vol 20 (1) ◽  
pp. 156-167
Author(s):  
Pengyuan Shao ◽  
Jin Wu ◽  
Songhui Ma
Keyword(s):  
Robust Control ◽  
Pid Control ◽  
Optimization Problem ◽  
Simple Structure ◽  
Control Method ◽  
Time Varying ◽  
Linear Parameter Varying ◽  
Parameter Dependent ◽  
Gain Scheduled ◽  
Static Output

AbstractIn control practices, problems of parametric or time-varying uncertainties must be dealt with. Robust control based on norm theory and convex and non-convex optimization algorithms is a powerful tool to solve these problems in theory, but it is employed rarely in applications. In most engineering cases, Proportional-Integration-Derivative (PID) control is still the most popular method for its easy-to-tune and controllable properties. The control method proposed in this paper integrates the PID control into robust control formulation as a robust Structured Static Output Feedback (SSOF) problem of Linear-Parameter-Varying (LPV) systems, which can be converted into a Parameter Dependent Bilinear-Matrix-Inequality (PDBMI) optimization problem. A convex-concave decomposition based method is given to solve the proposed PDBMI problem. The proposed solution has a simple structure in PID form and can guarantee stability and robustness of the system being controlled in the whole operation range with less conservativeness than existing solution.

Robust Control Method Based on Machine Learning for Boiler Combustion System

2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang
Keyword(s):  
Robust Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Support Vector ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
On Line ◽  
Control Output

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.

Research on Adaptive PID Control for Load Simulator with Varying Load

2014 ◽  
Vol 568-570 ◽  
pp. 1031-1035
Author(s):  
Ju Tian ◽  
Yao Chen
Keyword(s):  
Pid Control ◽  
Simple Structure ◽  
Control Method ◽  
Parameter Tuning ◽  
Hardware In The Loop ◽  
Tuning Method ◽  
Hydraulic Load ◽  
Variation Characteristics ◽  
Load Simulator ◽  
Adaptive Pid Control

The electro-hydraulic load simulator is an important equipment for aircraft hardware-in-the-loop simulation. An adaptive PID control method for compensating extraneous torque with simple structure and easy to implement is proposed according to the variation characteristics of load gradient in the load simulator. The control parameter tuning method is also given.

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

Reduction in the Number of Gain-Scheduling Parameters Using Dimensional Transformation

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Haftay Hailu ◽  
Sean Brennan
Keyword(s):  
Linear Time ◽  
Gain Scheduling ◽  
Linear Parameter Varying ◽  
Linear Time Invariant ◽  
Lti System ◽  
Gain Scheduled Controller ◽  
Parameter Dependent ◽  
Time Invariant ◽  
Linear Parameter Varying System ◽  
Gain Scheduled

A method is presented that can often reduce the number of scheduling parameters for gain-scheduled controller implementation by transformation of the system representation using parameter-dependent dimensional transformations. In some cases, the reduction in parameter dependence is so significant that a linear parameter-varying system can be transformed to an equivalent linear time invariant (LTI) system, and a simple example of this is given. A general analysis of the parameter-dependent dimensional transformation using a matrix-based approach is then presented. It is shown that, while some transformations simplify gain scheduling, others may increase the number of scheduling parameters. This work explores the mathematical conditions causing an increase or decrease in varying parameters resulting from a given transformation, thereby allowing one to seek transformations that most reduce the number of gain-scheduled parameters in the controller synthesis step.

Fractional Order LQR for Optimal Robust Control of a Simple Structure

2007 ◽  
Author(s):  
Abdollah Shafieezadeh ◽  
Keri Ryan ◽  
YangQuan Chen
Keyword(s):  
Robust Control ◽  
Control Problem ◽  
Fractional Order ◽  
Simple Structure ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Fractional Damping ◽  
Fractional Order Control

This study combines fractional order control with linear quadratic regulator (LQR) for optimal robust control of a simple civil structure. As a first attempt, the purpose of this paper is to demonstrate that, when fractional damping is introduced, additional benefits can be obtained over the best traditional control method. The control problem of this paper can be used as a simple benchmark example to test new control ideas before applying to more complicated models.

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