Reduced-Order Controller Design via Iterative Identification and Control

2003 ◽  
Vol 9 (1) ◽  
pp. 105-117 ◽  
Author(s):  
Antonio Sala ◽  
Alicia Esparza
Keyword(s):  
Controller Design ◽  
Iterative Identification ◽  
Reduced Order ◽  
And Control

A New Iterative Identification and Control Method of Closed-Loop Power System Based on Ambient Signals

2015 ◽  
Vol 798 ◽  
pp. 261-265
Author(s):  
Miao Yu ◽  
Chao Lu
Keyword(s):  
Power System ◽  
Closed Loop ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Stability Margin ◽  
System Stability ◽  
Iterative Identification ◽  
Effective Performance ◽  
And Control

Identification and control are important problems of power system based on ambient signals. In order to avoid the model error influence of the controller design, a new iterative identification and control method is proposed in this paper. This method can solve model set and controller design of closed-loop power system. First, an uncertain model of power system is established. Then, according to the stability margin of power system, stability theorem is put forward. And then controller design method and the whole algorithm procedure are given. Simulation results show the effective performance of the proposed method based on the four-machine-two-region system.

Integrated Structure Decomposition, Optimization and Control Design

2007 ◽  
Author(s):  
Shaoluo L. Butler ◽  
Anoop K. Dhingra
Keyword(s):  
Finite Element ◽  
Multiobjective Optimization ◽  
Controller Design ◽  
Design System ◽  
Element Analysis ◽  
Reduced Order ◽  
Stability Robustness ◽  
Entire Structure ◽  
Structure Decomposition ◽  
And Control

In this paper, an integrated optimization, controller design and reduced order finite element modeling based approach is presented for structural design. The proposed approach involves structure decomposition, subcontroller design, system controller assembly, and multiobjective optimization. The concept of structure decomposition with compatible and incompatible interfaces is presented for a control/optimum system problem, and developed for problems with compatible interfaces involving substructure controller design and multiobjective optimization. The substructure information obtained through finite element analysis is synthesized to reconstruct a reduced order model for the entire structure. Based on SSSC (Substructure Synthesis-Substructure Controller), a controller is designed for each substructure. The global controller is obtained by assembling all subcontrollers designed at the substructure level. A multiobjective optimum formulation is presented based on structure decomposition and controller design. Four objective functions are simultaneously optimized. These include a stability robustness index, structural weight, controller energy, and a controller performance index. Numerical examples are presented to demonstrate the effectiveness of the proposed methodology. Results obtained using the proposed approach are compared with those obtained from optimization of the entire structure.

scholarly journals An iterative identification algorithm and its convergence analysis of closed-loop power system based on ambient signals

2021 ◽  
Vol 2121 (1) ◽  
pp. 012004
Author(s):  
Weijie Du ◽  
Miao Yu ◽  
Jinglin Li ◽  
Shouzhi Zhang ◽  
Jingxuan Hu
Keyword(s):  
Power System ◽  
Closed Loop ◽  
Stable Equilibrium ◽  
Controller Design ◽  
Dynamic Performance ◽  
Model Identification ◽  
Identification Algorithm ◽  
Iterative Identification ◽  
Model Set ◽  
And Control

Abstract Identification and control are important problems of closed-loop power system. At present, most studies are separate identification methods. This paper studies an online and real-time integrated identification method, which can solve the problems of model set and controller design of closed-loop power system. This paper investigates a new iterative identification algorithm and its convergence problem of closed-loop power system based on ambient signals. Firstly, the whole algorithm procedure is given. This algorithm uses the iterative process under the closed-loop condition, which combines system model identification with controller design. Then the complementary of model identification and control design has been realized. Secondly, because of the dynamic performance of the iterative identification algorithm, it has characteristics described from the perspective of a partitioned dynamic system. Regard each iterative identification step as a state node. In this situation, the algorithm guarantees all the state nodes converge to the Lyapunov stable equilibrium. Finally, the simulation results show the correctness and effectiveness of the proposed method through the simulation of a power system with four-machine-two-region.

Solving Vibration Control Problems Using Reduced Order Models for Flexible Structures: A Genetic Algorithm Approach

1997 ◽  
Author(s):  
Sourav Kundu ◽  
Kentaro Kamagata ◽  
Shigeru Sugino ◽  
Takeshi Minowa ◽  
Kazuto Seto
Keyword(s):  
Genetic Algorithm ◽  
Vibration Control ◽  
Controller Design ◽  
Fitness Function ◽  
Flexible Structures ◽  
Design Solution ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Fitness Value ◽  
Genetic Algorithm Approach

Abstract A Genetic Algorithm (GA) based approach for solution of optimal control design of flexible structures is presented in this paper. The method for modeling flexible structures with distributed parameters as reduced-order models with lumped parameters, which has been developed previously, is employed. Due to some restrictions on controller design it is necessary to make a reduced-order model of the structure. Once the model is established the design of flexible structures is considered as a feedback search procedure where a new solution is assigned some fitness value for the GA and the algorithm iterates till some satisfactory design solution is achieved. We propose a pole assignment method to determine the evaluation (fitness) function to be used by the GA to find optimal damping ratios in passive elements. This paper demonstrates the first results of a genetic algorithm approach to solution of the vibration control problem for practical control applications to flexible tower-like structures.

scholarly journals An ADRC Method for Noncascaded Integral Systems Based on Algebraic Substitution Method and Its Structure

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhijian Huang ◽  
Yudong Li ◽  
Yihua Liu ◽  
Wenbo Sui ◽  
Guichen Zhang
Keyword(s):  
Controller Design ◽  
Integral Form ◽  
State Variables ◽  
Control Effect ◽  
Substitution Method ◽  
Integral System ◽  
Numerical Example ◽  
Disturbance Rejection Control ◽  
Integral Systems ◽  
And Control

The Active Disturbance Rejection Control (ADRC) prefers the cascaded integral system for a convenient design or better control effect and takes it as a typical form. However, the state variables of practical system do not necessarily have a cascaded integral relationship. Therefore, this paper proposes an algebraic substitution method and its structure, which can convert a noncascaded integral system of PID control into a cascaded integral form. The adjusting parameters of the ADRC controller are also demonstrated. Meanwhile, a numerical example and the oscillation control of a flexible arm are demonstrated to show the conversion, controller design, and control effect. The converted system is proved to be more suitable for a direct ADRC control. In addition, for the numerical example, its control effect for the converted system is compared with a PID controller under different disturbances. The result shows that the converted system can achieve a better control effect under the ADRC than that of a PID. The theory is a guide before practice. This converting method not only solves the ADRC control problem of some noncascaded integral systems in theory and simulation but also expands the application scope of the ADRC method.

Sign in / Sign up

Export Citation Format

Share Document