Developing a state space model for a turbocharged diesel engine using the subspace identification method

2011 ◽  
Vol 225 (12) ◽  
pp. 1692-1706 ◽  
Author(s):  
K Nikzadfar ◽  
A H Shamekhi
Keyword(s):  
Diesel Engine ◽  
State Space ◽  
State Space Model ◽  
Subspace Identification ◽  
Turbocharged Diesel Engine ◽  
Space Model ◽  
Identification Method ◽  
Subspace Identification Method

Closed-Loop Subspace Identification of MIMO Motion System With Flexible Structures for Motion Control

2016 ◽  
Author(s):  
Tao Huang ◽  
Kaiming Yang ◽  
Rong Cheng ◽  
Haihua Mu ◽  
Yu Zhu
Keyword(s):  
State Space ◽  
Motion Control ◽  
Closed Loop ◽  
State Space Model ◽  
Flexible Structures ◽  
Subspace Identification ◽  
Space Model ◽  
Identification Method ◽  
Motion System ◽  
Safety Case

In this paper, we study the closed-loop subspace identification of MIMO motion system with flexible structures. The fundamental objective of identification experiment is to achieve the state space model for motion control. The model with flexible structures of the motion system is analyzed and deduced to the form of state space model, which is composed with rigid modes and flexible modes. As the stability and safety case, the closed-loop subspace identification method is employed. The proposed identification method is suitable for modern control algorithms to construct space state model. The rigid and flexible modes are obtained and updated by the modal approach. Identification experiment is carried on the industrial wafer stage, which is the typical MIMO motion system with flexible structures. The results of experiment verify the feasibility and validity of the proposed identification method.

An Effective System Identification Method of Small-Scale Unmanned Helicopter

2014 ◽  
Vol 598 ◽  
pp. 442-452
Author(s):  
Yu Zhu Liu ◽  
Fei Hu
Keyword(s):  
Simulated Annealing ◽  
State Space ◽  
Prediction Error ◽  
Simulated Annealing Algorithm ◽  
State Space Model ◽  
Small Scale ◽  
Unmanned Helicopter ◽  
Space Model ◽  
Identification Method ◽  
Error Method

In order to control an unmanned helicopter accurately and reliably, it is necessary to have a precise mathematical model of its dynamics. This paper presents a new timedomain identification method and process for full state space model of small-scale unmanned helicopters. The identification method is called ISAcwPEM (Improved Simulated Annealing combined with Prediction Error Method), which is not sensitive to initial point selection and doesn’t require frequency-sweeping inputs. Firstly, the primary parameters to be identified are selected by model sensitivity analysis. After that, the improved simulated annealing algorithm runs in a distributed computing platform to figure out a 13-order state space model of the SJTU T-REX700E small-scale unmanned helicopter (consisting of a cruise modal and a hover modal). Then the iterative Prediction Error Method (PEM) is used to optimize the model. In addition, the time-delay term and the trim term are estimated and added to the model. Finally, the effectiveness of the identification method is well validated by real outdoor flight experimental results.

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