The Design of Space Scanning Mirror Control System Based on Optimal Tracking Controller

2012 ◽  
Vol 546-547 ◽  
pp. 790-794
Author(s):  
Wen Bo Sui ◽  
Ke Fei Song ◽  
Pei Jie Zhang
Keyword(s):  
Control System ◽  
State Space ◽  
Pid Controller ◽  
Simulation Experiment ◽  
State Space Model ◽  
System State ◽  
Scanning Mirror ◽  
Optimal Tracking ◽  
Space Model ◽  
Tracking Controller

Control system of space scanning mirror has high requirement of scanning accuracy. The use of optimal tracking controller, instead of traditional PID controller, can effectively improve the scanning accuracy of space scanning mirror control system. State space model of the control system is established; the control system based on optimal tracking controller is designed; simulation experiment of the control system based on optimal tracking controller is carried out. The simulation result, in comparison with the system based on a PID controller, shows that the scanning mirror control system using optimal tracking controller instead of PID controller has higher scanning accuracy and faster response.

scholarly journals Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Gergely Takács ◽  
Tomáš Polóni ◽  
Boris Rohal’-Ilkiv
Keyword(s):  
Control System ◽  
Vibration Control ◽  
State Space ◽  
Real Time ◽  
Cantilever Beam ◽  
State Space Model ◽  
Model Parameters ◽  
Extended Kalman Filtering ◽  
Space Model ◽  
Continuous State

This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

Analysis of a Hydrofoil Craft with a Suspension System

2020 ◽  
Author(s):  
Michel Touw ◽  
Jacob Lotz ◽  
Ido Akkerman
Keyword(s):  
Experimental Data ◽  
Control System ◽  
State Space ◽  
State Space Model ◽  
Suspension System ◽  
Future Research ◽  
Passive System ◽  
Height Control ◽  
Space Model ◽  
Front Wing

In this paper we investigate the efficacy of augmenting, or replacing, an active height control system for a submerged hydrofoil with a passive system based on springs and dampers. A state-space model for submerged hydrofoils is formulated and extended to allow for a suspension at the front wing, aft wing or both wings. The model is partially verified by obtaining results in the fixed-wing limit and comparing these with experimental data from the MARIN Foiling Future Demonstrator. In the current study we limit ourselves to translational springs, only allowing suspension motion in the heave direction. This results in unfavorable behavior: either the motions increased or the system becomes unstable. It is therefore recommended for future research to try rotational springs.

Recursive Immuno-Inspired Algorithm for Time Variant Discrete Multivariable Dynamic System State Space Identification

2015 ◽  
Vol 5 (2) ◽  
pp. 69-100 ◽  
Author(s):  
Mateus Giesbrecht ◽  
Celso Pascoli Bottura
Keyword(s):  
Dynamic System ◽  
State Space ◽  
System Modeling ◽  
State Space Model ◽  
Small Time ◽  
Time Interval ◽  
System State ◽  
Space Model ◽  
Starting Point ◽  
Benchmark System

In this paper a recursive immuno inspired algorithm is proposed to identify time variant discrete multivariable dynamic systems. The main contribution of this paper has as starting point the idea that a multivariable dynamic system state space model can be seen as a point in a space defined by all possible matrices quadruples that define a state space model. With this in mind, the time variant discrete multivariable dynamic system modeling is transformed in an optimization problem and this problem is solved with an immuno inspired algorithm. To do that the inputs given to the system and the resulting outputs are divided in small sets containing data from small time intervals. These sets are defined as time windows, and for each window an immuno inspired optimization algorithm is applied to find the state space model that better represents the system at that time interval. The initial candidate solutions of each time interval are the ones of the last interval. The immuno inspired algorithm proposed in this paper has some modifications to the original Opt-AINet algorithm to deal with the constraints that are natural from the system identification problem and these modifications are also contributions of this paper. The method proposed in this paper was applied to identify a time variant benchmark system, resulting in a time variant model. The outputs estimated with this model are closer to the benchmark system outputs than the outputs estimated with models obtained by other known identification methods. The Markov parameters of the variant benchmark system are also reproduced by the time variant model found with the new method.

Research on Control System of Pump and Valve Parallel Connection

2010 ◽  
Vol 44-47 ◽  
pp. 1751-1757 ◽  
Author(s):  
Jing Luo ◽  
Chun Geng Sun ◽  
Peng Zhang ◽  
Sen Liu ◽  
Song Tao Wu
Keyword(s):  
Control System ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Parallel Connection ◽  
Space Model ◽  
Valve System ◽  
Simulation Results ◽  
Valve Control

This paper introduces the composition of pump and valve control system of parallel connection and the output flux of pump and valve is distributed optimally. Then, establish the state-space model of pump and valve system, the system is simulated by Simlink and AMESim software, the simulation results obtained.

Modal Analysis of a Motorcycle Motion During Braking for its Stabilization Control System Design

2013 ◽  
Author(s):  
Shintaroh Murakami ◽  
Hidekazu Nishimura
Keyword(s):  
Control System ◽  
Modal Analysis ◽  
State Space ◽  
State Space Model ◽  
State Space Models ◽  
Control System Design ◽  
Space Model ◽  
Stabilization Control ◽  
Mode Separation ◽  
Nonlinear State

In this paper, modal motion of a motorcycle during braking is analyzed to clarify influence of a stabilization control system designed to the modes. A thirteen degree-of-freedom nonlinear state-space model including rider’s motion is linearized around an equilibrium point of quasi-steady state straight running with constant deceleration, and the modal analysis is carried out using the linearized state-space models. Conducting mode separation and performing simulations utilizing the linearized state-space models, the behavior of the modes including capsize, weave, and wobble modes are analyzed. The characteristic of each mode is clarified from relationships among the impulsive responses of simulations and the eigenvectors obtained from eigenanalysis. Furthermore, the influence of a motorcycle stabilization control system to each mode is analyzed from simulation results.

Output Prediction Method Based on Model and its Application in Power Systems

2011 ◽  
Vol 219-220 ◽  
pp. 986-989
Author(s):  
Ke Luo ◽  
Hong Li Lv
Keyword(s):  
Power Systems ◽  
State Space ◽  
Prediction Error ◽  
State Space Model ◽  
Prediction Method ◽  
Open Loop ◽  
System Model ◽  
System State ◽  
Space Model ◽  
Wide Area Damping Controller

An output prediction method based on state space model is proposed to overcome the poor reliability of the prediction method that does not use system model. The open-loop state observer is established based on the system state space model. Then the output prediction model is built in which the prediction error is used as input and a correction module is also contained. The module is used to correct the prediction error, and then the current predicted output can be obtained by the model from the delayed output. At last, a wide-area damping controller in power systems based on output prediction is designed to verify the effectiveness of the method.

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