Active absorption of acoustic waves using state‐space model and optimal control theory

1995 ◽  
Vol 97 (2) ◽  
pp. 1078-1087 ◽  
Author(s):  
Zhen Wu ◽  
Vijay K. Varadan ◽  
Vasundara V. Varadan ◽  
Kwang Y. Lee
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
State Space ◽  
Acoustic Waves ◽  
Optimal Control Theory ◽  
State Space Model ◽  
Active Absorption ◽  
Space Model

Optimal control method on assembly precision for a remanufactured car engine based on state space model

2016 ◽  
Vol 36 (4) ◽  
pp. 460-472 ◽  
Author(s):  
Jing Hu ◽  
Yuan Zhang ◽  
Maogen GE ◽  
Mingzhou Liu ◽  
Liu Conghu ◽  
...  
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Control Method ◽  
State Space Model ◽  
The State ◽  
Content Type ◽  
Space Model ◽  
Optimal Control Method ◽  
Assembly Error ◽  
Assembly Precision

Purpose The optimal control on reassembly (remanufacturing assembly) error is one of the key technologies to guarantee the assembly precision of remanufactured product. However, because of the uncertainty existing in remanufactured parts, it is difficult to control assembly error during reassembly process. Based on the state space model, this paper aims to propose the optimal control method on reassembly precision to solve this problem. Design/methodology/approach Initially, to ensure the assembly precision of a remanufactured car engine, this paper puts forward an optimal control method on assembly precision for a remanufactured car engine based on the state space model. This method takes assembly workstation operation and remanufactured part attribute as the input vector reassembly status as the state vector and assembly precision as the output vector. Then, the compensation function of reassembly workstation operation input vector is calculated to direct the optimization of the reassembly process. Finally, a case study of a certain remanufactured car engine crankshaft is constructed to verify the feasibility and effectiveness of the method proposed. Findings The optimal control method on reassembly precision is an effective technology in improving the quality of the remanufactured crankshaft. The average qualified rate of the remanufactured crankshaft increased from 83.05 to 90.97 per cent as shown in the case study. Originality/value The optimal control method on the reassembly precision based on the state space model is available to control the assembly precision, thus enhancing the core competitiveness of the remanufacturing enterprises.

Optimal Control Deconvolution for Velocity Meter Signals

1988 ◽  
Vol 110 (1) ◽  
pp. 17-23
Author(s):  
P. M. Clarkson ◽  
J. K. Hammond
Keyword(s):  
Experimental Data ◽  
Optimal Control ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Measurement Noise ◽  
Deconvolution Method ◽  
System Parameters ◽  
Space Model ◽  
Inaccurate Estimation

A method of deconvolution has been developed which uses the techniques of optimal control. The application of the technique to velocity meter signals is presented. It is shown that provided a state-space model of the transducer dynamics can be obtained the method can provide effective deconvolution even when the data are corrupted by measurement noise. As well as the deconvolution method and the control of the measurement noise the formation of the state-space model and the effects of inaccurate estimation of system parameters are considered. Results are presented using both simulated and experimental data.

Optimal control strategy of state feedback control for surface-mounted PMSM drives based on auto-tuning of seeker optimization algorithm

2021 ◽  
pp. 1-21
Author(s):  
Junhao Cao ◽  
Xiaodong Sun ◽  
Xiang Tian
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Optimization Algorithm ◽  
State Feedback ◽  
State Space Model ◽  
The State ◽  
Load Torque ◽  
Space Model ◽  
Auto Tuning ◽  
Seeker Optimization Algorithm

This paper focus on a state feedback controller (SFC)-based optimal control scheme for surface-mounted permanent-magnet synchronous motor (SPMSM) with auto-tuning of controller built on seeker optimization algorithm (SOA). First, based on the nonlinear state-space model of SPMSM, voltage feedforward compensation is used to design a linear SFC. Then in order to guarantee the steady performance in speed and current, integral models considering the errors of rotor speed and current response in d-axis are added in the state space model of SPMSM. Furthermore, by statically decoupling the load torque in the state equation, feedforward compensation is implemented on the load torque to improve the dynamic performance of the controller. The load torque is estimated using disturbance observer with reasonable parameter selection. Then, with the consideration of the search capacity of seeker optimization algorithm (SOA), it is adopted to acquire matrix coefficient of the presented controller. Furthermore, in order to suppress the speed overshoot, a penalty term is introduced to the fitness index. The performance of the proposed method has been validated experimentally and compared with the conventional method under different conditions.

scholarly journals The Cascade Control of Natural Gas Pipeline Systems

2019 ◽  
Vol 9 (3) ◽  
pp. 481
Author(s):  
Kai Wen ◽  
Jing Gong ◽  
Yan Wu
Keyword(s):  
Natural Gas ◽  
Control Theory ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Gas Pipeline ◽  
Cascade Control ◽  
Gas Pipelines ◽  
Space Model ◽  
Natural Gas Pipelines

With the boost of natural gas consumption, an automatic gas pipeline scheduling method is required to replace the dispatchers in decision making. Since the state space model is the fundamental work of modern control theory, it is possible that the classical controller synthesis method can be used for the complicated gas pipeline controller design. In this paper, a cascade control algorithm is proposed based on the state space model that is used for the transient flow simulation of the natural gas pipelines. A linear quadratic regulator is designed following the classical optimal control theory. Finally, the transient process with different control methods shows the effectiveness of the cascade control using information of the entire pipeline. According to the hardware configuration of natural gas pipelines, automatic scheduling process is ready to deploy as one step to the intelligent natural gas pipelines.

The Linear Optimal Control for the Mechanical Vibration Based on Remanufacturing Repaired

2013 ◽  
Vol 823 ◽  
pp. 47-51
Author(s):  
Ling Liu
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Vibration Suppression ◽  
State Space Model ◽  
State Regulation ◽  
Order System ◽  
Modal Control ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Space Model

It is used by the piezoelectric ceramics sheet of positive-inverse piezoelectric effect in a set of copper alloy remanufacturing repair cantilever vibration system as the research object in the paper.A state space model have been generated on the cantilever beem mechanical structure of dynamics finite element modeling and degrees of freedom dynamic polycondensation.It is inhibited effectively when a cantilever beam subjected to external transient pulse disturbance caused by first order, two order and higher order system mode vibration,by using the linear quadratic optimal control of two state regulation for the detection of position feedback independent modal control on the basis of the state-space model. Software is used to simulate active vibration control effect.The simulation results show that the mode control inhibited have excellent effects for the repaired cantilever vibration, also analysed on the modal control parameters for the vibration suppression effect.

A Nonlinear Optimal Control Approach for Multi-DOF Brachiation Robots

2021 ◽  
Author(s):  
G. Rigatos ◽  
M. Abbaszadeh ◽  
K. Busawon ◽  
Z. Gao ◽  
J. Pomares
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
State Space ◽  
Control Method ◽  
State Space Model ◽  
Nonlinear Optimal Control ◽  
Time Step ◽  
Control Approach ◽  
Space Model ◽  
Optimal Control Approach

This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-space model, as well as because of underactuation, the control problem of these robots is nontrivial. The dynamic model of the brachiation robots undergoes first approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the Jacobian matrices of the brachiation robots’ state-space model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the brachiation robots, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the brachiation robots, under moderate variations of the control inputs.

Observer Design for Active Suspension Control for Passenger Cars

2006 ◽  
Author(s):  
Federico Cheli ◽  
Ferruccio Resta ◽  
Edoardo Sabbioni
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
State Space ◽  
Optimal Control Theory ◽  
State Vector ◽  
The State ◽  
Observer Design ◽  
Passenger Cars ◽  
Suspension Control ◽  
System States

An observer for controlled suspension is presented in this paper based on acceleration measurements. The proposed observer allows to estimate the system states and can be profitably used in a state-derivative feed-back control. This kind of control, designed in the reciprocal-state-space framework (RSS), is based on the optimal control theory and consists in minimizing the derivative of the state vector instead of the state vector itself.

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