scholarly journals Iterative LQG Controller Design Through Closed-Loop Identification

1996 ◽  
Vol 118 (2) ◽  
pp. 366-372 ◽  
Author(s):  
Min-Hung Hsiao ◽  
Jen-Kuang Huang ◽  
David E. Cox
Keyword(s):  
Kalman Filter ◽  
State Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
Open Loop ◽  
The State ◽  
Magnetic Suspension ◽  
Loop Model ◽  
Closed Loop Identification ◽  
Noise Statistics

This paper presents an iterative LQG controller design approach for a linear stochastic system with an uncertain openloop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQG controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

Pseudo-random binary sequence closed-loop system identification error with integration control

2009 ◽  
Vol 223 (6) ◽  
pp. 877-884 ◽  
Author(s):  
Z Ren ◽  
G G Zhu
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Binary Sequence ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Identification Error ◽  
Closed Loop Identification ◽  
Integral Controller

This paper studies the closed-loop system identification (ID) error when a dynamic integral controller is used. Pseudo-random binary sequence (PRBS) q-Markov covariance equivalent realization (Cover) is used to identify the closed-loop model, and the open-loop model is obtained based upon the identified closed-loop model. Accurate open-loop models were obtained using PRBS q-Markov Cover system ID directly. For closed-loop system ID, accurate open-loop identified models were obtained with a proportional controller, but when a dynamic controller was used, low-frequency system ID error was found. This study suggests that extra caution is required when a dynamic integral controller is used for closed-loop system identification. The closed-loop identification framework also has significant effects on closed-loop identification error. Both first- and second-order examples are provided in this paper.

A novel trigger mechanism for a dual-filter to improve the state-of-charge estimation of lithium-ion batteries

2021 ◽  
pp. 1-12
Author(s):  
Chuanxiang Yu ◽  
Rui Huang ◽  
Zhaoyu Sang ◽  
Shiya Yang
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Open Loop ◽  
The State ◽  
State Of Charge ◽  
Loop Model ◽  
Trigger Mechanism ◽  
Soc Estimation

Abstract State-of-charge (SOC) estimation is essential in the energy management of electric vehicles. In the context of SOC estimation, a dual-filter based on the equivalent circuit model represents an important research direction. The trigger for parameter filter in a dual filter has a significant influence on the algorithm, despite which it has been studied scarcely. The present paper, therefore, discusses the types and characteristics of triggers reported in the literature and proposes a novel trigger mechanism for improving the accuracy and robustness of SOC estimation. The proposed mechanism is based on an open-loop model, which determines whether to trigger the parameter filter based on the model voltage error. In the present work, particle filter (PF) is used as the state filter and Kalman filter (KF) as the parameter filter. This dual filter is used as a carrier to compare the proposed trigger with three other triggers and single filter algorithms, including PF and unscented Kalman filter (UKF). According to the results, under different dynamic cycles, initial SOC values, and temperatures, the root-mean-square error of the SOC estimated using the proposed algorithm is at least 34.07% lower than the value estimated using other approaches. In terms of computation time, the value is 4.67%. Therefore, the superiority of the proposed mechanism is demonstrated.

Controller Design for See-Saw Systems

2014 ◽  
Vol 898 ◽  
pp. 680-683
Author(s):  
Hai Yan Wang
Keyword(s):  
Control Theory ◽  
State Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
The State ◽  
Feedback Controller ◽  
System Model ◽  
Asymptotically Stable ◽  
Closed Loop System ◽  
State Feedback Controller

The control theory has widely application in many fields such as industrial and agricultural. A class of see-saw system model will be studied in this paper. Using the theory of pole assignment, we will design the state feedback controller, such that the closed-loop system is asymptotically stable. At the same time, using the tool of MATLAB, the model of closed see-saw system will be simulated and analyzed. It reveals the state regularity of see-saw system.

State Feedback Robust H∞ Control for Generalized Discrete System and Simulation

2013 ◽  
Vol 467 ◽  
pp. 621-626
Author(s):  
Chen Fang ◽  
Jiang Hong Shi ◽  
Kun Yu Li ◽  
Zheng Wang
Keyword(s):  
Discrete System ◽  
State Feedback ◽  
Closed Loop ◽  
The State ◽  
Linear Matrix ◽  
Sufficient Condition ◽  
Matrix Inequalities ◽  
Parameter Uncertainties ◽  
Robust Controller ◽  
Closed Loop Systems

For a class of uncertain generalized discrete linear system with norm-bounded parameter uncertainties, the state feedback robust control problem is studied. One sufficient condition for the solvability of the problem and the state feedback robust controller are obtained in terms of linear matrix inequalities. The designed controller guarantees that the closed-loop systems is regular, causal, stable and satisfies a prescribed norm bounded constraint for all admissible uncertain parameters under some conditions. The result of the normal discrete system can be regarded as a particular form of our conclusion. A simulation example is given to demonstrate the effectiveness of the proposed method.

Impedance Reduction Controller Design for Mechanical Systems

2013 ◽  
Author(s):  
Hanseung Woo ◽  
Kyoungchul Kong
Keyword(s):  
Case Studies ◽  
Closed Loop ◽  
Controller Design ◽  
Mechanical Impedance ◽  
Open Loop ◽  
Mechatronic Systems ◽  
Closed Loop Systems ◽  
Guaranteed Stability ◽  
Reaction Forces ◽  
Definition Of

Safety is one of important factors in control of mechatronic systems interacting with humans. In order to evaluate the safety of such systems, mechanical impedance is often utilized as it indicates the magnitude of reaction forces when the systems are subjected to motions. Namely, the mechatronic systems should have low mechanical impedance for improved safety. In this paper, a methodology to design controllers for reduction of mechanical impedance is proposed. For the proposed controller design, the mathematical definition of the mechanical impedance for open-loop and closed-loop systems is introduced. Then the controllers are designed for stable and unstable systems such that they effectively lower the magnitude of mechanical impedance with guaranteed stability. The proposed method is verified through case studies including simulations.

State Feedback Controller Design for CSTR Based on Kalman Filter

2013 ◽  
Vol 404 ◽  
pp. 657-662 ◽  
Author(s):  
Hao Wu ◽  
Ze Biao Shan ◽  
Yao Wu Shi
Keyword(s):  
Kalman Filter ◽  
State Feedback ◽  
Controller Design ◽  
Dynamic Performance ◽  
Chemical Species ◽  
Operating Conditions ◽  
Feedback Controller ◽  
Continuous Stirred Tank Reactor ◽  
State Feedback Controller ◽  
Cstr System

Due to operating conditions and economic factors, it may be either practical or feasible to measuring the chemical species directly in the continuous stirred tank reactor (CSTR) system which is a typical nonlinear, multi-variables, time-varying system. So, a concentration estimate strategy of components based on Kalman filter is proposed, with which the measurement of temperature conversion can be reconstructed. Then the state feedback controller is designed based on the estimated strategy. Simulation results show that the proposed control scheme is efficient and the system contains good dynamic performance.

Model Predictive Control and Controller Parameter Optimisation of Combustion Instabilities

2019 ◽  
Vol 36 (2) ◽  
pp. 185-194 ◽  
Author(s):  
I. Yazar ◽  
F. Caliskan ◽  
R. Vepa
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Combustion Process ◽  
Open Loop ◽  
Loop Model ◽  
Parameter Optimisation ◽  
Direct Adaptive Control ◽  
The Cost ◽  
Adaptive Control Algorithm

Abstract In this paper the application of model predictive control (MPC) to a two-mode model of the dynamics of the combustion process is considered. It is shown that the MPC by itself does not stabilize the combustor and the control gains obtained by applying the MPC algorithms need to be optimized further to ensure that the phase difference between the two modes is also stable. The results of applying the algorithm are compared with the open loop model amplitude responses and to the closed loop responses obtained by the application of a direct adaptive control algorithm. It is shown that the MPC coupled with the cost parameter optimisation proposed in the paper, always guarantees the closed loop stability, a feature that may not always be possible with an adaptive implementations.

Closed-loop identification of carotid sinus baroreflex open-loop transfer characteristics in rabbits

1997 ◽  
Vol 273 (2) ◽  
pp. H1024-H1031 ◽  
Author(s):  
T. Kawada ◽  
M. Sugimachi ◽  
T. Sato ◽  
H. Miyano ◽  
T. Shishido ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Closed Loop ◽  
Transfer Functions ◽  
Carotid Sinus ◽  
Open Loop ◽  
Parametric Models ◽  
Efferent Nerve ◽  
Transfer Characteristics ◽  
Carotid Sinus Baroreflex ◽  
Closed Loop Identification

In the circulatory system, a change in blood pressure operates through the baroreflex to alter sympathetic efferent nerve activity, which in turn affects blood pressure. Existence of this closed feedback loop makes it difficult to identify the baroreflex open-loop transfer characteristics by means of conventional frequency domain approaches. Although several investigators have demonstrated the advantages of the time domain approach using parametric models such as the autoregressive moving average model, specification of the model structure critically affects their results. Thus we investigated the applicability of a nonparametric closed-loop identification technique to the carotid sinus baroreflex system by using an exogenous perturbation according to a binary white-noise sequence. To validate the identification method, we compared the transfer functions estimated by the closed-loop identification with those estimated by open-loop identification. The transfer functions determined by the two identification methods did not differ statistically in their fitted parameters. We conclude that exogenous perturbation to the baroreflex system enables us to estimate the open-loop baroreflex transfer characteristics under closed-loop conditions.

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