Time-Domain Fixed-Structure Closed-Loop Model Identification of an Unstable Multivariable Maglev Nanopositioning System

Huzefa Shakir,Won-jong Kim 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.1

This paper presents improved empirical representations of a general class of open-loop unstable systems using closed-loop system identification. A multi-axis magnetic-levitation (maglev) nanopositioning system with an extended translational travel range is used as a test model to verify the closed-loop system-identification method presented in this paper. A closed-loop identification technique employing a known controller structure is used for model identification and validation. Direct and coupling transfer functions (TFs) are then derived from the experimental input-output time sequences and the knowledge of controller dynamics. A persistently excited signal with a bandwidth in the frequency range of interest is used as a reference input. An order-reduction algo-rithm is developed to obtain TFs with predefined orders, which gives the closest match in the fre-quency range of interest without missing any significant plant dynamics. The entire analysis is per-formed in the discrete-time domain in order to avoid any errors due to continuous-to-discrete-time conversion and vice versa. Continuous-time TFs are used only for order-reduction and performance analysis of the identified TFs. Experimental results are presented in the time as well as frequency domains to verify the accuracy of the identified plant TFs. These results also demonstrate the effectiveness of the developed closed-loop identification method in meeting all of the three core objectives—(i) reduction in cross-axial coupling from 9.213 μm to 0.911 μm in translation and from 22.03 μrad to 1.353 μrad in rotation, (ii) large range motion capability with a travel range of ±2.9 mm, and (iii) improved robust stability.

Experiment on closed-loop subspace model identification of an unstable underactuated system

Hiroshi Oku,Shun Ushida 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

We report an experimental result on closed-loop subspace model identification of a cart-inverted pendulum system. Such a system as mentioned here is known as a typical unstable under actuated system, which is impossible of open-loop identification. Furthermore, any conventional SISO identification is not applicable to this systemsince this system is of single input and two outputs. Therefore, in this case, closed-loop subspace model identification is the only way of identification. Bode diagrams will show that the reisfairly good agreement between an identified model obtained from closed-loop subspace identification and an initial model used for a stabilizing feedback controller at the frequency important for control of this inverted pendulum.

Closed-loop Subspace Identification of Dual-rate Non-uniformly Sampled System under MPC with Zone Control

ByungJun Park,오세규,이종민 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.8

Frequent changes in process dynamics make re-identification of a dynamic model prerequisite for sustainable application of model predictive control. When the process needs to comply with a particular operating range for product specification or safety requirement, the model should be re-identified in closed-loop. In addition to potentially poor exciting signal for the identification, another challenge is that many industrial processes are multi-rate systems whose variables have different sampling intervals. This paper proposes a re-identification method for dual-rate non-uniformly sampled systems under closed-loop with a MPC controller by lifting the original system. The proposed identification method provides accurate and realistic model compared to the model used before the identification is conducted. We also compare the identified model and the existing model by applying to MPC.

Modeling of a radio-controlled car with camera based on system identification

Hiroshi Kusano,Koichi Hidaka 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

This paper describes a modeling of movement object. A auto driving of the car is studied to reduce traffic accidents and traffic jam in late years. The experiment tries there control with the radio controlled car which did movement same as a car. The control of the radio controlled car controls the steering voltage on speed uniformity this time. The control method usually uses model predictive control. The precision of the model becomes important for the model predictive control. To give the precision of model, a system model of straight line and curve line is necessary for the model of the radio controlled car. Since these movements of the radio controlled car are different, these model do not become the same models. The model of the car on curve needs closed loop identification with impossibility by open loop identification. Therefore, we examine the model of straight line using closed loop identification model to consider proper model.

Recurrent-neural-network-based identification of a cascade hydraulic actuator for closed-loop automotive power transmission control

유승한,Jin-Oh Hahn 대한기계학회 2012 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.26 No.5

"By virtue of its ease of operation compared with its conventional manual counterpart, automatic transmissions are commonly used as automotive power transmission control system in today’s passenger cars. In accordance with this trend, research efforts on closed-loop automatic transmission controls have been extensively carried out to improve ride quality and fuel economy. State-of-the-art power transmission control algorithms may have limitations in performance because they rely on the steady-state characteristics of the hydraulic actuator rather than fully exploit its dynamic characteristics. Since the ultimate viability of closed-loop power transmission control is dominated by precise pressure control at the level of hydraulic actuator, closed-loop control can potentially attain superior efficacy in case the hydraulic actuator can be easily incorporated into model-based observer/controller design. In this paper, we propose to use a recurrent neural network (RNN) to establish a nonlinear empirical model of a cascade hydraulic actuator in a passenger car automatic transmission, which has potential to be easily incorporated in designing observers and controllers. Experimental analysis is performed to grasp key system characteristics, based on which a nonlinear system identification procedure is carried out. Extensive experimental validation of the established model suggests that it has superb one-step-ahead prediction capability over appropriate frequency range, making it an attractive approach for model-based observer/controller design applications in automotive systems."

Modeling and a Simple Multiple Model Adaptive Control of PMSM Drive System

강태수,김민석,이사영,김영철 전력전자학회 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2

This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).

Modeling and a Simple Multiple Model Adaptive Control of PMSM Drive System

Taesu Kang,Min-Seok Kim,Sa Young Lee,Young Chol Kim 전력전자학회 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2

This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).

Modeling and a Simple Multiple Model Adaptive Control of PMSM Drive System

Kang, Taesu,Kim, Min-Seok,Lee, Sa Young,Kim, Young Chol The Korean Institute of Power Electronics 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2

This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).

Versatility of Particle Swarm Optimization in Identification for Continuous-Time Systems

Toshiharu Sugie,Takashi Wada 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

This paper shows the versatility of the Particle Swarm Optimization, which attracts alot of attention recently in the evolutionary computation are a due to its empirical evidence of its superiority, in the are a of continuous-time system identification. First, a method to identify(possibly nonlinear) continuous-time systems is shown, which uses the Particle Swarm Optimization to minimize the mean square prediction error. Second, its effectiveness is demonstrated through various numerical examples which include time-delay systems, closed loop ones and nonlinear ones.

폐루프 식별을 이용한 MLAC 제어기의 새로운 설계방법

김재진(Jae-Jin Kim),박기웅(Ki-Woung Park) 대한전기학회 2012 정보 및 제어 심포지엄 논문집 Vol.2012 No.10