Control System Synthesis Based on Plant Test Data

1995 ◽  
Vol 117 (4) ◽  
pp. 484-489
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Control System ◽  
Test Data ◽  
Closed Loop ◽  
Explicit Knowledge ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
System Synthesis ◽  
Control System Synthesis

A correlation equation is established between open-loop test data and the desired closed-loop system characteristics permitting control system synthesis to be done on the basis of a numerical approach using experimental data. The method is applicable when the system is linear-time-invariant and open-loop stable. The major merits of the algorithm are two-fold: 1) Arbitrary placement of the closed-loop system equation is possible, and 2) explicit knowledge of an open-loop system model is not needed for the controller synthesis.

Robust nonfragile observer-based H2/H∞ controller

2016 ◽  
Vol 24 (4) ◽  
pp. 722-738 ◽  
Author(s):  
Atta Oveisi ◽  
Tamara Nestorović
Keyword(s):  
Control System ◽  
Real Time ◽  
Closed Loop ◽  
Linear Time ◽  
Sufficient Conditions ◽  
Loop System ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Real Time System ◽  
Structured Uncertainty

A robust nonfragile observer-based controller for a linear time-invariant system with structured uncertainty is introduced. The [Formula: see text] robust stability of the closed-loop system is guaranteed by use of the Lyapunov theorem in the presence of undesirable disturbance. For the sake of addressing the fragility problem, independent sets of time-dependent gain-uncertainties are assumed to be existing for the controller and the observer elements. In order to satisfy the arbitrary H2-normed constraints for the control system and to enable automatic determination of the optimal [Formula: see text] bound of the performance functions in disturbance rejection control, additional necessary and sufficient conditions are presented in a linear matrix equality/inequality framework. The [Formula: see text] observer-based controller is then transformed into an optimization problem of coupled set of linear matrix equalities/inequality that can be solved iteratively by use of numerical software such as Scilab. Finally, concerning the evaluation of the performance of the controller, the control system is implemented in real time on a mechanical system, aiming at vibration suppression. The plant under study is a multi-input single-output clamped-free piezo-laminated smart beam. The nominal mathematical reduced-order model of the beam with piezo-actuators is used to design the proposed controller and then the control system is implemented experimentally on the full-order real-time system. The results show that the closed-loop system has a robust performance in rejecting the disturbance in the presence of the structured uncertainty and in the presence of the unmodeled dynamics.

Closed-Loop System Identification Based on Data Correlation

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Hassene Jammoussi ◽  
Matthew Franchek ◽  
Karolos Grigoriadis ◽  
Martin Books
Keyword(s):  
System Identification ◽  
Instrumental Variables ◽  
Closed Loop ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Engine Operation ◽  
Single Input Single Output

A closed-loop system identification method is developed to estimate the parameters of a single input single output (SISO) linear time invariant system (LTI) operating within a feedback loop. The method uses the reference command in addition to the input–output data and establishes a correlation framework to structure the system. The correlation-based method is capable of delivering consistent estimates provided that the specific conditions on the signals are met. The method parallels the instrumental variables four step algorithm (IV4) and is comprised of three steps. First a model is estimated using cross correlation calculations between the reference input signal and the control and measured output signals. In the second step, a prefilter is identified to reduce estimation bias. In the final step, the prefilter, the instrumental variables and the measured signals are employed to estimate the final model. A consistency proof is provided for the proposed estimation process. The method is demonstrated on two examples. The first uses data collected from a diesel engine operation, and an open-loop model relating fueling to engine speed is sought. The identification process is complicated by the presence of nonmeasurable external torque disturbances and stochastic sensor noise. The second example uses data obtained from a time domain simulation of a closed-loop system where high levels of nonmeasured noise and disturbances were considered and a comparison with existing methods is made.

A Biological Feedback Control System with Electronic Input: The Artificially Closed Femur-Tibia Control System of Stick Insects

1986 ◽  
Vol 120 (1) ◽  
pp. 369-385 ◽  
Author(s):  
G. WEILAND ◽  
U. BÄSSLER ◽  
M. BRUNNER
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Closed Loop ◽  
Stick Insect ◽  
Open Loop ◽  
Loop System ◽  
Chordotonal Organ ◽  
Closed Loop System ◽  
Open Loop System ◽  
Stick Insects

An experimental arrangement was constructed which is based on the open-loop femur-tibia control system of two stick insect species (Carausius morosus and Cuniculina impigra). It could be artificially closed in the following way: the position of the tibia was measured by an optical device and this value was used to drive a penmotor which moved the receptor apodeme of the femoral chordotonal organ in the same way as in intact animals. This arrangement allows direct comparison of the behaviour of the open-loop and the closed-loop system as well as introducing an additional delay. The Carausius system has a phase reserve of only 30°-50° and the factor of feedback control approaches 1 between 1 and 2 Hz. This agrees with the observation that an additional delay of 70–200 ms produces long-lasting oscillations of 1–2 Hz. The Cuniculina system has a larger phase reserve and consequently a delay of 200 ms produced no oscillations. All experiments show that extrapolation from the open-loop system to the closed-loop system is valid, despite the non-linear characteristics of the loop. Consequences for servo-mechanisms during walking and rocking movements are discussed.

Application of Anytime Control to an Inherently Unstable Physical System

2015 ◽  
Author(s):  
Wayne Maxwell ◽  
Al Ferri ◽  
Bonnie Ferri
Keyword(s):  
Closed Loop ◽  
Initial Conditions ◽  
Transient Behavior ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Two Stages

This paper extends the use of closed-loop anytime control to systems that are inherently unstable in the open-loop. Previous work has shown that anytime control is very effective in compensating for occasional missed deadlines in the computer processor. When misses occur, the control law is truncated or partially executed. However, the previous work assumed that the open-loop system was stable. In this paper, the anytime strategy is applied to an inverted pendulum system. An LQR controller with estimated state feedback is designed and decomposed into two stages. Both stages are implemented most of the time, but in a small percentage of time, only the first stage is applied, with the resulting closed-loop system being unstable for short periods of time. The statistical performance of the closed-loop system is studied using Monte-Carlo simulations. It is seen that, on average, the closed-loop performance is very close to that of the full-order controller as long as the miss rate is relatively small. However, the variance of the response shows much higher dependence on the miss rate, suggesting that the response becomes more unpredictable. At a critical value of miss rate, the closed-loop system is unstable. The critical miss rate found through simulation is seen to correlate well with the results of a deterministic stability analysis. The statistics on the settling time are also studied, and shown to grow longer as the miss rate increases. The transient behavior of the system is studied for a range of initial conditions.

Synthesis of Multivariable Controller With Plant Test Data

1994 ◽  
Vol 116 (2) ◽  
pp. 309-313 ◽  
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Control System ◽  
Test Data ◽  
Open Loop ◽  
Loop System ◽  
Controller Synthesis ◽  
System Model ◽  
Multivariable Control ◽  
Open Loop System ◽  
Plant Test ◽  
Multivariable Controller

A method to synthesize decoupled multivariable control system from a batch of plant test data is introduced. The method is applicable when the system has more inputs than outputs and is open-loop stable. An advantage of this method is that explicit identification of an open-loop system model is not required for controller synthesis.

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 Robust Design Optimization Framework for Systematic Model-Based Calibration of Engine Control Systems

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Hoseinali Borhan ◽  
Edmund Hodzen
Keyword(s):  
Control System ◽  
Design Optimization ◽  
Robust Design ◽  
Closed Loop ◽  
Optimization Technique ◽  
Loop System ◽  
Robust Design Optimization ◽  
Engine Control ◽  
Closed Loop System ◽  
Model Based

In this paper, a systematic model-based calibration framework basing on robust design optimization technique is developed for engine control system. In this framework, the control system is calibrated in an optimization fashion where both performance and robustness of the closed-loop system to uncertainties are optimized. The proposed calibration process has three steps: in the first step, the optimal performance of the system at the nominal conditions, where the effects of uncertainties are ignored, is computed by formulation of the controller calibration as an optimization problem. The capabilities of the controller are fully explored at nominal conditions. In the second step, the robustness and sensitivity of a selected control design to the system uncertainties are analyzed using Monte Carlo simulation. In the third step, robust design optimization is applied to optimize both performance and robustness of the closed-loop system to the uncertainties. The robustness capabilities of the controller are fully explored and the one that satisfies both performance and robustness requirements is selected. This process is implemented for the calibration of an advanced diesel air path control system with a variable geometry turbocharger (VGT) and dual loop exhaust gas recirculation (EGR) architecture.

Modeling and Control of an Automotive All-Wheel Drive Clutch as a Piecewise Affine System

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Shiming Duan ◽  
Jun Ni ◽  
A. Galip Ulsoy
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Lyapunov Theory ◽  
Loop System ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Modeling And Control ◽  
Piecewise Affine ◽  
Wheel Drive ◽  
And Control

Piecewise affine (PWA) systems belong to a subclass of switched systems and provide good flexibility and traceability for modeling a variety of nonlinear systems. In this paper, application of the PWA system framework to the modeling and control of an automotive all-wheel drive (AWD) clutch system is presented. The open-loop system is first modeled as a PWA system, followed by the design of a piecewise linear (i.e., switched) feedback controller. The stability of the closed-loop system, including model uncertainty and time delays, is examined using linear matrix inequalities based on Lyapunov theory. Finally, the responses of the closed-loop system under step and sine reference signals and temperature disturbance signals are simulated to illustrate the effectiveness of the design.

scholarly journals High Efficient Solar Integrated an Isolated Dc-Dc Full-Bridge Converter for Electric Vehicle Battery Charging Application

2020 ◽  
Vol 9 (4) ◽  
pp. 432-437
Keyword(s):  
Electric Vehicle ◽  
Closed Loop ◽  
Open Loop ◽  
Loop System ◽  
System Stability ◽  
Control Technique ◽  
Closed Loop System ◽  
Conductance Method ◽  
High Efficient ◽  
Electric Vehicle Battery

In this paper, the power from a solar PV panel 20VDC, 12.5ADC is used for charging an electric vehicle battery (12V, 7Ah) with the help of an isolated dc-dc converter in an efficient manner. The power rating maintained in the system is around (200-250) W. The parasitic circuit analysis is carried out theoretically. The zero voltage transition (ZVT) technique is implemented at the inverter stage and an isolation transformer (1:1) is used for source-load isolation purposes. In order to achieve ZVT, a proper design procedure is followed and a pulse triggering technique is carried out at the switching element. The designed values of the parasitic elements are used in the Simulink tool. The open loop and closed loop system of the proposed converter are simulated in MATLAB Simulink package. In the open loop system, an irradiation analysis carried out similarly closed loop has reference voltage variation analysis in order to verify the system stability at the various operating condition. The problem of transients in open loop output is rectified in the closed loop operation. The MPP and PI control technique is initiated in the closed loop system for better performance. The MPP technique used is incremental conductance method for tracking maximum power from the PV array.

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