Robustness Of Closed-loop System Research Articles

Robust closed‐loop control of induction and maintenance of propofol anesthesia in children

During closed-loop control, a drug infusion is continually adjusted according to a measure of clinical effect (e.g., an electroencephalographic depth of hypnosis (DoH) index). Inconsistency in population-derived pediatric pharmacokinetic/pharmacodynamic models and the large interpatient variability observed in children suggest a role for closed-loop control in optimizing the administration of intravenous anesthesia. To clinically evaluate a robustly tuned system for closed-loop control of the induction and maintenance of propofol anesthesia in children undergoing gastrointestinal endoscopy. One hundred and eight children, aged 6-17, ASA I-II, were enrolled. Prior to induction of anesthesia, NeuroSENSE™ sensors were applied to obtain the WAVCNS DoH index. An intravenous cannula was inserted and lidocaine (0.5mg·kg(-1) ) administered. Remifentanil was administered as a bolus (0.5μg·kg(-1) ), followed by continuous infusion (0.03μg·kg(-1) ·min(-1) ). The propofol infusion was closed-loop controlled throughout induction and maintenance of anesthesia, using WAVCNS as feedback. Anesthesia was closed-loop controlled in 102 cases. The system achieved and maintained an adequate DoH without manual adjustment in 87/102 (85%) cases. Induction of anesthesia (to WAVCNS ≤60) was completed in median 3.8min (interquartile range (IQR) 3.1-5.0), culminating in a propofol effect-site concentration (Ce ) of median 3.5μg·ml(-1) (IQR 2.7-4.5). During maintenance of anesthesia, WAVCNS was measured within 10 units of the target for median 89% (IQR 79-96) of the time. Spontaneous breathing required no manual intervention in 91/102 (89%) cases. A robust closed-loop system can provide effective propofol administration during induction and maintenance of anesthesia in children. Wide variation in the calculated Ce highlights the limitation of open-loop regimes based on pharmacokinetic/pharmacodynamic models.

Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem

Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC) algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.

PID Controller Design Based on Modified IMC and Optimal Robust Performance Based on Applied Mechanics

In this work, PID design with acceptable performance and robustness of closed-loop system was introduced. With the normalized time constant of internal model control (IMC) replaced by a damping ratio and a new time constant, a modified IMC was proposed and could be equivalent to a proportional integral derivative (PID) control. Since the control systems always have a dilemma between performance and robustness, the robust performance index was created with the integral of absolute error (IAE) weighted by the maximum sensitivity (Ms) with an exponential factor and the PID parameters were optimized through it. As an example, an empirical weighted factor 1.5 was selected to obtain the self-tuning PID formula for first-order plus delay time (FOPDT) processes. Simulation results show that the proposed PID control achieves good closed-loop performance and robustness.

Chaos suppression on a class of uncertain nonlinear chaotic systems using an optimal H∞ adaptive PID controller

This paper introduces an optimal H∞ adaptive PID (OHAPID) control scheme for a class of nonlinear chaotic system in the presence system uncertainties and external disturbances. Based on Lyapunov stability theory, it is shown that the proposed control scheme can guarantee the stability robustness of closed-loop system with H∞ tracking performance. In the core of proposed controller, to achieve an optimal performance of OHAPID, the Particle Swarm Optimization (PSO) algorithm is utilized. To show the feasibility of proposed OHAPID controller, it is applied on the chaotic gyro system. Simulation results demonstrate that it has highly effective in providing an optimal performance.

The Application of Fractional Order Calculus in Closed-Loop System Control

A design method of fractional controller has been developed to meet the five different specifications, including for the closed-loop system robustness. The specifications of cross frequency, phase to get financing ϕ meters and robustness and complete performance curve based on level off the stage of open loop system, ensure damping is worse reaction time of model uncertainty gain change.

Simple robust autotuning rules for 2-DoF PI controllers

This paper addresses the problem of providing simple tuning rules for a Two-Degree-of-Freedom (2-DoF) PI controller (PI 2) with robustness considerations. The introduction of robustness as a matter of primary concern is by now well established among the control community. Among the different ways of introducing a robustness constraint into the design stage, the purpose of this paper is to use the maximum sensitivity value as the design parameter. In order to deal with the well known performance/robustness tradeoff, an analysis is conducted first that allows the determination of the lowest closed-loop time constant that guarantees a desired robustness. From that point, an analytical design is conducted for the assignment of the load-disturbance dynamics followed by the tuning of the set-point weight factor in order to match, as much as possible, the set-point-to-output dynamics according to a first-order-plus-dead-time dynamics. Simple tuning rules are generated by considering specific values for the maximum sensitivity value. These tuning rules, provide all the controller parameters parameterized in terms of the open-loop normalized dead-time allowing the user to select a high/medium/low robust closed-loop control system. The proposed autotuning expressions are therefore compared with other well known tuning rules also conceived by using the same robustness measure, showing that the proposed approach is able to guarantee the same robustness level and improve the system time performance.

Open- and Closed-Loop Multiobjective Optimal Strategies for HIV Therapy Using NSGA-II

In this paper, multiobjective open- and closed-loop optimal treatment strategies for HIV/AIDS are presented. It is assumed that highly active antiretroviral therapy is available for treatment of HIV infection. Amount of drug usage and the quality of treatment are defined as two objectives of a biobjective optimization problem, and Nondominated Sorting Genetic Algorithm II is used to solve this problem. Open- and closed-loop control strategies are used to produce optimal control inputs, and the Pareto frontiers obtained from these two strategies are compared. Pareto frontier, resulted from the optimization process, suggests a set of treatment strategies, which all are optimal from a perspective, and can be used in different medical and economic conditions. Robustness of closed-loop system in the presence of measurement noises is analyzed, assuming various levels of noise.

Robust PI–LPV Tension Control with Elasticity Observer for Roll–to–Roll Systems

AbstractFlexible materials such as textiles, papers, polymers and metals are transported on rollers during their processing. Maintaining web tension in the entire processing line under an expected web speed is a key factor in achieving good final product quality. It is common practice in industrial web transport systems to use decentralized PI–type controllers. The performances of such control strategies highly depend on web speed and elasticity because of the strong coupling between these two variables. Moreover web speed and elasticity are subject to large variations during a same processing. The emphasis of this paper is on the design of linear parameter varying PI controllers with quadratic H∞ performance to increase closed–loop system robustness regarding these parameters variations. First a polytopic model of the experimental plant is derived from web speed and tension dynamics. A design methodology of the PI–LPV controllers, that guarantees closed–loop quadratic stability and H∞ performance, is then presented. The method uses an optimization software with genetic algorithms to determine the controllers parameters while minimizing the H∞ norm. Moreover, as it is difficult to measure web elasticity online, an observer is synthesized to estimate the Young's modulus. The effectiveness of the proposed control strategy is illustrated with simulations.

A discrete-time stable controller for an omni-directional mobile robot based on an approximated model

An adaptive controller based on multi-input fuzzy rules emulated networks (MIFRENs) is introduced for omni-directional mobile robot systems in the discrete-time domain without any kinematic or dynamic models. An approximated model for unknown systems is developed by using two MIFRENs with an online learning algorithm in addition to the stability analysis. The main theorem in this model is proposed to guarantee closed-loop performance and system robustness for all adjustable parameters inside MIFRENs. The system is validated by an experimental setup with a FESTO omni-directional mobile robot called Robotino ® . The proposed algorithm is shown to have superior performance compared to that of an algorithm that uses only an embedded controller. The advantage of the MIFREN initial setting is verified comparing its results with those of a controller that is based on neural networks.

PID controller design of TITO system based on ideal decoupler

The proposed method for designing multivariable controller is based on ideal decoupler D( s) and PID controller optimization under constraints on the robustness and sensitivity to measurement noise. The high closed-loop system performance and robustness are obtained using the same controller in all loops. The method is effective despite the values and positions of the right half plane zeros and dead-times in the process transfer function matrix G p( s). The validity of the proposed multivariable control system design and tuning method is confirmed using a test batch consisting of Two-Input Two-Output (TITO) stable, integrating and unstable processes, and one Three-Input Three-Output (TITO) stable process.

BACKSTEPPING-BASED ADAPTIVE CRITIC DESIGN FOR UNCERTAIN NONLINEAR SYSTEMS

A novel control system design approach is proposed, based on backstepping theory and adaptive critic design (ACD) for a class of uncertain nonlinear systems. It ensures the systems' stability and accurately track the reference commands under large parametric perturbation. This approach is based on backstepping theory so that the whole system is not divided into slow and fast subsystems compared with dynamic inversion (DI). However, backstepping can ensure the little robustness of the closed-loop systems. To solve this problem, ACD is employed, which is designed without any information of the parametric perturbation. In the ACD, variable structure control is employed to make the systems asymptotically stable. To evaluate the performance of uncertain nonlinear systems using the proposed approach, an empirical study is conducted on a two-link manipulator to validate the new controller. Results show that the nonlinear system using the proposed controller can achieve asymptotical stability and good dynamic response characteristics when large model uncertainties exist.

Quaternion‐based visual servo control in the presence of camera calibration error

AbstractVisual servo control systems use information from images along with knowledge of the optic parameters (i.e. camera calibration) to position the camera relative to some viewed object. If there are inaccuracies in the camera calibration, then performance degradation and potentially unpredictable response from the visual servo control system may occur. Motivated by the desire to incorporate robustness to the camera calibration, different control methods have been developed. Previous adaptive/robust controllers (especially for six degree‐of‐freedom camera motion) rely heavily on properties of the rotation parameterization to formulate state estimates and a measurable closed‐loop error system. All of these results are based on the singular axis–angle parameterization. Motivated by the desire to express the rotation by a non‐singular parameterization, efforts in this paper address the question: Can state estimates and a measurable closed‐loop error system be crafted in terms of the quaternion parameterization when the camera calibration parameters are unknown? To answer this question, a contribution of this paper is the development of a robust controller and closed‐loop error system based on a new quaternion‐based estimate of the rotation error. A Lyapunov‐based analysis is provided which indicates that the controller yields asymptotic regulation of the rotation and translation error signals given a sufficient approximate of the camera calibration parameters. Simulation results are provided that illustrate the performance of the controller for a range of calibration uncertainty. Copyright © 2009 John Wiley & Sons, Ltd.

Mechatronic System Design Applied to Double Inverted Pendulum with Flywheel Actuator

In this paper we study the stabilization problem of double inverted pendulum via wlywheel actuator. The main issue of the paper is whether such system can be stabilized in real conditions or not. It is shown that the answer strongly depends on the structural (geometric and physical) parameters of the system. The paper gives the procedure for optimizing these parameters under specified conditions to obtain the most robust closed loop system.

Transient lean burn air-fuel ratio linear parameter-varying control using input shaping

Transient air-fuel ratio control for lean burn engines is essential to achieve improved fuel economy and strict federal emission regulations. Unlike conventional Spark Ignition (SI) engines, lean burn engines are no longer operating in a narrow band around stoichiometric resulting in a very challenging air-fuel ratio tracking problem. An approach to combine an input shaping method together with Linear Parameter Varying (LPV) feedback control is proposed in this paper to solve the transient air-fuel ratio tracking problem. LPV air-fuel ratio control has been shown to regulate the air-fuel ratio at steady state engine operating conditions, reduce the variability of the closed-loop system, reject disturbance and guarantee robustness and stability in the presence of variable time delays. In this paper, an input shaping method is used to reduce the cost of feedback, and thereby enhance the air-fuel ratio tracking performance during engine transient operations. The prefilter is designed based on the closed-loop dynamics resulting from the LPV design. A systematic input shaping prefilter design process is developed. The designed prefilter successfully extends the closed-loop air-fuel ratio tracking bandwidth. Simulation results using Federal Test Procedure (FTP) drive cycle data are used to demonstrate the effectiveness of the input shaping prefilter. Moreover, the designed prefilter is structurally simple and computationally efficient.

A Software Tool for Robust PID Design

This paper presents a fast, interactive and easily modifiable software tool for robust PID design. The Matlab based program is supposed to give people with moderate knowledge on PID control a possibility to learn more and also be a future part of an autotuner. The PID design is made by minimizing the integrated absolute error value during a load disturbance on the process input. The optimization is performed with H∞ constraints on the sensitivity and complementary sensitivity function, providing a robust closed loop system. Nelder Mead optimization is used with the AMIGO method providing an initial controller. The proposed method works well, and is very efficient, on a large batch of systems common in process industry. The design tool is also shown to work on a highly oscillatory process model.

Polynomial approach for design and robust analysis of Lateral missile control

A polynomial approach is presented for the design and analysis of a sideslip velocity missile autopilot. The controller is designed using polynomial eigenstructure assignment (PEA). The missile model is described by linear parameter varying (LPV) matrices. The design renders to a closed-loop system independent of the choice of equilibria. Thus, if the operating points are in the vicinity of the equilibria, then only one linear model will describe closed-loop dynamics, regardless of the rate of change of the operating points. Parametric stability margins for uncertainty in the controller parameters and aerodynamic derivatives are analysed using a finite version of the Nyquist Theorem. The Finite Nyquist Theorem (FNT) exploits the polynomial framework to assess robustness for a parametric uncertain system with the Finite Inclusion Theorem (FIT). The design and analysis approach is applied to a single-input single-output (SISO) tail-controlled missile in the cruciform fin configuration. Simulations show good tracking of sideslip velocity with closed-loop system, fast responses and good parametric robustness against six uncertain parameters.

A ROBUST PASSIVE POWER-BASED CONTROL STRATEGY FOR THREE-PHASE VOLTAGE-SOURCE RECTIFIERS

In this paper, robustness of the damping injection schemes for passivity based control (PBC) of the three-phase AC/DC voltage-source (Boost type) rectifier is studied. The idea is to extend the tuning strategy for PBC that is presented in (Jeltsema and Scherpen, 2004) for DC/DC converters to three-phase AC/DC rectifiers. In the DC/DC converter case this tuning strategy leads to a PBC scheme with parallel damping injection that is robust against load perturbations. Straightforward application of this scheme to the three-phase AC/DC Boost rectifier, however, does not immediately lead to such robust closed loop system. A closer analysis reveals that first a pre-compensation should be done so that the AC input stage connected to the DC output stage is converted into two DC input stages connected to the DC output stage. Then, the PBC parallel damping injection scheme can be applied resulting in a closed-loop system that is robust against load variations.

Robust output tracking control for nonlinear time-varying robotic manipulators

In this paper, a systematic methodology for the robust tracking control of nonlinear time-varying robotic manipulators is proposed. The control method involves fuzzy logic and sliding mode techniques. Output error dynamics can be assigned. Closed-loop system stability is proven. The robustness of the closed-loop system can be achieved against parameter variations and external disturbances. A two-degrees-of-freedom manipulator tracking control problem is carried out. The result shows that output tracking performance can be improved very much comparatively.

Controllability of Processes with Large Singular Values

The singular-value decomposition has been used to analyze the robustness of closed-loop systems and to determine whether any controllability problems can be expected. Past controllability conditions have been derived in terms of the condition number and the minimum singular value of the process and the condition number of the controller transfer function matrix, in terms of potential sensitivities of the closed-loop system to model uncertainties or problems with saturation of the manipulated variables. This paper considers processes with a large maximum singular value. It is shown that the closed-loop control of such processes can result in poor transient performance as a result of valve accuracy considerations, even if the condition number is small and the minimum singular value is large, which would indicate no performance limitations according to existing controllability criteria. Further, processes with large singular values can be prone to sensor saturation. This indicates that the magnitude of all of the singular values should be considered when assessing the controllability of a process. A new interaction tool based on output correlation is introduced to help select measurements and manipulated variables that have a good range of singular values for practical application. The approach proposed is illustrated on two simple examples and on the Tennessee Eastman process.

Reducing the effect of truncation error in spatial and pointwise models of resonant systems with damping

This paper is concerned with finding analytical solutions to the problems of reducing the effect of truncation error in models of resonant systems that include damping. Pointwise and spatial models of resonant systems are both considered in the paper. It is known that the truncation of an infinite-dimensional model produces errors in the zero locations and zero-frequency content of the system. Our approach is to add a feedthrough term to the truncated model to reduce the uncertainty caused by neglected dynamics. This will improve the accuracy of the model by reducing the errors in the zero locations and zero-frequency content of the system, which is important in ensuring the closed-loop system's robustness when a feedback controller is implemented. The optimal feedthrough terms are determined by minimising the weighted H 2 norm and spatial H 2 norm of the error systems associated with the pointwise and spatial models, respectively. The existence of analytical solutions for optimal feedthrough terms allows models of resonant systems to be compensated in a straightforward manner. Simulation results are presented to demonstrate the effectiveness of our approach in reducing the effect of truncation error.