Stability augmentation design of a large flexible transport using nonlinear parameter optimization

Robust controller synthesis attracts reviving research interest, driven by\nthe rise of learning-based systems where uncertainty and perturbation are\nubiquitous. Facing an uncertain situation, a robustly stabilizing controller\nshould maintain stability while operating under a perturbed system deviating\nfrom its nominal specification. There have been numerous results for robust\ncontroller synthesis in multiple forms and with various goals, including\nmu-synthesis, robust primal-dual Youla, robust input-output, and robust system\nlevel parameterizations. However, their connections with one another are not\nclear, and we lack a general approach to robust controller analysis and\nsynthesis.\n To serve this purpose, we derive robust stability conditions for general\nsystems and formulate the general robust controller synthesis problem. The\nconditions hinge on the realization-stability lemma, a recent analysis tool\nthat unifies existing controller synthesis methods. Not only can the conditions\ninfer a wide range of existing robust results, but they also lead to easier\nderivations of new ones. Together, we demonstrate the effectiveness of the\nconditions and provide a unified approach to robust controller analysis and\nsynthesis.\n

Background/Introduction Prior studies revealed exposure to ambient air pollution would increase cardiovascular disease–related mortality and nonfatal events, but the underlying mechanism was not fully elucidated. Disruption of autonomic regulation might be a possible cause of increased cardiovascular morbidity and mortality, but previous work showed inconsistent relationship between ambient air pollution and heart rate variability analyzed by traditional linear methods. Our previous study showed the relationship between ambient air pollution and home blood pressure was non-linear, thus non-linear methods, such as detrended fluctuation analysis (DFA) and multi-scale entropy (MSE), could be more useful tools while assessing the effect of ambient air pollution on biomedical parameters. Purpose To use both traditional linear and novel non-linear methods to evaluate the impact of ambient air pollution on 24-hour heart rate variability. Methods From 2015/01 to 2015/12, patients undergoing 24-hour Holter ECG study in a tertiary medical center were enrolled as the study population. The patients were divided into two groups based on the severity of air pollution in their living areas (severe and mild air pollution groups). The two groups were matched by propensity-score matching. Linear and non-linear methods, including DFA and MSE, were used to calculate 24-hour heart rate variability. Results A total of 568 patients (284 patients in each group) were enrolled in this study. Traditional linear analysis of HRV didn’t show significant difference between the two groups regarding any time- or frequency-domain parameters. In non-linear analysis of HRV, DFA failed to detect significant difference between the two groups, while most MSE parameters (Area1-5, Ln_Area1-5, Area6-20 and Ln_Area6-20) were significantly lower in the severe air pollution group. The MSE analysis revealed significant differences across all scales (1 to 20). Conclusion(s) Ambient air pollution was associated with decreased 24-hour heart rate variability, and the impact was better evaluated by non-linear analysis (specifically multi-scale entropy) than traditional linear method.Table Figure

This paper proposes a control theoretic formulation and a controller design method for the feature-based visual servoing with redundant features. The linear time-invariant (LTI) formulation copes with the redundant features and provides a simple framework for controller design. The proposed linear quadratic (LQ) method can deal with the redundant features, which is important because the previous LQ methods are not applicable to redundant systems. Moreover, this LQ method gives flexibility for performance improvement instead of the very limited design parameters provided by the generalized inverse and task function controllers. Validity of the LTI model and effectiveness and flexibility of the LQ optimal controller are evaluated by real-time experiments on a PUMA 560 manipulator.

This paper discusses about synthesizing a state-feedback controller for a quadcopter based on an optimal linear quadratic control method. The resulting flight control system enables the quadcopter to maintain stability and to track a reference input. The solution to this control problem involves solving an algebraic Riccati equation. The reference-input tracking capability is simulated to show the capability of the quadcopter flight control system.

We present the parameter robust risk-sensitive control theory to deal with the parameter uncertainties of a system. In this synthesis, the parameter uncertainties are decomposed into three parts, and are reflected in the cost function and the noise models. This new method improves the tolerance of a controller to parameter uncertainties in a system. We apply the newly developed method to satellite structure attitude control application. The linearized version of the satellite structure attitude model is derived for the attitude hold mode. To determine the performance of the parameter robust risk-sensitive control method, the steady-state mean square histories of the state and input variables are calculated by finding the covariance matrices. Moreover, the performance robustness of parameter robust risk-sensitive control is compared with the classical linear quadratic Gaussian control. Finally, as an application of this parameter robust risk-sensitive control, we consider commercially operating remote sensing satellite. The numerical simulations show that the parameter robust risk-sensitive control method has better performance and stability characteristics than the classical linear quadratic Gaussian control method, especially when the parameter uncertainties are large.

The state equation of five degrees of freedom rotor system suspended by AC hybrid magnetic bearings is given, and the approach to how to use linear quadratic method of optimal control theory to design a centralized and decentralized parameter controller is introduced. The simulation analysis between the centralized and decentralized parameter controllers is completed using MATLAB software. The digital control system based on TMS320F2812 DSP for AC magnetic bearings has been designed and tested using the decentralized control arithmetics. The research results have shown that the decentralized controller based on linear quadratic method meets performance requirements of AC magnetic bearing system, and has good control effect when the speed of the rotor runs under 30000 rpm.

In the present work a typical section aeroelastic model of a vertical fin is used to evaluate two different active control strategies to attenuate buffeting response at high angle of attack, namely the classic aerodynamic surface control approach using the rudder, and a new `smart' structures strain actuation approach. The three-degree-of-freedom typical section model including plunge, airfoil and flap rotation is augmented to incorporate the unsteady airloads due to motion, and an internal `buffet mode' to simulate the buffering excitation observed in wind tunnel tests of the fin at a given range of reduced frequencies. The two control strategies are studied using the Linear Quadratic Gaussian method of the Optimum Control Theory. Numerical results are presented in terms of Bode plots of the structure aeroelastic response, and root-loci of the aeroelastic modes at a representative flight condition.

Various alternatives to linear quadratic design methods for jet engine control systems are discussed. The main alternatives are classified into two broad categories: nonlinear global mathematical programming methods and linear local multivariable frequency domain methods. Specific studies within these categories include model reduction, the eigenvalue locus method, the inverse Nyquist method, polynomial design, dynamic programming, and conjugate gradient approaches.

On some attitude control syntheses for satellites with flexible appendages

Comparison of nonparametric recursive partitioning to parametric discriminant analyses in laboratory differentiation of hypercalcemia

Günümüzde teknolojinin gelişimiyle birlikte simülatörlerin kullanım alanları çeşitlenerek artmaktadır. Simülatörler her sektörde kendilerine yer bulabildikleri gibi havacılık ve uzay çalışmalarında da büyük rol oynamaktadırlar. Bu çalışmada, yeni bir küresel uçuş simülatörü tasarlanmış, küresel uçuş simülatörünün doğrusal olmayan dinamiği Newton-Euler yöntemi kullanılarak matematiksel olarak modellenmiştir. Elde edilen matematiksel model küresel uçuş simülatörü için kontrolcü tasarımında kullanılmıştır. Kontrolcü tasarımında kutup yerleştirme yöntemi ve doğrusal karesel düzenleyici yöntemi (LQR) seçilmiş olup bu yöntemler kıyaslanmıştır. Sistemin matematiksel benzetimi SIMULINK ortamında yapılmıştır.

This paper presents a variable ratio control strategy for a rear wheel active steering in order to improve the vehicle control stability and obtain an ideal steering characteristic. Considering the vehicle's control response performance at low speed and driving stability performance at high speed, using an expected yaw velocity with variable ratio and linear quadratic regulator LQR optimal control method, we design a vehicle rear wheel active steering controller to ensure the tracking at expected yaw velocity. The simulation result showed that the proposed control strategy has not only improved the control response at low speed but also enhanced the driving stability performance at high speed.

A noninterior continuation method is proposed for nonlinear complementarity problems. It improves the noninterior continuation methods recently studied by Burke and Xu [Math. Oper. Res., 23 (1998), pp. 719--734] and Xu [The Global Linear Convergence of an Infeasible Non-Interior Path-following Algorithm for Complementarity Problems with Uniform P-functions, Preprint, Department of Mathematics, University of Washington, Seattle, 1996]; the interior point neighborhood technique is extended to a broader class of smoothing functions introduced by Chen and Mangasarian [Comput. Optim. Appl., 5 (1996), pp. 97--138]. The method is shown to be globally linearly convergent following the methodology established by Burke and Xu. In addition, a local acceleration step is added to the method so that it is also locally quadratically convergent under suitable assumptions.

The Distributed Tuned Mass Damper (DTMD) technology, which is one of the modifications of the classical Tuned Mass Damper (TMD) technique, is defined as the multiple TMD design based on one mode of the primary structures. The modeling procedure for this kind of problem is similar to that for the single TMD design, especially for discrete (or modeled as) primary structures, such as the building-type structures. Therefore, the challenge work in this area is to attain the best vibration suppression performance through an optimally designed DTMD system. From the point of optimization, basically, two typical approaches have been utilized to design the DTMD system. The first one is to directly obtain the transfer function and then define the variance or the Dynamic Magnification Factors (DMF) as objective functions, which was utilized by many researchers. In the other methodology, the transfer function is expressed as a dynamic model with an optimal H2 controller under predefined form. In this study, a new optimal DTMD design approach will be presented, in which the optimization objective function and method will be established based on the Linear Quadratic Controller design method. The presented method provides a simple and straightforward way to design the DTMD system. The numerical example will be presented to illustrate the vibration suppression performance of the optimally designed DTMD system.

Trade-Off Between Energy Capture and Dynamic Loads in Variable Speed Wind Turbines