Uncertainty observer-based robust tracking control for high-order nonlinear systems using forwarding technique

Based on uncertainty observers, we develop a robust tracking control approach for high-order nonlinear systems subject to uncertainties satisfying mismatched condition. In this study, by combining with forwarding technique, uncertainty observers are designed to estimate uncertainties including parameter perturbations and external disturbances in a bottom-up way; at the same time, the convergence rate of estimate error of uncertainty observers is analysed in detail. The insensitivity to uncertainties for each manifold, no need of a prior knowledge on the bound of the uncertainty and the feasibility of practical implementation are three advantages of the proposed scheme. Moreover, approximate error of uncertainty observer can be made sufficiently small by tuning the parameters. The design procedures are elaborated and the boundedness of all trajectories of the closed-loop systems is guaranteed. Two examples are illustrated, highlighting the superiority of the proposed methodology via comparison with other control strategies.     

基于干扰补偿的BTT导弹自动驾驶仪抗尖峰滑模控制器设计

为了提高BTT导弹自动驾驶仪在非匹配干扰影响下的系统性能,提出一种新型基于干扰补偿的抗尖峰滑模控制器(PDOSMC).所提出的PDOSMC不仅不需要非匹配干扰满足$H_2$假设,还有效解决了高观测增益下估计尖峰引起现有干扰补偿滑模控制器(DOSMC)控制性能下降的问题.仿真结果表明,在都选取高观测增益的情况下,PDOSMC算法不仅能够取得与现有DOSMC算法相同的高控制精度,而且能够避免DOSMC算法中由估计尖峰所带来的控制饱和以及跟踪误差振荡.     

Multipurpose controller design using parametric optimization with dynamic constraints

A systematic and effective design procedure for a class of linear multivariable feedback control systems is proposed For simultaneously achieving robust tracking of the prescribed input signal via the Q-parametrization approach and internal model principle, the prescribed transient specifications by choosing an appropriate performance criterion, robust stabilization, and sensitivity minimization. The problem can best be cast in the form of an optimization problem with dynamic constraints. A numerical method is formulated to solve the optimization problem with dynamic constraints using a non-linear programming method. A numerical example is provided to illustrate the main results of the paper.     

Optimal design of flexible mechanisms using a parametric approach

In this paper, an effort to develop a more generic design procedure for flexible mechanisms is initiated. Based on a parametric study, the important parameters which affect the stress, displacement, and natural frequency can be closely related. An approach using these relations to obtain the optimal design of flexible mechanisms subject to stress, displacement and natural frequency constraints is presented. Optimality conditions are derived to moderate the conflicting constraints, and a recursion approach is developed to show the application of this study. Two examples using this approach to design flexible mechanisms are presented to demonstrate the idea.     

Controller design for nonlinear systems using the Contoured Robust Controller Bode plot

In this paper, we develop the Contoured Robust Controller Bode (CRCBode) plot and demonstrate its use in the design of robust controllers for nonlinear single‐input single‐output (SISO) systems. The CRCBode plot shows contours (level sets) of a robust performance quantity on the Bode magnitude and phase plots of the controller. An iterative frequency domain loop‐shaping design approach is employed to eliminate all intersections of the controller frequency response with certain ‘forbidden regions,’ indicating that a standard SISO robust stability and performance criterion is satisfied. Nonlinearities are accounted for by avoiding the maximum forbidden regions over a structured uncertainty set consisting of linearizations of the system dynamics about several operating points. We demonstrate this technique by designing and experimentally verifying a flow‐rate controller for a butterfly‐valve based liquid cooling system, which is robust to valve nonlinearities and flow disturbances. Finally, we compare this compensator with one generated using an automated H _∞ synthesis algorithm and discuss the advantages of the CRCBode approach. Copyright © 2013 John Wiley & Sons, Ltd.     

Controller design for time-delay systems using genetic algorithms

This paper presents a new approach to design controllers for time-delay systems by using genetic algorithms (GAs) together with the solvability of linear matrix inequalities (LMIs). Both of the state-feedback controller and the static output feedback controller can be designed with this approach. It is confirmed by numerical examples that this approach achieves less conservative results than previously existing methods on the given examples.     

Process optimization of SnCuNi soldering material using artificial parametric design

The European Union has implemented the directive restriction of hazardous substances (RoHS) prohibiting the uses of tin-lead solder. SAC305 (Sn96.5/Ag3.0/Cu0.5) has come into widespread use as a candidate soldering material in the electronics manufacturing industry. Nevertheless, the price of silver has increased dramatically in recent years. This study evaluates the feasibility of replacing the commonly used SAC305 with low cost SnCuNi (Sn99.25/Cu0.7/Ni0.05/Ge; SCN) solder alloy in wave soldering for high layer count printed circuit board. However, the melting temperature of SCN alloy is 227, 10  \(^{\circ }\text{ C}\) higher than SAC305. The objective of this research is to investigate manufacturing issues and propose an optimal process. Process parameters such as soldering temperature and dwell time are determined to achieve the desired quality levels. Multiple quality characteristics, namely assembly yield and solder joint pull strength, are considered. Thus, this study compares two approaches, integration of principal component analysis/grey relational analysis and artificial neural networks (ANN) combined with genetic algorithms (GA), to resolve the problems of multiple quality characteristics. The results of verification test shows that samples prepared with the process scenario suggested by the ANN combined with GA are superior. The process scenario with maximum desirability value is 268.64  \(^{\circ }\text{ C}\) soldering temperature and 7.42 s dwell time, indicating the recommended manufacturing process.     

Steady-state design of second-order digital filters using the Kalman formulation

A design methodology for second-order digital band-pass filters is described based on the Kalman filter formulation with a sinusoidal signal model. When driver noise is included, steady-state relationships between the Kalman gain, the coefficients of the covariance matrix and the coefficients of the driver-noise covariance matrix are derived. Then, expressions for the steady-state filter, discrete-time transfer function, magnitude and phase functions, pole-zero locations and ?3dB frequencies are derived. Finally, a procedure for selecting the driver-noise covariance matrix based on the desired frequency domain characteristics is developed. A design example illustrates the procedure.     

A feature based shape optimization technique for the configuration and parametric design of flat plates

A new feature based shape optimization technique is presented that is capable of modifying the topology (configuration) and shape to reduce the area of 2-D components based on the stress distribution in the component. Shape optimization attempts to maximize material usage to achieve a uniform stress distribution near the allowable limit of the material. Features can be added to the component, or can be modified, in order to optimize the material usage. By using features as a basis for shape modification, the problem of component connectivity can be handled in a consistent, intelligent manner, and the problem of smoothness is eliminated. A program was written to implement the optimization technique and was applied to two example problems, including one from the literature that used a different modification technique. The other example illustrates shape modification capabilities with more complicated geometry. Results from both examples are compared to results obtained using other topological modification techniques.     

Parameterization and parametric design of mannequins

This paper presents a novel feature based parameterization approach of human bodies from the unorganized cloud points and the parametric design method for generating new models based on the parameterization. The parameterization consists of two phases. First, the semantic feature extraction technique is applied to construct the feature wireframe of a human body from laser scanned 3D unorganized points. Secondly, the symmetric detail mesh surface of the human body is modeled. Gregory patches are utilized to generate G¹ continuous mesh surface interpolating the curves on feature wireframe. After that, a voxel-based algorithm adds details on the smooth G¹ continuous surface by the cloud points. Finally, the mesh surface is adjusted to become symmetric. Compared to other template fitting based approaches, the parameterization approach introduced in this paper is more efficient. The parametric design approach synthesizes parameterized sample models to a new human body according to user input sizing dimensions. It is based on a numerical optimization process. The strategy of choosing samples for synthesis is also introduced. Human bodies according to a wide range of dimensions can be generated by our approach. Different from the mathematical interpolation function based human body synthesis methods, the models generated in our method have the approximation errors minimized. All mannequins constructed by our approach have consistent feature patches, which benefits the design automation of customized clothes around human bodies a lot.     

Loop transfer recovery design via new observer-based and css architecture-based controllers

Two new controller structures, namely the continuous-time current-type observer and current-type CSS (Chen-Saberi-Sannuti) architecture-based controllers, are considered in this paper for loop transfer recovery design for general non-strictly proper non-minimum phase systems. The proposed observer is structurally analogous to the current estimator of discrete-time systems, while the proposed CSS architecture falls into the category of the controller structures developed recently by Chen, Saberi and Sannuti. The properties of these new structures are characterized. In particular, sets of necessary and sufficient conditions under which a target loop transfer function can be either exactly and/or asymptotically recovered by the abovementioned controllers are obtained. More importantly, the new current-type observer balances the observer structures for continuous-time and discrete-time linear systems.     

时滞依赖型中立系统的观测器设计与镇定

研究了一类时滞依赖型线性中立系统的观测器的设计与镇定问题,首先建立了一个时滞依赖型稳定性准则,基于LMI正定解的存在性,给出确保误差动力系统渐近稳定的充分条件及经状态反馈而达到镇定的设计方案.最后通过数值仿真来说明本文所得结论的正确性和有效性.     

A non-linearly virtual sample generation technique using group discovery and parametric equations of hypersphere

In manufacturing systems, only a small training dataset can be obtained in the early stages. A small training dataset usually leads to low learning accuracy with regard to classification of machine learning, and the knowledge derived is often fragile, and this is called the small sample problem. This research mainly aims at overcoming this problem using a special nonlinear classification technique to generate virtual samples to enlarge the training dataset for learning improvement. This research proposes a new sample generation method, named non-linear virtual sample generation (NVSG), which combines a unique group discovery technique and a virtual sample generation method using parametric equations of hypersphere. By applying a back-propagation neural network (BPN) as the learning tool, the computational experiments obtained from the simulated dataset and the real dataset quoted from the Iris Plant Database show that the learning accuracy can be significantly improved using NVSG method for very small training datasets.     

Robust microscale grasping through a multimodel design: synthesis and real time implementation

This paper deals with robust force control at the microscale for safe manipulation of deformable soft materials. Since mechanical properties of micrometer sized objects are highly uncertain, instability often occurs during a gripping task. This leads to object damage or destruction due to excessive gripping force. In this paper we propose the design of a robust dynamic output feedback controller that is able to insure desired performances for a set of 65 soft and resilient microspheres whose diameter ranges from 40 μm to 80 μm and stiffness varies from 2.8 N/m to 15.7 N/m. The degrees of freedom of the controller are managed by the use of a set of elementary observers. Robustness with respect to parametric uncertainties is satisfied thanks to an iterative procedure alternating between multimodel closed loop eigenstructure assignment and worst case analysis. The developed controller is of low order and can be implemented in real time. Robust gripping force control is for the first time demonstrated experimentally when dealing with the manipulation of a large number of variable deformable soft materials at the microscale. Both simulations and experimental results validate the interest of such control design approach.     

Delay-dependent observer-based stabilizing controller design for linear multiple state-delayed systems

This article concerns a coupled LMIs approach to delay-dependent observer-based output feedback stabilizing controller design for linear continuous-time systems with multiple state delays. The advantage of our proposed delay-dependent coupled LMIs criterion lies in that: (1) it can optimize one of multiple time delays with others selected properly, and at the same time, the feedback-gain and observer-gain can be obtained, respectively. (2) it is less conservative than the existing delay-independent ones in the literature. Algorithm to solve the coupled LMIs is also given. Numerical examples illustrate the effectiveness of our method.     

Partitioned model-based IMC design using JITL modeling technique

A partitioned model-based internal model control (PM-IMC) design strategy is proposed for a class of nonlinear systems that can be described by just-in-time learning (JITL) modeling technique. The PM-IMC scheme consists of a conventional IMC controller augmented by an auxiliary loop to account for nonlinearities in the system. Two alternative implementations of the JITL are discussed and compared via simulation studies of an industrial polymerization reactor and an isothermal reactor exhibiting inverse response. It is shown that PM-IMC using the database-updating JITL is more desirable owing to the relative ease in collecting the process data required to construct its initial database, while achieving comparable control performance as that obtained by PM-IMC using the JITL with fixed-database, which requires process data collected over the entire operating region to construct its database. In addition, a comparison is made between PM-IMC and its linear counterpart.     

Canopy surface technique for parametric blending

A method based on canopy surfaces is presented for blending parametric surfaces. The blend designed using this method gives freedom to the designer in selecting i) the primitive surfaces to be blended, ii) the contact curves lying on them (in which the blend meets the primitives), iii) the endtangent directions along the contact curves (which are used to ensure tangentplane continuity), and iv) the shape of the cross-sectional curve. An important feature of this method, which is not seen in earlier methods, is the use of end tangents to ensure theC ¹ continuity of iso-parametric curves across the junctions between the blend and the primitives in addition to the tangent-plane continuity.     

Structural optimization of finite deformation elastoplasticity using continuum-based shape design sensitivity formulation

A continuum-based shape design sensitivity formulation and optimization method is proposed for finite deformation elastoplasticity. In response analysis, the multiplicative decomposition of the deformation gradient into elastic and plastic parts is used for the hyperelasticity-based elastoplastic constitutive model with respect to the intermediate configuration. In design sensitivity analysis, the shape variation at the undeformed configuration is taken using a design velocity concept and then is transformed to the current configuration to recover the updated Lagrangian formulation. The design sensitivity equation of the direct differentiation method is solved at each time step without iteration. The effect of using different reference frames for response analysis and sensitivity analysis is discussed in detail. The path-dependency of the sensitivity is due to the evolutions of the intermediate configuration and the internal plastic variables. A numerical example is shown to confirm the accuracy and efficiency of the proposed computational method using a vehicle bumper optimization.     

Decentralized observer-based controller design for large-scale systems with quantized measurements and actuator faults

This paper is focused on designing observer-based decentralized memory feedback controller for ensuring the asymptotic mean square stability of the large-scale systems with minimum H_∞ performance index. Precisely, the unknown interconnection between each subsystems of a large-scale system is assumed to satisfy quadratic bounds, and measured output is quantized by a logarithmic quantizer. Also, the signals are transmitted through the actuator component wherein the occurrence of fault is indispensable. Thus, the impact of faults in actuator is considered in control design to tolerate the fault effects and also for ensuring robust performance. A state space representation of the system is formulated to reconstruct the unmeasurable states via the available informations of input/output dynamics. Based on the designed observer, a decentralized memory feedback controller is developed. Specifically, in terms of linear matrix inequalities, the stability conditions are derived and which are sufficient to guarantee the desired result. At last, simulations are carried out for two numerical examples to validate the potential of the theoretical result.