直线伺服系统非线性自适应鲁棒控制器的优化设计

对永磁直线电动机伺服系统提出了非线性自适应鲁棒控制器的优化设计方法.在系统非线性数学模型的基础上,建立了误差系统的动态模型.将跟踪和干扰抑制归结为非线性自适应鲁棒控制器的设计问题,通过构造存储函数得到自适应鲁棒控制器的定理,以及电阻和电感的辨识算法.证明了定理给出的控制器能满足干扰抑制和系统渐近稳定,并用遗传算法对控制器的参数进行优化.仿真结果验证了该方法是有效的.     

A robust design of simulated annealing approach for mixed-model sequencing

The effectiveness of the solution method based on simulated annealing (SA) mainly depends on how to determine the SA-related parameters. A scheme as well as parameter values for defining an annealing schedule should be appropriately determined, since various schemes and their corresponding parameter values have a significant impact on the performance of SA algorithms. In this paper, based on robust design we propose a new annealing parameter design method for the mixed-model sequencing problem which is known to be NP-hard. To show the effectiveness of the proposed method, extensive computation experiments are conducted. It was found that the robust designed method outperforms the SA algorithm by McMullen and Frazier [McMullen, P.R., & Frazier, G.V. (2000). A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line. IIE Transactions, 32, 679–686].     

Simultaneous design and control of processes under uncertainty: A robust modelling approach

This paper presents a new methodology to integrate process design and control. The key idea in this method is to represent the system’s closed-loop nonlinear behaviour as a linear state space model complemented with uncertain model parameters. Then, robust control tools are applied to calculate bounds on the process stability, the process feasibility and the worst-case scenario. The new methodology was applied to the simultaneous design and control of a mixing tank process. The resulting design avoids the solution of computationally intensive dynamic optimizations since the integration of design and control problem is reduced to a nonlinear constrained optimization problem.     

Application of discrete event simulation for robust system design of a melt facility

This paper presents a methodology to identify robust operating regions through the selection of controllable factory variables, using discrete event simulation. A casting plant melt facility was used as an industrial test bed to develop these techniques. A robust system design was determined by response surface analysis of key production parameters. Furthermore, robust operating policies that maximise throughput, while minimizing work-in-progress and thus energy consumption were identified.     

A fast hybrid primal heuristic for multiband robust capacitated network design with multiple time periods

We investigate the Robust Multiperiod Network Design Problem, a generalization of the Capacitated Network Design Problem (CNDP) that, besides establishing flow routing and network capacity installation as in a canonical CNDP, also considers a planning horizon made up of multiple time periods and protection against fluctuations in traffic volumes. As a remedy against traffic volume uncertainty, we propose a Robust Optimization model based on Multiband Robustness (Büsing and D’Andreagiovanni, 2012), a refinement of classical Γ-Robustness by Bertsimas and Sim that uses a system of multiple deviation bands.Since the resulting optimization problem may prove very challenging even for instances of moderate size solved by a state-of-the-art optimization solver, we propose a hybrid primal heuristic that combines a randomized fixing strategy inspired by ant colony optimization and an exact large neighbourhood search. Computational experiments on a set of realistic instances from the SNDlib show that our original heuristic can run fast and produce solutions of extremely high quality associated with low optimality gaps.     

The challenge of equality constraints in robust design optimization: examination and new approach

In recent years, robust design optimization (RDO) has emerged as a significant area of research. The focus of RDO is to obtain a design that minimizes the effects of uncertainty on product reliability and performance. The effectiveness of the resulting solution in RDO highly depends on how the objective function and the constraints are formulated to account for uncertainties. Inequality constraint and objective function formulations under uncertainty have been studied extensively in the literature. However, the approaches for formulating equality constraints in the RDO literature are in a state of disharmony. Moreover, we observe that these approaches are generally applicable only to certain special cases of equality constraints. There is a need for a systematic approach for handling equality constraints in RDO, which is the motivation for this research. In this paper, we examine critical issues pertinent to formulating equality constraints in RDO. Equality constraints in RDO can be classified as belonging to two classes: (1) those that cannot be satisfied, because of the uncertainty inherently present in the RDO problem, and (2) those that must be satisfied, regardless of the uncertainty present in the problem. In this paper, we propose a linearization- based approach to classify equality constraints into the above two classes, and propose respective formulation methods. The theoretical developments presented in this paper are illustrated with the help of two numerical examples.     

Application of two‐loop robust control to air‐conditioning systems

This paper presents the design and application of a two‐loop robust controller for temperature control in air‐conditioning systems. A Takagi‐Sugeno fuzzy model with uncertain local models is developed to describe the associated nonlinearities and uncertainties in the operation of the air handling units. Parallel distributed compensation is used to design the global control law. The local control law consists of two loops: an inner‐loop integral controller and an outer‐loop min‐max predictive controller with short prediction horizon. A discounting scheme is developed to weight the contribution of the two loops. Experimental results are presented which show that the proposed strategy can achieve acceptable control performance with a minimum of onsite tuning. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

异步电机鲁棒控制器及其Backstepp ing 设计

基于异步电机的精确模型,用Backstepping方法设计控制器,其误差系统在原点全局稳定。然而,由于反馈量的计算受参数不确定性和“可导条件”的影响,使得控制器鲁棒性较差,采用扩张状态观测器来增强鲁棒性,无需电机的精确模型,即可准确地获得反馈量,新控制器结合了Backstepping和扩张状态观测器的优点,能保证误差系统的稳定性,并具有很强的抗扰动能力,给出了控制器的详细设计过程和原理框图,并进行了数值仿真验证。     

Decoupled approach to integrated optimum design of structures and robust control systems

Integrated optimum design of structures and control systems is studied by using H ₂ and robust control formulations. It is derived that conventional simultaneous optimization approach by using these robust control laws can be approximated by a decoupled optimization approach in which the structures are optimized by shaping the structural singular values and then the controllers can be designed, namely, decoupled, sequential or successive design approach. It is shown that the proposed decoupled optimization approach can be used to design optimum robust structures and has certain advantages over the conventional simultaneous optimization procedures such as it avoids the drawbacks of pure robust control laws and faster, especially if the number of degrees of freedom (DOF) of the associated structure is large. The bounds for achievable robustness measures are also obtained. Following, simultaneous and decoupled optimization approaches are applied to active control of two structures. The optimization results are presented, and it is concluded that the proposed decoupled optimization approach yields the achieved global minimum much faster than the simultaneous optimization approach.     

Optimal design of controlled multibody dynamic systems for performance,robustness and tolerancing

The multidisciplinary design approach has gained increasing popularity in recent years due to its ability to deal with conflicting design requirements imposed by discipline-specific objectives. The traditional design process involving multiple disciplines is typically a sequential process where the design objectives are met one at a time in a sequence of designs. However, in doing so, unnecessary limitations are imposed on the design parameters and the final design is far from being optimal. The effectiveness of integrated design methodology has been proven and such designs are being obtained in many applications. However, most of the work in this area has been problem and/or system specific and does not address important manufacturing considerations, such as tolerance allocation, robustness with respect to machining tolerances, etc. The results presented in this paper are intended to contribution towards filling these gaps. In particular, the new approach will help designers avoid a common known pitfall of performance optimization, i.e. the fact that designs that are optimized for performance alone are notoriously sensitive to deviations from the nominal design. Thus, optimizing for performance alone leads to designs that fall below acceptable standards of robustness; they are also expensive to manufacture because the tolerances must be kept very tight to ensure acceptable performance. The approach presented here will allow the user to systematically tradeoff performance versus robustness and tolerancing concerns. A proof-of-concept example that was solved to evaluate this methodology is also presented in this paper. This example provides a convincing demonstration of the fact that small sacrifices in performance can yield huge benefits in the other areas, provided a methodology is available for making these tradeoffs in a systematic way. This especially can be used by designers in various fields such as automotive, aerospace, deployable structures, machine tools (including hexapods), robotic systems, precision machinery, etc.     

A nonparametric approach to design robust controllers for uncertain systems: Application to an air flow heating system

This paper presents an approach to design robust fixed structure controllers for uncertain systems using a finite set of measurements in the frequency domain. In traditional control system design, usually, based on measurements, a model of the plant, which is only an approximation of the physical system, is first built, and then control approaches are used to design a controller based on the identified model. Errors associated with the identification process as well as the inevitable uncertainties associated with plant parameter variations, external disturbances, measurement noise, etc. are expected to all contribute to the degradation of the performance of such a scheme. In this paper, we propose a nonparametric method that uses frequency-domain data to directly design a robust controller, for a class of uncertainties, without the need for model identification. The proposed technique, which is based on interval analysis, allows us to take into account the plant uncertainties during the controller synthesis itself. The technique relies on computing the controller parameters for which the set of all possible frequency responses of the closed-loop system are included in the envelope of a desired frequency response. Such an inclusion problem can be solved using interval techniques. The main advantages of the proposed approach are: (1) the control design does not require any mathematical model, (2) the controller is robust with respect to plant uncertainties, and (3) the controller structure can be chosen a priori, which allows us to select low-order controllers. To illustrate the proposed method and demonstrate its efficacy, an application to an air flow heating system is presented.     

产品概念设计可制造性评价方法研究

随着新产品开发技术的发展,人们对产品使用性能和外观艺术的要求越来越高。但概念设计不仅仅体现艺术性,更应符合工业产品的制造特点和使用特性。认为产品概念设计方案的可制造性决定于概念设计的工业设计阶段,并针对工业设计因素建立概念设计评价体系。认为产品概念设计可制造性评价是一个多层次、多属性的决策问题,建立概念设计评价模型,并基于多属性决策的理论知识给予了解决。     

离散系统鲁棒稳定的简化条件及其反馈控制方法

给出了一种离散系统鲁棒稳定性的分析方法。通过对离散系统不确定部分不同表达式的研究，提出一种系统鲁棒稳定判别不等式。为解决系统鲁棒稳定性的实际计算问题，给出了离散系统鲁棒稳定性的另一种描述，井由此描述和不等式恒等变形，得到新的鲁棒稳定性判据。该判据结构筒单，很容易判定系统的鲁棒性。在此基础上，给出了系统鲁棒反馈控制的设计方法。     

A delta transform approach to loop gain-phase shaping design of robust digital control systems

This paper addresses the existence of loop gain-phase shaping (LGPS) solutions for the design of robust digital control systems for SISO, minimum-phase, continuous-time processes with parametric uncertainty. We develop the frequency response properties of LGPS for discrete-time systems using the Δ-transform, a transform method that applies to both continuous-time and discrete-time systems. A theorem is presented which demonstrates that for reasonable specifications there always exists a sampling period such that the robust digital control problem has a solution. Finally, we offer a procedure for estimating the maximum feasible sampling period for LGPS solutions to robust digital control problems.     

An H-minimax approach to the design of robust control systems

A realistic feedback design problem is posed based on the minimization of a weighted combination of the sensitivity and complementary sensitivity matrices. A solution is obtained which makes use of the recently proposed methods for minimizing the sensitivity function alone.     

基于本体的产品设计知识表示方法

针对产品设计知识的多样性、动态化和相关性等特点,提出了一种基于本体的产品设计知识表示方法。建立了以客体、概念集、属性集、命题集和函数集为核心的知识单元,并设计了五者之间的联系,在此基础上引入了输入输出模块,以增强产品设计知识表示的全面性和灵活性。最后以圆柱形螺旋弹簧设计为例,验证了所提方法的有效性。     

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

Helical milling is a hole-making process which has been applied in hardened materials. Due to the difficulties on achieving high-quality boreholes in these materials, the influence of noise factors, and multi-quality performance outcomes, this work aims the multi-objective robust design of hole quality on AISI H13 hardened steel. Experiments were carried out through a central composite design considering process and noise factors. The process factors were the axial and tangential feed per tooth of the helix, and the cutting velocity. The noise factors considered were the tool overhang length, the material hardness and the borehole height of measurement. Response models were obtained through response surface methodology for roughness and roundness outcomes. The models presented good explanation of data variability and good prediction capability. Mean and variance models were derived through robust parameter design for all responses. Similarity analysis through cluster analysis was performed, and average surface roughness and total roundness were selected to multi-objective optimization. Mean square error optimization was performed to achieve bias and variance minimization. Multi-objective optimization through normalized normal constraint was performed to achieve a robust Pareto set for the hole quality outcomes. The normalized normal constraint optimization results outperformed the results of other methods in terms of evenness of the Pareto solutions and number of Pareto optimal solutions. The most compromise solution was selected considering the lowest Euclidian distance to the utopia point in the normalized space. Individual and moving range control charts were used to confirm the robustness achievement with regard to noise factors in the most compromise Pareto optimal solution. The methodology applied for robust modelling and optimization of helical milling of AISI H13 hardened steel was confirmed and may be applied to other manufacturing processes.     

A systematic knowledge-based method for design of transformable product

A transformable product can perform different functions or change functionality by changing its physical structure. It is formed by integration of different components whose states can be transformed each other. However, there is a lack of systematic methods to guide design of the transformable product. In order to improve the design efficiency of transformable products, a large number of products are studied in this research to build a case base of transformation parameters and transformation principles for the design knowledge. A systematic design process is proposed to apply the design knowledge. The transformation design problem is first mapped from the problem domain to the knowledge domain expressed by transformation parameters. A general solution is then obtained in the knowledge domain. A multi-classification support vector machine is used to train a model of the transformation recommendation based on transformation parameters. Finally, the general solution is mapped into the problem domain for the specific solution using the analogy design. The effectiveness of the method is verified in the design of a self-propelled boom sprayer.     

A modified sliding-mode observer design with application to diffusion equation

In many physical systems, the system's full state cannot be measured. An observer is designed to reconstruct the state from measurements. Disturbances often contribute to the dynamics of the system, and the designed observer must account for them. In this paper, a modified sliding-mode observer (SMO), a robust observer, is proposed that combines the efficiency of a nonlinear observer with the robustness of an SMO. The estimation error is proven to converge to zero under natural assumptions. This improved observer is compared with an extended Kalman filter and an unscented Kalman filter, as well as a standard SMO for three different versions of heat equation: a linear, a quasi-linear, and a nonlinear heat equation. The comparisons are done with and without an external disturbance. The simulations show improved performance of the modified SMO over other observers.     

基于遗传进化的陶瓷产品质感设计

针对陶瓷产品设计中用户的情感因素难以量化的问题,提出了基于遗传进化的陶瓷产品质感设计方法。该方法通过对陶瓷产品的材料特性描述方法研究,确定聚类后的典型感觉意向词汇群;通过对产品样本的感觉语意量化调查,以及感觉意象与产品材料特征的建模,建立起消费者感性认知与陶瓷产品材料特性的关系;通过遗传算法实现对陶瓷产品材料质感要素的进化设计;最终实现了对陶瓷产品设计中用户情感的量化描述,得到了符合情感目标的产品进化设计结果。