The Optimal Design of a Planar Parallel Platform for Prescribed Machining Tasks

In this paper a general methodology is presented for determining theoptimum design of a planar parallel platform to be used in machining.The method, based on a mathematical optimization approach, is used tofind a platform design and placement such that firstly, the execution ofa prescribed task path is feasible, and secondly, the actuator forcesrequired to execute the prescribed task are minimized. The applicationof the method is illustrated for two prescribed tasks, five designvariables and a number of geometrical inequality constraints such asactuator length limits. The method succeeds in finding locally optimumand feasible platform designs for which the required task lies insidethe workspace. Two optimization algorithms are implemented and theirrespective results are compared. The first algorithm is a robust andreliable trajectory algorithm, LFOPC, which is however expensive interms of the number of required function evaluations. As the simulationsperformed here in evaluating the objective and constraint functions maybe computationally intensive, an approximation method, Dynamic-Q, isalso used to find the optimum design with greater efficiency. Theeffectiveness of this approximation approach is evaluated.     

Optimal design of a 3-PUPU parallel robot with compliant hinges for micromanipulation in a cubic workspace

In recent years, nanotechnology has been developing rapidly due to its potential applications in various fields that new materials and products are produced. In this paper, a novel macro/micro 3-DOF parallel platform is proposed for micro positioning applications. The kinematics model of the dual parallel mechanism system is established by the stiffness model with individual wide-range flexure hinge and the vector-loop equation. The inverse solutions and parasitic rotations of the moving platform are obtained and analyzed, which are based on a parallel mechanism with real parameters. The reachable and usable workspace of the macro motion and micro motion of the mechanism are plotted and analyzed. Finally, based on the analysis of parasitic rotations and usable workspace of micro motion, an optimization for the parallel manipulator is presented. The investigations of this paper will provide suggestions to improve the structure and control algorithm optimization for the dual parallel mechanism in order to achieve the features of both larger workspace and higher motion precision.     

Optimal design of gear pumps for exhaust gas aftertreatment applications

In this paper an innovative procedure for determining the optimal design of an external spur gear pump for a particular emission reduction application in automobiles has been proposed. The pump forms the main part of a mechatronic system that controls the flow rate of a mixture of urea in water to catalytically reduce emissions in diesel engines. The proposed research proves to be an advance in gear machine design by using a multi-objective based genetic algorithm, to determine the optimal design of the gears and the casing by maximizing the volumetric efficiency, minimizing pressure overshoots, localized cavitation and noise emissions. The research uses HYGESim (HYdraulic GEar machines Simulator) simulation tool, which is being developed by the authors’ research group, for calculating the important performance features of the machine. The best designs for the machine based on enhancement in performance are presented. Results in terms of simulations and tests which validate the effectiveness of the proposed novel design methodology are also presented.     

User-system cooperative evolutionary computation for both quantitative and qualitative objective optimization in image processing filter design

This study proposes a cooperative evolutionary optimization method between a user and system (CEUS) for problems involving quantitative and qualitative optimization criteria. In a general interactive evolutionary computation (IEC) model, both the system and user have their own role in the evolution, such as individual reproduction or evaluation. In contrast, the proposed CEUS allows the user to dynamically change the allocation of search roles between the system and user, resulting in simultaneous optimization of qualitative and quantitative objective functions without increasing user fatigue. This is achieved by a combination of user evaluation prediction and the integration of interactive and non-interactive EC. For instance, the system performs a global search at the beginning, the user then intensifies the search area, and finally the system conducts a local search in the intensified search area. This study applies CEUS to an image processing filter design problem that involves both quantitative (filter output accuracy) and qualitative (filter behavior) criteria. Experiments have shown that the proposed CEUS can design image filters in accordance with user preferences, and CEUS interacting with a non-naive user enhanced the initial global search so that it converged and found a reasonable solution more than four times faster than a non-interactive search.     

Optimal design of adaptive structures: Part I. Remodeling for impact reception

The paper (written in two parts) is devoted to the presentation of numerical tools, based on the so-called virtual distortion method (VDM) for fast structural reanalysis and to the application of this tools for optimal design of adaptive structures exposed to impact loads. The first paper deals with fast modifications of the material distribution (coupled stiffness and mass redistribution) in dynamically loaded structures, which allows their optimal remodeling, e.g., to minimize average deflections. The VDM-based approach allows analytical sensitivity determination, which is very helpful in efficient implementation of the optimization procedure, utilized to solve the defined remodeling problem. The presented methodology is illustrated with a numerical example of truss–beam structure exposed to random impact loads.     

Optimal design of a 2-DOF parallel manipulator with actuation redundancy considering kinematics and natural frequency

In this paper, a planar 2-DOF parallel manipulator with actuation redundancy is proposed and the optimal design considering kinematics and natural frequency is presented. The stiffness matrix and mass matrix are derived, and the structural dynamics is modeled. The natural frequency is obtained on the basis of dynamic model. Based on the kinematic performance, the range for link length is given. Then, considering the natural frequency, the geometry is optimized. The natural frequency is simulated and compared with the corresponding non-redundant parallel manipulator. The designed redundant parallel manipulator has desired kinematic performance and natural frequency and is incorporated into a 4-DOF hybrid machine tool.     

桥式起重机智能定制与报价系统开发

通过长期对桥式起重机结构和企业需求的分析研究,将快速智能设计与智能报价两者相结合。以VB6.0为编程工具,Access为数据支撑,运用模块化与参数化技术,二次开发技术以及基于混沌遗传算法的主梁优化设计等关键技术。开发了桥式起重机智能快速定制与报价系统。该系统可根据用户定制参数进行设计计算、优化设计以及快速报价,为企业快速响应用户需求、缩短产品设计周期、降低企业设计成本奠定了技术基础,其对桥式起重机的长期发展具有深远影响。     

Conceptual design and analysis of the 2T1R mechanism for a cooking robot

This paper deals with the design and analysis of a two-translation and one-rotation (2T1R) mechanism for a novel cooking robot. Firstly the motions involved in stir-fry, the most representative operation in the cooking processes used in Chinese cuisine, are analyzed in details. Then the featured motions are decomposed into four main movements that are used as a design base for a wok motion mechanism. Several three-degrees-of-freedom (DOF) parallel manipulators are considered. From these, a 2T1R mechanism is selected as an ideal candidate. A 4-DOF (2T1R+1T) cooking robot is constructed by combining the 2T1R parallel manipulator with a 1-DOF linear feed mechanism. It is shown that the combined 4-DOF robot can perform the required cooking operations, particularly the stir-fry. The analysis conducted on the proposed 2T1R parallel manipulator includes inverse kinematics, forward kinematics, the velocity analysis, the constant orientation workspace, and the total orientation workspace. A prototype of the cooking robot is developed. The experiments verify that the proposed cooking robot is suitable for performing the required operations.     

形成三星星座的最优脉冲变轨的控制与仿真

由于火箭发射入轨精度的限制,无法直接发射形成星座,星座的形成需要变轨。该文针对三星星座,进行星座发射中的最优脉冲式变轨研究,文中基于卫星相对运动状态转移方程,推出了星座双脉冲式变轨控制的理论解;利用遗传算法,对双脉冲式变轨的脉冲控制量进行了优化仿真;探讨了星座脉冲式变轨的工程实现途径,为工程应用和研究提供参考。     

Concurrent design of controller and passive elements for robots with impulsive actuation systems

There are some biological evidences showing that the actuation system in legged animals is impulsive; it is not continuous. As opposed to continuous control/actuation, the control actions occur in specific intervals, and from the instant of one actuation until the start of the next one, passive elements guarantee the stability of the robotic system and govern its natural dynamics. In this paper, we present an analytical method for concurrent design of impulsive controller and passive elements (compliance and damper) for robotic systems; e.g., manipulators and legged-robots. To optimize the force profiles of passive elements, three different cost functions are presented which optimize the natural dynamics and energy consumption of the robot. The presented method can be applied to both cyclic and non-cyclic (explosive) tasks so as to attain energy efficient and bio-inspired motions. The method is applied to three biological models: a simulated human arm for throwing an object, a swing leg for drawing an oval, and a 3D quadruped robot for performing walking gait. Our findings in the simulation studies are in line with the hypothesis of impulsive actuation in nature and show the applicability of our method in robotics.     

Optimal input design for parameter estimation in a single and double tank system through direct control of parametric output sensitivities

In this paper the traditional and well-known problem of optimal input design for parameter estimation is considered. In particular, the focus is on input design for the estimation of the flow exponent present in Bernoulli's law. The theory will be applied to a water tank system with a controlled inflow and free outflow. The problem is formulated as follows: Given the model structure (f, g), which is assumed to be affine in the input, and the specific parameter of interest (θ), find a feedback law that maximizes the sensitivity of the model output to the parameter under different flow conditions in the water tank. The input design problem is solved analytically. The solution to this problem is used to estimate the parameter of interest with a minimal variance. Real-world experimental results are presented and compared with theoretical solutions.     

Parametric modelling and evolutionary optimization for cost-optimal and low-carbon design of high-rise reinforced concrete buildings

Design optimization of reinforced concrete structures helps reducing the global carbon emissions and the construction cost in buildings. Previous studies mainly targeted at the optimization of individual structural elements in low-rise buildings. High-rise reinforced concrete buildings have complicated structural designs and consume tremendous amounts of resources, but the corresponding optimization techniques were not fully explored in literature. Furthermore, the relationship between the optimization of individual structural elements and the topological arrangement of the entire structure is highly interactive, which calls for new optimization methods. Therefore, this study aims to develop a novel optimization approach for cost-optimal and low-carbon design of high-rise reinforced concrete structures, considering both the structural topology and individual element optimizations. Parametric modelling is applied to define the relationship between individual structural members and the behavior of the entire building structure. A novel evolutionary optimization technique using the genetic algorithm is proposed to optimize concrete building structures, by first establishing the optimal structural topology and then optimizing individual member sizes. In an illustrative example, a high-rise reinforced concrete building is used to examine the proposed optimization approach, which can systematically explore alternative structural designs and identify the optimal solution. It is shown that the carbon emissions and material cost are both reduced by 18–24% after performing optimization. The proposed approach can be extended to optimize other types of buildings (such as steel framework) with a similar problem nature, thereby improving the cost efficiency and environmental sustainability of the built environment.     

A comparison of simulated annealing and genetic algorithm for optimum design of nonlinear steel space frames

In this article, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames that are based on simulated annealing and genetic algorithm. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as the American Institute of Steel Construction (AISC) wide-flange shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraints for columns were imposed on frames. The algorithms were applied to the optimum design of three space frame structures, which have a very small amount of nonlinearity. The unconstrained form of objective function was applied in both optimum design algorithms, and constant penalty factors were used instead of gradually increasing ones. Although genetic algorithm took much less time to converge, the comparisons showed that the simulated annealing algorithm yielded better designs together with AISC-LRFD code specification.