Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

Smart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process

Lack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.     

基于人工制造约束的三维拓扑优化设计方法

为了更好地解决三维拓扑优化工程实用化的问题,提出了基于人工制造约束的拓扑优化设计方法。该方法在拓扑优化过程中实时地监控拓扑优化结果,并借助设计人员的工程经验,实时地加入符合制造工艺成型的约束条件辅助计算进行机拓扑优化设计。钢结构拱桥算例中以有限元软件ANSYS为平台进行二次开发、以双向渐进结构优化法为核心算法通过人为干预实现了在拓扑优化过程中钢结构拱桥斜支撑向竖直支撑的转变。通过对比发现该方法的优化结果与实际拱桥模型结构相似,表明了该方法是有效的和可行的。     

催化裂化烟气超低排放技术的可行性研究

工业废气是一项主要空气污染源。烟气超低排放技术是一项主流的烟气污染源治理方法。对催化裂化烟气超低排放技术进行研究,分析影响催化裂化烟气超低排放的制约因素,明确催化裂化烟气超低排放工程的注意事项。     

PDM++: Planning Framework from a Construction Requirements Perspective

Construction requirements represent the key preconditions for construction. These include topological precedence, key resources, space requirements, etc. Consequently, identifying them is necessary for feasible construction planning to be achieved. Despite this, little attention has been given to the impact of construction requirements on a project schedule, possibly because of the lack of a good tool for representing these requirements. This paper distinguishes construction requirements into static and dynamic types, according to changes in the need of the requirement during its life cycle. A modeling framework, PDM++, is then proposed. The framework deals with schedule constraints arising from both static and dynamic construction requirements, provides greater semantic expression to capture schedule constraints unambiguously, and facilitates the representation of interdependent conditional relationships. The concept of meta-intervals is also devised to represent complex requirements involving several activities and schedule constraints, and it facilitates modeling at higher levels of plan abstractions. Finally, an illustrative case study is presented to show the applicability of PDM++ in representing schedule constraints and alternative scheduling from a construction requirements perspective.     

基于Pro/E和ADAMS的双足步行机器人造型及仿真研究

对步行机器人的双足进行了三维造型及运动仿真研究。首先利用通用软件Pro/E对人形机器人支撑受力部位腿部进行了三维造型的设计与装配,并在相应软件中检测了装配的正确性及精确度。然后根据ZMP稳定判据分析得出机器人步行的稳定性条件,最后将腿部模型其导入ADAMS中并对其进行了步行运动仿真。研究结果表明,所设计的步行机器人双足关节转角插值正确合理、无干涉,能够较好满足双足机器人的步行需要,论文成果具备一定参考价值和积极意义。     

船用管件弯曲成型的有限元建模与实验验证

基于弯曲成型理论并结合船用管件弯曲成型的实际工况,采用ABAQUS/CAE模块建立了20钢管件的数控弯曲成型有限元模型,对建模过程中的力学模型、几何模型、单元定义、网格划分及其敏感性分析和约束接触设置等步骤进行了详细的说明。通过提取弯曲段横截面的最小壁厚值,与变形前的截面壁厚相比,定义了弯管外侧壁厚的减薄率。同时,通过提取畸变后的管件截面的椭圆长短轴,推导出了截面畸变程度质量指标的计算方法。与实验结果比较,有限元模型的计算结果与实验测量数据之间的相对误差较小,从而验证了有限元模型计算的精确度和可靠性,为管件的弯曲成型加工提供了理论依据,可应用于加工后管件质量的评价。     

Exponential ARX model-based long-range predictive control strategy for power plants

For nonlinear thermal power plants whose dynamics vary with load demand, a load-dependent exponential ARX (Exp-ARX) model, which can effectively describe the nonlinear properties of the plants, is presented. The Exp-ARX model requires only off-line identification. Based on the model, a constrained multivariable generalized predictive control (CMGPC) strategy is designed and implemented in a simulation of 375 MW thermal power plants. This CMGPC algorithm does not resort to on-line parameter estimation and can more exactly predict the future outputs of the nonlinear plants, so it shows better reliability and control performance than the usual GPC algorithm.     

A framework of critical resource chain for project schedule analysis

Analysing a schedule is beneficial to help stakeholders understand the scheduled project. Project schedules, which create time plans based on the critical path method (CPM) or on resource‐constrained project scheduling problem (RCPSP) optimization, are targets herein. The Theory of Constraints (TOC) treats a schedule as a system. Schedule elements are suspected constraints and a goal depends on the schedule creation policy. Resource information is further surveyed herein to identify true constraints. A framework is proposed to integrate identified constraints on a schedule, and the critical resource chain concept is introduced. Three scenarios illustrate the proposed framework under different scheduling considerations. Results explain schedule constraints, and several schedule analysis issues are discussed.     

Continuous-time norm-constrained Kalman filtering

This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two separate optimization problems, one which solves for the optimal observer gain associated with the unconstrained state estimates, while the other solves for the optimal observer gain associated with the constrained state estimates. The optimal constrained state estimate is found by projecting the time derivative of an unconstrained estimate onto the tangent space associated with the norm constraint. The special case where the entire state estimate is norm-constrained is briefly discussed. The utility of the filtering results developed are highlighted through a spacecraft attitude estimation example. Numerical simulation results are included.