Limited-resource scheduling by generalized rule-based system

A general paradigm for solving resource allocation, time-tabling, and scheduling problems is presented. The paradigm is based on an expert system approach, which looks for a feasible solution that satisfies the problem's real-life constraints. The new paradigm includes generic concepts for resources, activities, constraints, and allocations. The general control strategy of the new paradigm is suitable for a large family of resource allocation and time-tabling problems. This control strategy includes three parts that deal with allocation, constraint checking, and changes to allocations.

The proposed paradigm was tested on three real-world problems: crew assignment to air force missions, class scheduling for a university department, and time-tabling of final examinations for the faculty of natural sciences. All cases were solved well in a few minutes of central processing unit time, by Prolog-based systems that implemented the proposed paradigm. These case studies are described in the paper in some detail, and an overall evaluation of the methodology is given.     

RTC: Language support for real-time concurrency

This paper presents a model and language constructs for expressing timing and concurrency requirements in distributed real-time programs. Our approach combines an abstract data type paradigm for the specification of shared resources and a distributed transaction-based paradigm for the specification of application processes. Resources provide abstract views of shared system entities, such as devices and data structures. Each resource has a state and defines a set ofactions that can be invoked by processes to examine or change its state. A resource also specifies scheduling constraints on the execution of its actions to ensure its consistency. Processes access resources by invoking actions and by expressing precedence, execution and timing constraints on action invocations. The implementation of our language constructs and the use of this system to control the simulation of a distributed robotics application is also described.This work is supported in part by the following grants: ARO DAAG-29-84-k-0061, ONR N000014-89-J-1131, and NSF CCR90-14621.     

A framework for receding-horizon control in infinite-horizon aggregative games

A novel modelling framework is proposed for the analysis of aggregative games on an infinite-time horizon, assuming that players are subject to heterogeneous periodic constraints. A new aggregative equilibrium notion is presented and the strategic behaviour of the agents is analysed under a receding horizon paradigm. The evolution of the strategies predicted and implemented by the players over time is modelled through a discrete-time multi-valued dynamical system. By considering Lyapunov stability notions and applying limit and invariance results for set-valued correspondences, necessary conditions are derived for convergence of a receding horizon map to a periodic equilibrium of the aggregative game. This result is achieved for any (feasible) initial condition, thus ensuring implicit adaptivity of the proposed control framework to real-time variations in the number and parameters of players. Design and implementation of the proposed control strategy are discussed and an example of distributed control for data routing is presented, evaluating its performance in simulation.     

含不等式约束的欠驱动系统约束跟随控制

在运动控制领域, 欠驱动机械系统通常需要满足一系列的等式约束(完整或非完整的)以便获得较好的运动 表现, 同时出于安全考虑还需要满足一定的不等式约束条件. 本文提出了一种约束跟随控制方法, 用以解决同时含 等式和不等式约束的欠驱动系统控制问题. 该控制设计主要分为两步: 第1步: 只考虑系统需要满足的等式约束, 运 用约束跟随控制方法推导出基于系统模型的状态反馈控制律; 第2步: 考虑系统需要满足的不等式约束, 先通过状 态变量映射将不等式约束整合到原等式约束中以得到新的等式约束, 再基于新的等式约束和第1步所述的约束跟随 控制方法, 推导出系统所需的状态反馈控制律. 将该约束跟随控制方法应用于三自由度非线性强耦合的欠驱动平面 垂直起降(PVTOL)飞行器. 仿真结果表明, 该控制方法能有效处理PVTOL飞行器运动过程中需满足的等式约束(轨 迹跟踪和姿态保持)和不等式约束(边界服从).     

基于LMI优化的主动悬架多目标控制

首先将汽车主动悬架的控制问题归结为有时域硬约束的鲁棒干扰抑制问题.在多目标控制框架下,基于线性矩阵不等式(LMI)优化技术,提出了一种H2/广义H2混合控制策略:利用广义H2范数描述系统的时域硬约束,同时选择H2范数最小化系统的性能输出,最终将系统的控制律归结为求解具有LMI约束的半定规划问题.以半车模型为例设计了主动悬架控制器,并给出了较全面的分析和仿真结论.最后利用快速原型(RCP)和硬件在回路仿真(HILS)一体化技术进一步验证所提方法的有效性和可行性.     

Interactive constrained dynamics for rigid and deformable objects

Following the continuous increase in computational power of consumer hardware, interactive virtual environments have been recently enriched with more and more complex deformable objects. However, many physics engines are still very limited in the way they handle interacting rigid and deformable objects. This paper proposes a constraint‐based approach to real‐time simulation of coupled rigid and deformable objects capable of providing two‐way interactions. Similar techniques have seen widespread usage for either rigid or deformable objects, but not for the simultaneous simulation of both. By extending such approaches, we show not only how interaction is possible but also how it can be performed at real‐time rates. We address contact response and also show how to implement typical constraints to enforce limitations in the degrees of freedom and to enhance the dynamical properties of deformable objects. The method is easily integrated into existing physics engines that use similar constraint solvers and is independent on the kind of deformable object paradigm chosen. The provided simulation results show that the method is fast and effective in handling contacts between rigid and deformable objects and in simulating friction and other kinds of constraints. Copyright © 2015 John Wiley & Sons, Ltd.     

基于SQP/GA混合优化算法的双容水箱非线性预测控制

为了计算控制序列，非线性模型预测控制可以转换为一个带约束的非线性优化过程．本文分析了三种约束处理方案，根据遗传算法的特点，将等式约束用于状态量计算，在搜索空间降维的同时消除遗传算法难以求解的等式约束．对双容水箱进行遗传算法和序列二次规划仿真试验和实际控制，结果表明遗传算法对控制量的优化效果优于序列二次规划．为克服遗传算法耗时较长、优化结果存在随机抖动的缺点，结合序列二次规划提出一种混合优化算法，仿真和实控结果表明其可行性和有效性．     

Evolution and development of neural controllers for locomotion,gradient-following, and obstacle-avoidance in artificial insects

This paper describes how the SGOCE paradigm has been used to evolve developmental programs capable of generating recurrent neural networks that control the behavior of simulated insects. This paradigm is characterized by an encoding scheme, an evolutionary algorithm, syntactic constraints, and an incremental strategy that are described in turn. The additional use of an insect model equipped with six legs and two antennae made it possible to generate control modules that allowed it to successively add gradient-following and obstacle-avoidance capacities to walking behavior. The advantages of this evolutionary approach, together with directions for future work, are discussed.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.     

State-based versus event-based specifications for information systems: a comparison of B and eb 3

This paper compares two formal methods, B and eb³, for specifying information systems. These two methods are chosen as examples of the state-based paradigm and the event-based paradigm, respectively. The paper considers four viewpoints: functional behavior expression, validation, verification, and evolution. Issues in expressing event ordering constraints, data integrity constraints, and modularity are thereby considered. A simple case study is used to illustrate the comparison, namely, a library management system. Two equivalent specifications are presented using each method. The paper concludes that B and eb³ are complementary. The former is better at expressing complex ordering and static data integrity constraints, whereas the latter provides a simpler, modular, explicit representation of dynamic constraints that are closer to the user’s point of view, while providing loosely coupled definitions of data attributes. The generality of these results from the state-based paradigm and the event-based paradigm perspective are discussed.     

Using collaborative computing technologies to enable the sharing and integration of simulation services for product design

Nowadays simulation is commonly used in engineering design for verifying design concepts before physical prototypes are produced. The simulation of complex products such as mechatronics in general involves a synergy of multiple traditional disciplinary areas and entails the collaborative work of a multidisciplinary team. A need thus arises for supporting the effective and efficient integration of subsystem models at simulation runtime and in a distributed environment. These models are generally created using different simulation tools and depend on the inputs from each other to perform numerical integration. As such, many issues need to be addressed, e.g. system modeling, the use of computing technologies, and the runtime interaction between models. In this paper, a service-oriented paradigm is presented which is underpinned by collaborative computing technologies to enable the provision of simulation models as services as well as the integration of these services for performing simulation tasks in product design. As well as the implementation of such a paradigm, a method for the interaction between models is in particular developed to achieve high accuracy for the simulation of design problems involving the solving of system equations. Preliminary evaluation work shows that the proposed paradigm underpinned by collaborative computing technologies is viable and have great potential in supporting collaborative simulation development in industry and the method for interaction control successfully achieves better accuracy compared with traditional methods.     

主旋翼升力和机身姿态受限的模型直升机非线性控制（英文）

A nonlinear control is proposed for trajectory tracking of a 6-DOF model-scaled helicopter with constraints on main rotor thrust and fuselage attitude. In the procedure of control design, the mathematical model of helicopter is simplified into three subsystems: altitude subsystem, longitudinal-lateral subsystem and attitude subsystem. The proposed control is developed by combining the sub-controls for the corresponding subsystems. The sub-controls for altitude subsystem and longitudinal-lateral subsystem are designed with hyperbolic tangent functions to satisfy the constraints; the sub-control for attitude subsystem is based on backstepping technique such that fuselage attitude tracks the virtual control for longitudinallateral subsystem. It is proved theoretically that tracking errors are ultimately bounded, and control constraints are satisfied.Performances of the proposed controller are demonstrated by simulation results.     

主旋翼升力和机身姿态受限的模型直升机非线性控制

针对主旋翼升力和机身姿态受限的6自由度模型无人直升机的轨迹跟踪控制问题设计了一种非线性控制器.在控制器设计过程中,直升机的数学模型被简化为三个子系统: 姿态子系统,纵-侧向子系统和高度子系统,所设计的控制器由针对这三个子系统的子控制器组成.纵-侧向和高度子控制器基于双曲正切函数进行设计,以保证满足受限条件; 姿态子控制器利用反步法设计,使得机身姿态能够跟踪纵-侧向和高度子系统的虚拟控制.本文在理论上证明了闭环系统跟踪误差最终有界,并且控制器满足受限条件.仿真结果证实了所设计控制器的性能.     

Solving Mixed and Conditional Constraint Satisfaction Problems

Constraints are a powerful general paradigm for representing knowledge in intelligent systems. The standard constraint satisfaction paradigm involves variables over a discrete value domain and constraints which restrict the solutions to allowed value combinations. This standard paradigm is inapplicable to problems which are either:(a) mixed, involving both numeric and discrete variables, or(b) conditional,¹ containing variables whose existence depends on the values chosen for other variables, or(c) both, conditional and mixed.We present a general formalism which handles both exceptions in an integral search framework. We solve conditional problems by analyzing dependencies between constraints that enable us to directly compute all possible configurations of the CSP rather than discovering them during search. For mixed problems, we present an enumeration scheme that integrates numeric variables with discrete ones in a single search process. Both techniques take advantage of enhanced propagation rule for numeric variables that results in tighter labelings than the algorithms commonly used. From real world examples in configuration and design, we identify several types of mixed constraints, i.e. constraints defined over numeric and discrete variables, and propose new propagation rules in order to take advantage of these constraints during problem solving.     

基于遗传算法的结晶器液位约束广义预测控制

针对实际连铸过程中结晶器液位控制须满足多种约束的问题,将一种基于遗传算法的有约束广义预测控制方法（ＧＣＧＰＣ）应用于结晶器液位控制．首先基于机理模型构造了有约束结晶器液位广义预测控制器;然后以遗传算法处理带约束的非线性优化问题,并以此作为滚动优化策略,求得最优控制律．仿真结果表明,在有效处理了约束的基础上,基于遗传算法的有约束广义预测控制效果优于ＰＩＤ 控制以及无约束广义预测控制．     

A distributed constraint-based scheduler

This paper presents the design and implementation of a distributed advisory system which helps different human experts in the management and control of traffic within railway stations and along railway branches. Our approach allows the management of a whole railway line in a modular, expandable and scalable way. The scheduling of trains along a railway line is performed by several modules each one controlling a certain number of resources. These modules solve the scheduling of trains by interacting and communicating with each other. Each module has to deal with temporal constraints, priority between trains and constraints due to the structure of the station and railway branches. Our approach is based on the constraint logic programming (CLP) paradigm for solving the constraints involved in the problem. Therefore, this paper shows the versatility and adequacy of the CLP approach for the problems of this type.     

Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints

In this paper, adaptive tracking control is proposed for a class of uncertain multi-input and multi-output nonlinear systems with non-symmetric input constraints. The auxiliary design system is introduced to analyze the effect of input constraints, and its states are used to adaptive tracking control design. The spectral radius of the control coefficient matrix is used to relax the nonsingular assumption of the control coefficient matrix. Subsequently, the constrained adaptive control is presented, where command filters are adopted to implement the emulate of actuator physical constraints on the control law and virtual control laws and avoid the tedious analytic computations of time derivatives of virtual control laws in the backstepping procedure. Under the proposed control techniques, the closed-loop semi-global uniformly ultimate bounded stability is achieved via Lyapunov synthesis. Finally, simulation studies are presented to illustrate the effectiveness of the proposed adaptive tracking control.     

Optimal Navigation for a Differential Drive Disc Robot: A Game Against the Polygonal Environment

This paper considers the problem of globally optimal navigation with respect to minimizing Euclidean distance traveled by a disc-shaped, differential-drive robot (DDR) to reach a landmark. The robot is equipped with a gap sensor, which indicates depth discontinuities and allows the robot to move toward them. In this work we assume that a topological representation of the environment called GNT has already been built, and that the landmark has been encoded in the GNT. A motion strategy is presented that optimally navigates the robot to any landmark in the environment, without the need of using a previously known geometric map of the environment. To our knowledge this is the first time that the shortest path for a DDR (underactuated system) is found in the presence of obstacle constraints without knowing the complete geometric representation of the environment. The robot’s planner or navigation strategy is modeled as a Moore Finite State Machine (FSM). This FSM includes a sensor-feedback motion policy. The motion policy is based on the paradigm of avoiding the state estimation to carry out two consecutive mappings, that is, from observation to state and then from state to control, but instead of that, there is a direct mapping from observation to control. Optimality is proved and the method is illustrated in simulation.     

自由漂浮空间机器人轨迹跟踪的模型预测控制

针对传统控制方法难以解决自由漂浮空间机器人(free-floating space robot, FFSR)轨迹跟踪过程中的各类约束的问题,采用模型预测控制对自由漂浮空间机器人的轨迹跟踪问题进行了研究.在自由漂浮空间机器人拉格朗日动力学模型的基础上,建立了系统伪线性化的扩展状态空间模型;在给定系统的性能指标和各类约束的情况下,基于拉盖尔模型设计相应的离散模型预测控制器,并证明控制器的稳定性,控制器中引入任务空间滑模变量实现了对末端期望位置和期望速度的同时跟踪;以平面二杆自由漂浮空间机器人为例,对无约束末端轨迹跟踪和有约束末端轨迹跟踪两种情况进行对比仿真验证.仿真结果表明,该模型预测控制器不仅可以实现对末端期望轨迹的有效跟踪,还能满足各类约束.     

输入受限不确定离散系统的灰色滑模控制

对于输入受限离散系统,首先构造出输入受限条件的等效约束矩阵,然后基于线性矩阵不等式给出了满足输入受限条件的切换函数时变参数的构造方法.采用离散趋近控制,结合李雅普诺夫函数和线性矩阵不等式方法提出了滑动模态渐近稳定的充分条件,对不确定部分建立灰色估计模型,证明了闭环系统的稳定性.理论和仿真表明,不仅利用到基于等效控制的滑模控制器构造简单、易于实现等优点,而且满足输入受限条件,克服了传统基于等效控制的滑模控制器瞬时输出量过大的缺点,有效地消除了系统抖振和不确定因素的影响.