浅谈美国警察自由裁量权的控制

警察自由裁量权是警察权中最显著和独特的一部分。由于它在执法过程中衍生出来的各种问题,使其在被发现之日起,美国的警政专家就对此进行了大量的研究,并探索出了有效的控制方法。

FUZZY ADAPTIVE CONTROL OF FLEXIBLE-LINK ROBOT MANIPULATOR

A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.

Influence of Design Margin on Operation Optimization and Control Performance of Chemical Processes

Operation optimization is an effective method to explore potential economic benefits for existing plants. The m.aximum potential benefit from operationoptimization is determined by the distances between current operating point and process constraints, which is related to the margins of design variables. Because of various ciisturbances in chemical processes, some distances must be reserved for fluctuations of process variables and the optimum operating point is not on some process constraints. Thus the benefit of steady-state optimization can not be fully achied（ed while that of dynamic optimization can be really achieved. In this study, the steady-state optimizationand dynamic optimization are used, and the potential benefit-is divided into achievable benefit for profit and unachievable benefit for control. The fluid catalytic cracking unit （FCCU） is used for case study. With the analysis on how the margins of design variables influence the economic benefit and control performance, the bottlenecks of process design are found and appropriate control structure can be selected.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Optimal Trajectory Planning of the Dual Arm Manipulator Using DAMM

This paper presents an optimal trajectory planning method of the dual arm manipulator using Dual Arm Manipulability Measure （DAMM）. When the manipulator carries an object from a certain position to the destination, various trajectory candidates could be conskied. TO select the optimal trajectacy from the several candidates, energy, time, and the length of the tmjecttay could be utilized. In order to quantify the carrying effidency of dual-arms, DAMM has been defined and applied for the decision of the optimal path. DAMM is defined as the interaction of the manipulability ellipsoids of the dualarras, while the manipulability measure irdicates the relationship between the joint velocity and the Cartesian velocity for each ann. The cast function for achieving the optimal path is defined as the Summation of the distance to the goal and inverse of this DAMM, which aims to generate the efficient motion to the goal. It is confirmed that the optimal path planning keeps higher manipulability through the short distance path by using computer simulation. To show the effectiveness of this cooperative control algorithm experimentally, a 5-DOF dual-ann robot with distributed controllers for synchronization control has been developed and used for the experiments.

The Implementation of Decision Support System for Realizing Effective Usability of CNC Operator Knowledge Capturing System

This article describes experimental evaluations of the authors＇ previous studies on the knowledge-based system （KBS） aimed at capturing and managing CNC （Computer Numerical Control） operator knowledge. The proposed KBS follow thinking steps of CNC operators when they assess machining parameters described in the CAM （Computer Aided Manufacturing） file before proceeding to CNC machining processes. Also, the decision support system equipped with expert system （ES） has been proposed to realize efficient knowledge capturing system and effective usability of captured knowledge, and to recommend actions and decisions. From the viewpoint of providing useful information, the KBS should be aware of context or constraints in which the user has to deal with. In this study, the usefulness of DSS （Decision Support System） and ES is experimentally evaluated using real cases. Comparing the results of the testing participants with and without the DSS and ES, the effectiveness and usefulness were demonstrated. In addition, it was shown that the proposed system is also useful to narrow the discrepancies between CAM and CNC operators, focusing on CNC milling operations.

A Composite Model Predictive Control Strategy for Furnaces

Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control(CMPC)strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The controllers connected with two kinds of communication networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reasonable CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.

Distributed coordinated adaptive tracking in networked redundant robotic systems with a dynamic leader

Distributed coordinated control of networked robotic systems formulated by Lagrange dynamics has recently been a subject of considerable interest within science and technology communities due to its broad engineering applications involving complex and integrated production processes,where high flexibility,manipulability,and maneuverability are desirable characteristics.In this paper,we investigate the distributed coordinated adaptive tracking problem of networked redundant robotic systems with a dynamic leader.We provide an analysis procedure for the controlled synchronization of such systems with uncertain dynamics.We also find that the proposed control strategy does not require computing positional inverse kinematics and does not impose any restriction on the self-motion of the manipulators;therefore,the extra degrees of freedom are applicable for other sophisticated subtasks.Compared with some existing work,a distinctive feature of the designed distributed control algorithm is that only a subset of followers needs to access the position information of the dynamic leader in the task space,where the underlying directed graph has a spanning tree.Subsequently,we present a simulation example to verify the effectiveness of the proposed algorithms.