A HOLONIC FRAMEWORK OF RECONFIGURABLE SHOP FLOOR CONTROL SYSTEMS IN AUTOMATED MANUFACTURING SYSTEMS

The agility and the flexibility of the current shop floor control systems have been limited so far, owing to the lack of structural flexibility and agility in its control software layer. Most of them are based on traditional hierarchical architecture and the top down approach and depend structurally on their specific configuration and job scheduling. Not only can they hardly satisfactorily adapt to these increasing changes and disturbances, but also make the redevelopment and maintenance of shop floor control system (SFCS) to need high cost and much time. And SFCS based on the heterarchical architecture don′t provide a predictable and high performance system, especially not in the heterogeneous environments, where the resources are scarce and the current decisions have serious repercussions on the future performances. For this reason, the heterarchical control is hardly applied in industry. Obviously, it is necessary to develop a new structural framework of reconfigurable SFCS to improve their agility, flexibility and maintainability. This paper presents a holonic framework of reconfigurable SFCS based on holonic manufacturing concepts. The framework is composed of resource holons, product holons and other staff holons. The model of each holon and the co operative mechanisms of holons are described. To verify the proposed approach experimentally, a prototype reconfigurable SFCS for a flexible manufacturing shop floor producing discrete parts is implemented.

Powertrain Torque Control Based on Torque Observer

To reduce shock during transmission gear shift, a transmission torque feedback closed loop control system is proposed based on the powertrain system model and a torque observer. The ignition time of engine was delayed to reduce transmission output shaft torque during gear shift. In contrast to traditional control method, the closed loop control system based on torque observer can obviously reduce the transmission output shaft torque during gear shift. It can be concluded that by way of torque feedback closed loop control, transmission shift shock can be reduced.

Integrated Automation of Power Plant Electrical System

Aiming at the comparatively laggard level of power plant electrical system automation, this paper analyzes the feasibility,necessity and some key points of the application of integrated automation technology to power plant electrical system. New idea using fieldbus control system technology is presented. This paper also gives the outline and detailed schemes.

Threshold decision for instrument control system and its application in nuclear power plant

Threshold decision is an important function of nuclear instrument control system based on physical parameters threshold decision. Because the conventional decision methods lack correlation with time and conditions, by analyzing the existing methods, some optimized methods are adopted. Considering safety, those methods are improved in data processing algorithms, floating threshold with multiple values, association with specific working condition, etc. These measures im- prove the nuclear instrument control system in fault tolerance and fault diagnosis, especially, the shutdown number of nucle- ar power plant decreases.

NECESSARY AND SUFFICIENT CONDITIONS FOR QUADRATIC STABILITY OF UNCERTAIN DISCRETE TIME SYSTEMS

The robust stability analysis of discrete time systems with fast time varying uncertainties is considered in this paper. The necessary and sufficient conditions for quadratic stability are presented. Moreover, the stability robustness index is introduced as the measurement of the stability robustness. For the systems with given uncertain parameter bounds, checking the necessary and sufficient conditions and calculating the stability robust index are converted to solving minimax problems. It is shown that the maximization can be reduced to comparisons between the functional values of the corners when the parameter region is bounded by hyperpolydredon, and any local minimum value in the minimization is exactly the global minimum.

NOVEL DESIGN OF ENERGY CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE

A novel design method of control strategy for a parallel hybrid electric vehicle is proposed. The sequential quadratic programming（SQP） is first used to solve the optimal problem of maximizing system efficiency in terms of the global optimization. And then a fuzzy logic controller is developed to implement the optimal control strategy for a tradeoff between the engine and the battery in local. In addition, the performance of the fuzzy system is improved by optimizing the fuzzy rules based on the SQP results. Simulation results show that the proposed control strategy achieves better fuel economy under the duty cycle.

Optimum Design of the Control System for a Laser Beam Riding Guidance Anti-Tank Missile

The optimum theory and methods were adopted to design the laser beam riding guidance anti tank missile's control system in the short run. Through building the mathematical model of system, selecting a proper method and taking advantage of computer's high speed calculation and logic traits, an optimal controller was designed. Simulation results showed that the designed control system has fair performance and it satisfies the tactical and technical requirements. The results also demonstrate that by the combination of the optimizing methods and the computer the control system could be designed as soon as possible.

Multivariate Statistical Process Monitoring and Control: Recent Developments and Applications to Chemical Industry

Multivariate statistical process monitoring and control (MSPM&C) methods for chemical process monitoring with statistical projection techniques such as principal component analysis (PCA) and partial least squares (PLS) are surveyed in this paper. The four-step procedure of performing MSPM&C for chemical process, modeling of processes, detecting abnormal events or faults, identifying the variable(s) responsible for the faults and diagnosing the source cause for the abnormal behavior, is analyzed. Several main research directions of MSPM&C reported in the literature are discussed, such as multi-way principal component analysis (MPCA) for batch process, statistical monitoring and control for nonlinear process, dynamic PCA and dynamic PLS, and on-line quality control by inferential models. Industrial applications of MSPM&C to several typical chemical processes, such as chemical reactor, distillation column, polymerization process, petroleum refinery units, are summarized. Finally, some concluding remarks and future considerations are made.

INVESTIGATION IN REDUCING EXHAUST EMISSIONS FROM TWO STROKE MOTORCYCLES

Test results of reducing two stroke motorcycle emissions with new type carburettors and electronic fuel injection systems are presented. Analyses and comparison between different systems are discussed. The adoption of electronically controlled injection and corresponding electronic control technique is an effective measure of prolonged vitality to improve emissions from two stroke motorcycles. Suggestions about the strategic steps of China′s motorcycle emission control are proposed.

Linear and nonlinear control of a robotic excavator

Various control systems for a robotic excavator named LUCIE (Lancaster University Computerized and Intelligent Excavator),were investigated. The excavator is being developed to dig trenches autonomously. One stumbling block is the achievement of adequate,accurate,quick and smooth movement under automatic control. Here,both classical and modern approaches are considered,including proportional-integral-derivative (PID) control tuned by conventional Zigler-Nichols rules,linear proportional-integral-plus (PIP) control,and a novel nonlinear PIP controller based on a state-dependent parameter (SDP) model structure,in which the parameters are functionally dependent on other variables in the system. Implementation results for the excavator joint arms control demonstrate that SDP-PIP controller provides the improved performance with fast,smooth and accurate response in comparison with both PID and linearized PIP control.

Iterative Learning Control With Incomplete Information： A Survey

Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.

Optimization of actuator/sensor position of multi-body system with quick startup and brake

A new method was put forward to optimize the position of actuator/sensor of multi-body system with quick startup and brake. Dynamical equation was established for the system with intelligent structure of piezoelectric actuators. According to the property of the modes varying with time, the performance index function was developed based on the optimal configuration principle of energy maximal dissipation, and the relevant optimal model was obtained. According to its characteristic, a float-encoding genetic algorithm, which is efficient, simple and excellent for solving the global-optimal solution of this problem, was adopted. Taking the plane manipulator as an example, the result of numerical calculation shows that, after the actuator/sensor position being optimized, the vibration amplitude of the multi-body system is reduced by 35% compared with that without optimization.

Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints

Abstract--In this paper, an adaptive neural network （NN） control approach is proposed for nonlinear pure-feedback sys- tems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions （BLFs） with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closed- loop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach. Index TermsmAdaptive control, neural networks （NNs）, non- linear pure-feedback systems, time-varying constraints.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

Analysis of the effect on control systems of order variation for fractional-orderPI~λD~μcontrollers

This paper is concerned with fractional-order PI~λD~μcontrollers. The definitions and properties of fractional calculus are introduced. The mathematical descriptions of a fractional-order controller and fractional-order control systems are outlined. The effects on control systems of order variation for fractional-order PI~λD~μ controllers are investigated by qualitative analysis and simulation. The conclusions and simulation examples are given. The results show the fractional-order PI~λD~μ controller is not sensitive to variation of its order.

Control synthesis for polynomial nonlinear systems and application in attitude control

A method for positive polynomial validation based on polynomial decomposition is proposed to deal with control synthesis problems. Detailed algorithms for decomposition are given which mainly consider how to convert coefficients of a polynomial to a matrix with free variables. Then, the positivity of a polynomial is checked by the decomposed matrix with semidefinite programming solvers. A nonlinear control law is presented for single input polynomial systems based on the Lyapunov stability theorem. The control synthesis method is advanced to multi-input systems further. An application in attitude control is finally presented. The proposed control law achieves effective performance as illustrated by the numerical example.

Hydraulic support stability control of fully mechanized top coal caving face with steep coal seams based on instable critical angle

Analyzed the support instable mode of sliding,tripping,and so on,and believed the key point of the support stability control of fully mechanized coal caving face with steep coal seams was to maintain that the seam true angle was less than the hydraulic support instability critical angle.Through the layout of oblique face,the improvement of support setting load,the control of mining height and nonskid platform,the group support system of end face,the advance optimization of conveyor and support,and the other control tech- nical measures,the true angle of the seam is reduced and the instable critical angle of the support is increased,the hydraulic support stability of fully mechanized coal caving face with steep coal seams is effectively controlled.

Energy Efficient Predictive Control for Vapor Compression Refrigeration Cycle Systems

Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.

VPLS Based Quality and Cost Control for Tennessee Eastman Process

Product quality and operation cost control obtain increasing emphases in modern chemical system engineering. To improve the fault detection power of the partial least square (PLS) method for quality control, a new QRPV statistic is proposed in terms of the VP (variable importance in projection) indices of monitored process variables, which is significantly advanced over and different from the conventional Q statistic. QRPV is calculated only by the residuals of the remarkable process variables (RPVs). Therefore, it is the dominant relation between quality and RPV not all process variables (as in the case of the conventional PLS) that is monitored by this new VP-PLS (VPLS) method. The combination of QRPV and T2 statistics is applied to the quality and cost control of the Tennessee Eastman (TE) process, and weak faults can be detected as quickly as possible. Consequently, the product quality of TE process is guaranteed and operation costs are reduced.

Introduction to Unity of Physics and Biology, Inorganic Life Materials

The unity between physics and biology refers to that the inorganic systems： the Solar System, galaxies and artificial systems have the same structures and functions as the organisms. The development of science and technology is demonstrating the intense unification trends of physics and biology and a holistic science and technology era is about to start. The physics and biology unify on the basis of the four seasons＇ law, which is the most important rule of the universe. Life is defined as the four seasons＇ whole with the structure and process of four seasons. The organism is basically structured into a dual four-season body by state-varying, state-stabilizing and control organizations. Animals, the Solar System and the earth are all the dual four-season bodies. In the unity between physics and biology, the inorganic life materials and inorganic life body can be manufactured artificially.