Control Methodology For Systems Research Articles

Soft computing simulation design of intelligent control systems in micro-nano-robotics and mechatronics

The soft computing simulation design methodology of intelligent control system for mobile micro-nano-robots based on modeling of non-linear dissipative equations of robots motion with a minimum entropy production is described. It includes hierarchical levels for description of dynamic behavior of mobile micro-nano-robots based on laws of microphysics, quantum logic of intelligent dynamic behavior of control objects, optimal control of states and dynamic system theory of mechanical motion. The description of a thermodynamic intelligent behavior (with minimum entropy production) of control objects (robots) and their interrelations with Lyapunov stability conditions are introduced. The role of soft computing on the basis of GA with a fitness function as a minimum entropy production for intelligent control of mobile micro-nano-robots is discussed.

Current status and future trends in the automation of mineral and metal processing

A review of the current status and future trends in the automation and control of mineral and metal processing is presented. Evaluation of publications on IFAC МММ events during the last 20 years shows some trends in the application of a number of process control methods in the MM industry. Classical control has seen an extraordinary wide application, but its inability to solve all the application problems of interest has led to further developments in control system methodologies and theory. One aim of this paper is to review the success of the translation of theoretically based developments into practice. Finally, the importance of Information Technology for the MM industry and process automation is highlighted and discussed.

A proposed control system/CAQC methodology and prediction system for the improvement of surface defects in the continuous casting of slabs

A control system or computer aided quality control system methodology is presented to determine surface defects in the continuous casting of steel slabs. When no defects are present, slabs can be either hot charged or direct rolled, thereby increasing the throughput of the system and decreasing energy consumption.

A novel fuzzy logic system based on N-version programming

For the consideration of different application systems, modeling the fuzzy logic rule, and deciding the shape of membership functions are very critical issues due to they play key roles in the design of fuzzy logic control system. This paper proposes a novel design methodology of fuzzy logic control system using the neural network and fault-tolerant approaches. The connectionist architecture with the learning capability of neural network and N-version programming development of a fault-tolerant technique are implemented in the proposed fuzzy logic control system. In other words, this research involves the modeling of parameterized membership functions and the partition of fuzzy linguistic variables using neural networks trained by the unsupervised learning algorithms. Based on the self-organizing algorithm, the membership function and partition of fuzzy class are not only derived automatically, but also the preconditions of fuzzy IF-THEN rules are organized. We also provide two examples, pattern recognition and tendency prediction, to demonstrate that the proposed system has a higher computational performance and its parallel architecture supports noise-tolerant capability. This generalized scheme is very satisfactory for pattern recognition and tendency prediction problems.

Numerical stability analysis of fuzzy control systems via quadratic programming and linear matrix inequalities

This paper proposes a numerical stability analysis methodology for the singleton-type linguistic fuzzy control systems based on optimization techniques. First, it demonstrates that a singleton-type linguistic fuzzy logic controller (FLC) can be converted into a region-wise sector-bounded controller or, more generally, a polytopic system by quadratic programming (QP). Next, the convex optimization technique called linear matrix inequalities (LMI) is used to analyze the closed loop of the converted polytopic system. Finally, the applicability of the suggested methodology is highlighted via simulation results.

An object oriented production planning system development in ERP environment

The planning and control concepts of production systems involve organizing and managing the process of converting raw materials into a predesigned finished product. In this paper, we present an object class extraction methodology of production planning and control system as a part of enterprise resource planning (ERP) environment. For extracting process, we (1) define the object classes within the system, (2) establish the relationships among classes, (3) establish hierarchical structure of classes, (4) establish the event trace diagram, (5) define the detail attributes and operations about object classes. Depending on the characteristics of the function, we divide the system into object class group associated with production plan function, object class group associated with production plan information, and object class group associated with user interface on a large scale.

ON THE BIRTH OF MULTIPLE LIMIT CYCLES IN NONLINEAR SYSTEMS

Degenerate (or singular) Hopf bifurcations of a certain type determine the appearance of multiple limit cycles under system parameter perturbations. In the study of these degenerate Hopf bifurcations, computational formulas for the stability indexes (i.e., curvature coefficients) are essential. However, such formulas are very difficult to derive, and so are usually computed by different approximation methods. Inspired by the feedback control systems methodology and the harmonic balance approximation technique, higher-order approximate formulas for such curvature coefficients are derived in this paper in the frequency domain setting. The results obtained are then applied to a study of nonlinear dynamical systems within the region of one periodic solution, bypassing a direct investigation of the multiple limit cycles and some tedious discussion of the complex multiplicity issue. Finally, we will show that several types of stability bifurcations can be controlled based on the results obtained in this paper.

An H approach to linear iterative learning control design

A new design methodology for iterative learning control systems is developed. It is based on the convergence condition for systems operating on an infinite time interval which is of the H∞ type. The principal idea of the design technique is to design a learning controller such that the speed of convergence is maximized, with a compromise to robustness. The issue of finite versus infinite trial lengths is addressed, as well as limitations on the best achievable rate of convergence due to structural properties of the plant.

AnH∞ approach to linear iterative learning control design

A new design methodology for iterative learning control systems is developed. It is based on the convergence condition for systems operating on an infinite time interval which is of the H∞ type. The principal idea of the design technique is to design a learning controller such that the speed of convergence is maximized, with a compromise to robustness. The issue of finite versus infinite trial lengths is addressed, as well as limitations on the best achievable rate of convergence due to structural properties of the plant.

Learning combined feedback and feedforward control of a musculoskeletal system.

The goal of this paper is the learning of neuromuscular control, given the following necessary conditions: (1) time delays in the control loop, (2) non-linear muscle characteristics, (3) learning of feedforward and feedback control, (4) possibility of feedback gain modulation during a task. A control system and learning methodology that satisfy those conditions is given. The control system contains a neural network, comprising both feedforward and feedback control. The learning method is backpropagation through time with an explicit sensitivity model. Results will be given for a one degree of freedom arm with two muscles. Good control results are achieved which compare well with experimental data. Analysis of the controller shows that significant differences in controller characteristics are found if the loop delays are neglected. During a control task the system shows feedback gain modulation, similar to experimentally found reflex gain modulation during rapid voluntary contraction. If only limited feedback information is available to the controller the system learns to co-contract the antagonistic muscle pair. In this way joint stiffness increases and stable control is more easily maintained.

Rigorous design of robust predictive controllers for processes with more inputs than outputs

In this paper we present a design methodology for multivariable Quadratic Dynamic Matrix Control (QDMC) systems with more manipulated variables than outputs. The algorithm requires the utilization of an end-condition and calculates low bounds on the move suppression coefficients in the on-line objective function. We show that these bounds are the solutions of an off-line constrained nonlinear minimization problem. The technique guarantees the robust stability of the closed-loop system, when both input and output constraints are present. The success of the method is illustrated through the application to an industrial case.

AVCS

This paper described AVCS, which is an APL-oriented version control system devised as a tool to track the history of software projects and to control concurrent access to project components. The basics of version control systems are explained, and specific aspects of applying a version control system methodology to project development in APL environments are considered. Particular attention is given to features which differentiate the approach accepted in AVCS from that of available version control and project management systems. Specification of AVCS's data maintenance, programming and user interface is presented to the extent required in order to explain how the system works. In conclusion, the possible application of AVCS to solving problems of porting APL projects across different environments is outlined.

Limitations to Input-Output Analysis of Cascade Control of Unstable Chemical Reactors

In this paper we show that the traditional methods of analyzing cascade control (based on series or parallel input/output relationships) should not be used when the primary and secondary processes are coupled, and the process is open-loop unstable. The connection between cascade control and traditional state feedback control is studied. In addition, we develop a cascade control system methodology which incorporates a specified inner-loop controller in the outer-loop controller design. This cascade control design procedure is compared to a conventional cascade control design procedure and to a noncascade control strategy.

A three-layered hierarchical path control system for mobile robots: Algorithms and experiments

Abstract Autonomous operation of mobile robots in unknown cluttered environments is one of the cornerstones of future applications of autonomous systems. This paper presents a three-layered hierarchical path control system for guiding a mobile robot through an unprepared cramped workspace to a specified goal point. It is assumed that the location of the robot with respect to a fixed world frame is provided by a suitable localization algorithm. The path control consists of three modules: global planning, local navigation , and collision avoidance . Each module is restricted to a subtask of limited competence and responsibility, allowing for on-line implementation within the associated time frames. The main emphasis is placed on achieving satisfactory performance with a minimum effort in sensing and computer hardware. Experimental results with the Siemens mobile platform ROAMER illustrate the methodology and performance of the path control system in unprepared cluttered environments.

Recursive on-line estimation of the specific growth rate from off-gas analysis for the adaptive control of fed-batch processes

A recursive estimation algorithm for the specific growth rate of aerobic fed-batch processes was developed. The estimate μ(t) is independent of the state estimates X(t) of the process. This improves the stability of the closed loop system. The performance of the nonlinear control system was tested on fermentations with streptomyces tendae with great success. The methodology of the nonlinear control system is very general. Thus, it can be applied to substrate control problems of any other aerobic fed-batch process.

Optimal population stabilization and control usingthe Leslie matrix model

We consider the problem of optimal stabilization and control of populations which follow the Leslie model dynamics, within state space and control systems theory and methodology. Various types of culling strategies are formulated and introduced into the Leslie model as control inputs, and their effect on global asymptotic stability is investigated. Our new approach provides answers to several unexplored problems. We show that in general it is possible to achieve a desired stable equilibrium population level, through the design of a class ofshifted-proportional stabilizing culling policies. Further, we formulate general non-linear constrained opitmization problems, for obtaining the cost-optimal policy among this generally infinite class of such stabilizing policies. The theoretical findings are illustrated through the solution of the problem over an infinite planning horizon for a numerical example. A comparative study of the costs and dynamic effects of various culling strategies also supports the mathematical results.

Design methodology for linear optimal control systems

Design methodology for linear optimal control systems

Hyperplane design techniques for discrete-time variable structure control systems

The design of variable structure control schemes for uncertain discrete-time systems is considered. Previous work in this area which parallels the discrete-time sliding mode philosophy with that for the continuous-time case is reviewed. Theoretical results are presented which indicate that such a parallel approach is not necessarily desirable. A novel design methodology for discrete-time variable structure control systems is then formulated. A numerical example is given to illustrate the results described.

A motion control algorithm for a continuous mining machine based on a hierarchical Real-time Control System design methodology

The drive toward increased safety for coal miners has led to the development of computer-assisted methods of underground coal mining. The development of control architectures for the control of the movement of continuous mining machines (tramming control) is an important part of this overall effort. The tramming control algorithm design described is in concert with hierarchical architecture design principles developed at National Institute of Standards and Technology (NIST), referred to as the Real-time Control Systems (RCS) methodology. The algorithm design allows for the control of both cutting and free-space movement by a continuous mining machine and allows for a high degree of human operator interaction.

Intelligent and Adaptive Control of FMS Contributing to CIM Trend

This paper addresses some basic concepts involved in a knowledge-based adaptive control system and dynamic adaptive scheduling methodology for FMSs, Recent advances in flexible automation resulted in a complex multiprocessing environment. To cope with dynamically changing external demands, internal production goals and unanticipated events arising at the factory floor, the proposed intelligent control system is provided with features contributing to the CIM trend, system adaptivity and a new modelreformulating approach to scheduling, in a real-time decision making environment.