Real-time Control Approach Research Articles

A real-time learning control approach for nonlinear continuous-time system using recurrent neural networks

In this paper, a real-time iterative learning control (ILC) approach for a nonlinear continuous-time system using recurrent neural networks (RNNs) with time-varying weights is presented. Two RNNs are utilized in the ILC system. One is used to approximate the nonlinear system and another is used to mimic the desired system response. The ILC rule is obtained by combining the two RNNs to form a neural network control system. Also, a kind of iterative RNNs training algorithm is developed based on the two-dimensional (2-D) system theory. An RNN using the proposed 2-D training algorithm is able to approximate any trajectory to a very high degree of accuracy. Simulation results show that the proposed ILC approach is very efficient. The newly developed 2-D RNNs training algorithms provides a new dimension to the application of RNNs in a nonlinear continuous-time system.

Central limit approximation approach for connection admission control in broadband satellite systems

The transient cell loss ratio (CLR) is investigated as a quality of service (QoS) measure for ATM satellite systems. To determine the QoS measure, a central limit approximation is proposed for a bufferless fluid model. The proposed approximation scheme is a promising approach for real-time connection admission control (CAC).

Improved Realtime Output Voltage Control of Series-Resonant High-Frequency AC-Linked DC-AC Converter

This paper proposes a series-resonant high-frequency AC linked DC-AC new-type converter and an improved realtime control approach for sinusoidal output voltage waveform, which is less influenced by the input voltage and load variations. By using application software of MATLAB, the simulation of this converter is offered to compare the performances of converter by applying the conventional control method and the proposed control method. The operation of the proposed converter with the proposed control method is verified by experiment and simulation results.

Rule-based approach for real-time reactive power control in interconnected power systems

This paper presents two rule-based modules for voltage profile improvement and power loss minimization of interconnected power systems. The first module is used to alleviate voltage limit violations based on the voltage sensitivities to the most effective voltage control devices in the network. The second module deals with power loss minimization by optimal adjustment of voltage control buses. In this module, the large-scale system is decomposed to small subsystems, and the solution of these subsystems is coordinated to minimize the overall network losses. The subsystem solutions are very fast and robust. The proposed modules minimize the actions taken and are suitable for real-time applications. The required rules are developed using turbo-Prolog and integrated with the network simulation programs. The performance of the developed modules is evaluated on a real power system and the obtained results are presented in the paper.

A Sensor-Based Robot Transition Control Strategy

This article presents a real-time sensor-based control approach to the manipulation of the transition of a robot from free space motion to contact with an environment. Use is made of exter nal sensors, including proximity sensors and a force sensor at the end effector of the robot, to control the interaction between the robot and its environment. To achieve direct robot end-effector position control, a short-range fiber optic proximity sensor is used. A multi-phase cantrol strategy is proposed that includes an approach phase, where a force con trol scheme is used prior to contact, as well as a proximity phase where the proximity sensor-based control is employed. Implementation results carried out on an industrial robot are reported.

Distributed Approach to Real-Time Control of Complex Signalized Networks

Urban traffic characteristics are examined along with the various available current approaches to controlling traffic efficiently at signalized intersections. Fixed-time, central, and distributed real-time control approaches are considered. It is determined that the best method of control varies with network and flow conditions. It is concluded that for smooth traffic and uncomplicated networks that provide good opportunity for progression, a centralized quasi-real-time model such as the split, cycle, and offset optimization technique (SCOOT) is appropriate. However, when faced with significant demand fluctuations or interference from transit or emergency vehicles, a distributed real-time model will be required. The paper recommends use of a fully distributed model to deal with such conditions, at least for the foreseeable future until appropriate hierarchical models can be developed.

Distributed Approach to Real-Time Control of Complex Signalized Networks

Urban traffic characteristics are examined along with the various available current approaches to controlling traffic efficiently at signalized intersections. Fixed-time, central, and distributed real-time control approaches are considered. It is determined that the best method of control varies with network and flow conditions. It is concluded that for smooth traffic and uncomplicated networks that provide good opportunity for progression, a centralized quasi-real-time model such as the split, cycle, and offset optimization technique (SCOOT) is appropriate. However, when faced with significant demand fluctuations or interference from transit or emergency vehicles, a distributed real-time model will be required. The paper recommends use of a fully distributed model to deal with such conditions, at least for the foreseeable future until appropriate hierarchical models can be developed.

Real-Time Control of Robot Manipulators by Neural Networks

This paper describes an innovative approach for real-time kinematic control of robot manipulators by using neural networks. While different approaches in this field have appeared in the literature, this paper shows how control theory can be incorpora

Development of a knowledge-based approach for real-time predictive process control : T.H. Lee, C.C. Hang, S. Nungam, pp 847–850

Development of a knowledge-based approach for real-time predictive process control : T.H. Lee, C.C. Hang, S. Nungam, pp 847–850

Development of a Knowledge-Based Approach for Real-Time Predictive Process Control

In this paper, we present a knowledge-based approach to real-time predictive control which is applicable to a large class of industrial process control problems. The class of processes considered are those where dead-time IS significant and the .approach adopted is an integration of hard algorithms With knowledge-based methods. The paper also Includes the results of real-time experiments for level control In a coupled-tank system.

A knowledge-based pattern recognition approach for real-time diagnosis and control of fermentation processes as variable structure plants

A fundamental property of microbial systems, which are the central part of fermentation plants, is their structural variability. From the viewpoint of process control, this imposes serious difficulties because the problem of controlling variable structure plants is analytically unsolved. However, the amalgamation of some nonstandard methodologies offers possibilities for handling the variable structure phenomenon. Of special interest is the knowledge-based pattern recognition approach, which provides a natural basis for classification of the structural state of the microbial systems, and is well-suited to their uncertain characteristics. The development of such knowledge-based techniques and their application to the control of an amino acid production process are discussed. >

A New Approach for Real-Time Control of Urban Traffic Networks

Using a new decomposition-coordination approach, an efficient design method for traffic regulation in congested network is presented. A simplified network model is chosen here for testing the proposed two-level structure which alleviates some of the difficulties encountered with classical methods. A local feedback control law is determined which is based on the length of the vehicles queues at each intersection. This law is modified by a coordination term, calculated at the upper level, which takes into consideration the state of the traffic at other intersections. Due to the inherent flexibility of the method, state constraints are treated at the upper level. Only simple calculations are required to determine the control law, leading to short computation time and thus allowing real time control of over saturated networks. The results obtained on various examples confirm the advantages of the proposed technique.

An interpretive approach for interactive real-time control through a network

The CERN Super Proton Synchrotron (SPS) accelerator represents a large industrial control problem, with the additional complication that the control strategies are not fixed. Right from the beginning, it was decided to use an interpretive language for the control process. The main goal of this approach was to reduce the amount of programming effort needed for a proper control of the accelerator, by allowing the actual users — physicists, engineers and technicians — to write the control programs they needed. It very quickly appeared that this method was ideal for providing interactive tools for a control system based on a network. The requirement for interactive network control has been implemented by leaving to the user the choice of those parts of the network best suited for the execution of sections of his program. For that reason interpreter instructions have been defined, allowing the user to define where in the network a logical unit of his algorithm should be executed, and where individual items of the data should be stored. This strategy allows easy access to all the hardware through a distributed data-base. The interpreter being basically a string handler, equipment control can be packed into a module which is called from the program through a name with a standard input-output scheme. All this allows algorithm exportation, while network transfers are minimized. Such a system has been in operation since 1976. Many non-professional programmers are regularly writing or modifying ‘network procedures’ for everchanging control purposes. The simplicity and flexibility of the interpretive method has enabled many technical innovations to be installed over the years, and some of these are described.