Showing papers in "International Journal of Systems Science in 1999"
TL;DR: This work reviews the static scheduling research in which the setup time or cost is of main concern in the problem studied and classifed each situation on the basis of sequence dependence and separability of setup.
Abstract: We review the static scheduling research in which the setup time or cost is of main concern in the problem studied. The literature is classified into job, class and job-andclass setup situations. Also, each situation is further classifed on the basis of sequence dependence and separability of setup. Directions for future research on setup time problems are also identified.
110 citations
TL;DR: Trends in controlarchitectures for autonomous vehicles are described to show how developments in architectures for autonomous land vehicles have been extended for use in autonomous underwater vehicles.
Abstract: This article describes therecenttrends in controlarchitectures for autonomous vehicles. The study has been carried out on 22 architectures, most of which relate to the field of underwater robotics. The main aim of this article is to show the relationships between these various architectures and to show how developments in architectures for autonomous land vehicles have been extended for use in autonomous underwater vehicles. A summary of important features of the 22 architectures is presented and a new hybrid architecture is proposed for the underwater vehicle GARBI.
65 citations
TL;DR: This paper describes techniques which are candidates for control of a flight AUV and identifies controllers used on some existing vehicles.
Abstract: Unmanned, underwater vehicles have been developed considerably in recent years. Remotely operated vehicles (ROVs) are increasingly used for routine inspection and maintenance tasks but have a range that is limited by the umbilical cable. For long range operations, such as oceanographic exploration and surveying, autonomous underwater vehicles (AUVs) are emerging which haveon-board power and are equipped with advanced control capabilities to carry out tasks with the minimum of human intervention. AUVs typically resemble torpedoes in that mosthave control surfaces and a single propulsion unit, and must move forwards to manoeuvre. Such vehicles are called flight vehicles. This paper describes techniques which are candidates for control of a flight AUV and identifies controllers used on some existing vehicles. Since underwater vehicle dynamics are nonlinear, fuzzy logic and sliding mode control were felt to have promise for autopilot application due to their potential robustness. Following development using a...
63 citations
TL;DR: Sufficient conditions are proposed to solve the H control problem for a class of linear discrete-time systems with Markovian jumping parameters in terms of a set of solutions of coupled algebraic Riccati inequalities.
Abstract: In this paper, we investigate the H control problem for a class of linear discrete-time systems with Markovian jumping parameters. The jumping parameters considered here is modelled by adiscrete-time Markov process. Ourattentionisfocused onthedesign of linear state feedback controller such that both stochastic stability and a prescribed H performance are required to be achieved when the real system under consideration has different types of uncertainty. Sufficient conditions are proposed to solve the above problem, which are in terms of a set of solutions of coupled algebraic Riccati inequalities. An example is given to show the potential of the proposed techniques.
56 citations
TL;DR: It is concluded that returns to scale constitutes only one component of economies of scale, and DEA is advantageous over the translog method in providing information relating to returns to Scale possibilities of each of the individual production units.
Abstract: This paper critically analyses, in the context of classical and neoclassical perspectives, the concepts of 'returns to scale' and 'economies of scale' by relating the former to the concept of 'production unit' and the latter to the concept of 'firm', and concludes that returns to scale constitutes only one component of economies of scale. The estimation models of frontier translog production function and DEA are applied to data on the Indian steel industry for a period of eight years in order to compare inferences about the production correspondence of the steel industry. Our results indicate that DEA is advantageous over the translog method in providing information relating to returns to scale possibilities of each of the individual production units. W ith regard to the efficiency evaluation, both the models are found to give statistically significant 'technical' and 'technical and scale' efficiency ratings.
51 citations
TL;DR: A unifying framework of steady-state Kalman filtering, smoothing and prediction for descriptor systems is presented by using the innovation analysis method in the time domain and formulae for selecting their initial values are given.
Abstract: A unifying framework of steady-state Kalman filtering, smoothing and prediction for descriptor systems is presented by using the innovation analysis method in the time domain. The descriptor Kalman estimators are presented on the basis of the autoregressive moving-average innovation model and white-noise estimators. The new algorithms of steady-state descriptor Kalman estimators gains are given. The solution of the Riccati equation is avoided. To ensure the asymptotic stability of descriptor Kalman estimators with respect to the initial values of innovation process, formulae for selecting their initial values are given. A simulation example shows the usefulness of the proposed results.
50 citations
TL;DR: It is shown that the RBF-AR model can not only reconstruct the dynamics of given nonlinear time series effectively, but also give much better fitting to complextime series than the approach of directly RBF neural network modelling.
Abstract: This paper investigates nonlinear time series modelling using the general state-dependent autoregressive model. To achieve the estimate of the model, an attempt is made to approximate the state-dependent parameter by employing the Gaussian radial basis function for its universal approximation capability. As a result, a radial basis function-based autoregressive (RBF-AR) model is derived which has a form similar to a generalized exponential autoregressive model. To reach the applicability of the RBF-AR model, the evolutionary programming algorithm is employed to select a suitable set of radial basis function centres. By applying the resulting model to some complex data, it is shown that the RBF-AR model can not only reconstruct the dynamics of given nonlinear time series effectively, but also give much better fitting to complextime series than the approach of directly RBF neural network modelling. Therefore, as a paradigm combining a statistical model and neural network, the RBF-AR model has better perform...
50 citations
TL;DR: This paper describes the design and implementation of a fault-tolerant system for Omni-Directional Intelligent Navigator (ODIN), a six-degree-of-freedom autonomous underwater vehicle (AUV) designed at the University of Hawaii.
Abstract: This paper describes the design and implementation of a fault-tolerant system for Omni-Directional Intelligent Navigator (ODIN), a six-degree-of-freedom autonomous underwater vehicle (AUV) designed at the University of Hawaii. A fault-tolerant system consists of three areas: fault detection, fault isolation and fault accommodation. Each area is described, and methods discussed in the literaturearebriefly reviewed. The presented design focuses on the thruster (or actuator) and sensor system failures in an AUV. Experimental results show that the presented approach is practical and effective when tolerable failures in actuators and sensors occur. This methodology and concept can be extended to fault-tolerant system design for various AUVs with hardware redundancy.
48 citations
TL;DR: An order-level inventory model for deteriorating items is developed under the conditions of exponential decay, instantaneous replenishment and linear time-dependent demand rate with a positive trend and a number of structural properties of the inventory system is proved analytically.
Abstract: An order-level inventory model for deteriorating items is developed under the conditions of exponential decay, instantaneous replenishment and linear time-dependent demand rate with a positive trend. A number of structural properties of the inventory system is proved analytically. The exact formulae for the optimal average cost and the lot size are derived without carrying out any approximation over the constant deterioration rate. A numerical example is taken to illustrate the procedure of finding the optimal lot size, the average cost and the cycle period. A sensitivity analysis is carried out to demonstrate the effects of changing parameter values on the optimal solution of the system.
47 citations
TL;DR: This work is concerned with the control design of a certain class of manufacturing systems modelled by continuous time Petri nets, and the convergence of the output buffer to a desired level is proved.
Abstract: This work is concerned with the control design of a certain class of manufacturing systems modelled by continuous time Petri nets. The considered systems are large series assembly workshops for which the final machine is a mono-input mono-output one. The average production frequencies of the machines are controlled according to the buffers' content. Three different feedback control designs are investigated: a bang-bang one, a proportional one, and a combined one. The convergence of the output buffer to a desired level is proved, and the analytic expression of the marking is detailed in the case of a single machine station. The results are then applied for the control design of open manufacturing lines.
44 citations
TL;DR: Applying robust design allows one to solve practical problems in nonlinear robust control and optimization by using nonlinear models with parameter variations and input bounds by overcoming the gap between the theory and its application.
Abstract: New results and innovative procedures are presented to design nonlinear robust controllers for a class of nonlinear time-varying systems with uncertain parameters and control constraints. The straightforward techniques for designing the robust bounded controllers are developed by utilizing the theoretical foundations of the HamiltonJacobi theory and L yapunov's method. The major contribution is the development of feasible and computationally efficient algorithms to stabilize uncertain nonlinear systems. Various aspects of recent developments concerning robust control and nonlinear optimization are discussed and further researched. Necessary and sufficient conditions for optimality and robust stability are studied. By applying robust design, this paper allows one to solve practical problems in nonlinear robust control and optimization by using nonlinear models with parameter variations and input bounds. To overcome the gap between the theory and its application, two examples are thoroughly studied. Robust ...
TL;DR: The paper develops the state equation model of an electroplating line in the max algebra that includes a control vector designed to ensure the control of movements of the transporting system, to respect constraints and to optimize the production.
Abstract: The paper develops the state equation model of an electroplating line in the max algebra. The state equation includes a control vector designed to ensure the control of movements of the transporting system, to respect constraints and to optimize the production. An industrial application and some results are given for the dynamic modelling of minimum-maximum P-time event graphs in dioids, namely in the max and min algebras.
TL;DR: It is proved that the proposed genetic algorithm possesses the capability of finding the stochastic gradient and adapting the control parameters in the direction of descent.
Abstract: This paper proposes a stochastic approach for optimization of control parameters ( probabilities of crossover and mutation ) in genetic algorithms ( GAs ) . The genetic search can be modelled as a controlled Markovian process, the transition of which depends on the control parameters. A stochastic optimization problem is formed for control of GA parameters, based on a given performance index of populations and analysed as a controlled Markovian process during the genetic search. The optimal values of control parameters can be found from a recursive estimation of control parameters, which is obtained by introducing a stochastic gradient of the performance index and using a stochastic approximation algorithm. The algorithm possesses the capability of finding the stochastic gradient and adapting the control parameters in the direction of descent. A non-stationary Markov model is developed to investigate asymptotic convergence properties of the proposed genetic algorithm. It is proved that the proposed geneti...
TL;DR: Using the weighted integration of the measurable output probability density functions, two adaptive on-line updating rules are developed which guarantee the global stability for theclosed loop adaptive control system under certain conditions.
Abstract: This paper presents a model reference based adaptive control approach for the control of the output probability density function for unknown linear time-invariant stochastic systems. Different from most existing models used in stochastic control, it is assumed here that the measured control input directly affects the distribution of the system output in probability sense. As such, the purpose of control is to make the shape of the probability density function of the system output as close as possible to a prespecified one. Using the weighted integration of the measurable output probability density functions, two adaptive on-line updating rules are developed which guarantee the global stability for theclosed loop adaptive control system under certain conditions. Ithas been shown, when there is no external disturbance, that the so-formed closed loop system also realizes the perfect tracking (i.e., the probability density function of the system output approaches a class of given distributions asymptotically)...
TL;DR: A new methodology the grey compromise programming ( GCP ) method is presented in which the parameter uncertainties in the optimization process are specifically considered as interval numbers and the related stability theory is proved as well.
Abstract: Multiple conflicting objectives characterize the current water resources management systems. In particular, the conflict between environmental protection of reservoir water quality and economic development by different uses of land within the reservoir watershed is a problem that receives wide attention in many developing countries. The optimal balance between carrying capacity of watershed land-use and assimilative capacity of reservoir water quality remains unclear. However, the inherent uncertainties of both environmental and economic goals and parameter values may result in additional difficulties in public decision making. This paper presents a new methodology the grey compromise programming ( GCP ) method in which the parameter uncertainties in the optimization process are specifically considered as interval numbers and the related stability theory is proved as well. The case study is drawn from the optimal planning of land-use programme in the Tweng-Wen reservoir watershed in Taiwan.
TL;DR: This paper focuses on the analysis and synthesis problem of robust H control for a class of linear time-varying uncertain systems with delayed state and control when the full states cannot be measured.
Abstract: This paper focuses on the analysis and synthesis problem of robust H control for a class of linear time-varying uncertain systems with delayed state and control when the full states cannot be measured. A dynamic output feedback controller is given to quadratically stabilize the linear time-delay system with norm-bounded uncertainty and reduce the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. Sufficient conditions for the existence of a robust H dynamic output feedback control law are derived and two synthesis methods are presented for a robust H dynamic output feedback control law to uncertain time-delay systems. One method is to construct robust H dynamic output feedback control laws by two equivalent linear time-invariant structural descriptions for the sufficient conditions, and the control law can be obtained by solving two Algebraic Riccati Equations (AREs). The other method is to transform the sufficient conditions into two Linear Ma...
TL;DR: In this paper neurofuzzy modelling techniques are presented and their application to the identification of an Autonomous Underwater Vehicle (AUV) is demonstrated.
Abstract: Neurofuzzy modelling is ideally suited to many nonlinear system identification and data modelling applications. By combining the attractive attributes of fuzzy systems and neural networks transparent models of ill-defined systems can be identified. Available expert a priori knowledge is used to construct an initial model. Data modelling techniques from the neural network, statistical and conventional system identification communities are then used to adapt these models. As a result accurate parsimonious models which are transparent and easy to validate are identified. Recent advances in the datadriven identification algorithms have now made neurofuzzy modelling appropriate for high-dimensional problems for which the expert knowledge and data may be of a poor quality. In this paper neurofuzzy modelling techniques are presented. This powerful approach to system identification is demonstrated by its application to the identification of an Autonomous Underwater Vehicle (AUV).
TL;DR: A new recursive algorithm is proposed to solve the generalized algebraic Riccati equations and enough conditions are found to find sufficient conditions for the convergence of the proposed algorithm.
Abstract: In this paper, we study the H control problem for singularly perturbed systems under both perfect- and imperfect-state measurements by using the recursive approach of Gacjic et al. We construct a controller that guarantees a disturbance attenuation level larger than a boundary value of the reduced-order slow and fast subsystems when the singular perturbation parameter epsilon1 approaches zero. In order to obtain the controller, we must solve the generalized algebraic Riccati equations. The main results in this paper are to propose a new recursive algorithm to solve the generalized algebraic Riccati equations and to find sufficient conditions for the convergence of the proposed algorithm. Using the recursive algorithm, we show that the solution of the generalized algebraic Riccati equation converges to a positive semidefinite stabilizing solution with the rate of convergence of O(epsilon1k) under sufficient conditions. Furthermore, in the case of perfect-state measurements, we also show that the controller...
TL;DR: The proposed model-based approach of selfdiagnosis for AUVs in order to supervise whether the vehicle operates itself in an appropriate way is carried out based on a dynamics model of an AUV and an active mechanism to obtain desirable information.
Abstract: In the underwater environment, installation of a proper scheme to cope with unexpected situations is essential for Autonomous Underwater Vehicles (AUVs) to carry out their mission out of human reach. This paper proposes a model-based approach of selfdiagnosis for AUVs in order to supervise whether the vehicle operates itself in an appropriate way. The proposed self-diagnosis is carried out based on a dynamics model of an AUV and an active mechanism to obtain desirable information. The dynamics model is constructed by an artificial neural network taking advantage of its flexible learning capability. When a sensor is found to be defective, dead reckoning usingits corresponding outputof thedynamics modelcan beintroduced in anattemptto cope with the defect. The performance of the proposed system was examined by implementing it on the 'Twin-Burger', a test-bed AUV. It is shown that the system without the introduction of extra sensors detects failures of onboard sensors and actuators, and then selects a proper ...
TL;DR: A three-layer controller architecture is proposed to enhance the autonomy of the vehicle using Hinfintiy/H2 control design technique to drive the actuators directly and to reconfigure the system under fault conditions.
Abstract: This paper is concerned with the development of an integrated control design approach for regulation, trajectory tracking, diagnosis and control reconfiguration of autonomous underwater vehicles (AUVs). A three-layer controller architecture is proposed to enhance the autonomy of the vehicle. Atthe bottom layer,thelocalfeedback controllers are designed using Hinfintiy/H2 control design technique to drive the actuators directly. A four-degree-of-freedom controller is used to incorporate the sensor and actuator faults and to account for the interaction between the regulation and the diagnostic module. A predictive control design technique is employed at the middle layer (guidance) to manoeuvre optimally the AUV along a desired trajectory. A robust filtering scheme is proposed at the top level to provide the necessary information to the guidance system and to reconfigure the system under fault conditions. The condition for global stability is derived and simulation results are presented to demonstrate the per...
TL;DR: This study suggests a new approach to provide time-varying parameter estimates in ARMA (Auto Regression Moving Average) models of stochastic nature based on the use of the recursive version of Instrumental Variable Method (IVM) with a Matrix Forgetting Factor (MFF).
Abstract: This study suggests a new approach to provide time-varying parameter estimates in ARMA (Auto Regression Moving Average) models of stochastic nature based on the use of the recursive version of Instrumental Variable Method (IVM) with a Matrix Forgetting Factor (MFF). This combination is a tool for estimating the entries of a nonstationary parameter matrix involved in the ARMA model. An asymptotic analysis of the error matrix is presented. Simulation results demonstrate the effectiveness of the suggested approach.
TL;DR: The generalized equations are developed in the absolute coordinate system using Lagrange's technique, then a simple linear transformation is proposed to obtain the set of nonlinear equations in the DevanitHartenberg coordinate system.
Abstract: In this paper, the equations of motion for a general multi-link inverted pendulum system are derived. Assumptions previously employed to simplify such formulation are removed. The pendulum system is more general and includes nonlinear friction terms to suit various engineering applications. The generalized equations are first developed in the absolute coordinate system using Lagrange's technique, then a simple linear transformation is proposed to obtain the set of nonlinear equations in the DevanitHartenberg coordinate system. The equations of motion for double and triple link inverted pendulum systems are given as examples for such dynamics equations.
TL;DR: Under the proposed decentralized control law, it has been shown theoretically and by simulation that manipulator systems are practically stable.
Abstract: A design method for the decentralized control of manipulators is proposed. The dynamics of manipulators are firstly represented as a set of interconnected subsystems. The dynamics of the subsystems are divided into two parts: a nominal system and uncertainties. Based on the nominal system and the bounds on the uncertainties, the Riccati equation approach is used for the control design for the manipulators. Under the proposed decentralized control law, it has been shown theoretically and by simulation that manipulator systems are practically stable.
TL;DR: New robust stability criteria and a sufficient condition for the existence of memoryless robust stabilizing control law are derived and the results depend on the size of the delay and are given in terms of several linear matrix inequalities (LMIs).
Abstract: The delay-dependent robust stabilization problem for a class of uncertain linear timedelay systems containing saturating actuator is considered in this paper. The uncertain time-delay systems under consideration are described by state differential equations with time-varying unknown-but-bounded uncertain parameters and delayed state. The delay is assumed to be constant bounded but unknown. New robust stability criteria and a sufficient condition for the existence of memoryless robust stabilizing control law are derived. The results depend on the size of the delay and are given in terms of several linear matrix inequalities (LMIs). A numerical example is presented to illustrate the obtained results.
TL;DR: A nonlinear controller is designed for a 6 DOF model of an unmanned underwater vehicle (UUV) which includes both the kinematics and the dynamics, and the proposed control law achieves excellent tracking for slowly changing trajectories.
Abstract: In this paper a nonlinear controller is designed for a 6 DOF model of an unmanned underwater vehicle (UUV) which includes both the kinematics and the dynamics. It is shown how the use of a Lyapunov function,consisting of aquadraticterm in the velocity (both linear and angular), a quadratic term in the position and a logarithmic term in the attitude leads to a design of a control law that achieves global asymptotic stabilization to an arbitrary set point in position/attitude. The control law is made linearly bounded by avoiding cancellation of some of the quadratic nonlinearities in the model. No information about the inertia matrix, thedamping,and the Coriolis/centripetal parameters is used in the controller, endowing it with a certain amount of parametric robustness. The control law is given in terms of the Modified Rodrigues parameters. An extensive simulation study shows that the proposed control law achieves excellent tracking for slowly changing trajectories, even though it is designed only for set p...
TL;DR: The observer design for nonlinear multiple-output systems is shown to be considerably simplified in a decentral approach and the method is illustrated by the ball-and-beam example.
Abstract: The observer design for nonlinear multiple-output systems is shown to be considerably simplified in a decentral approach. The method requires a block-triangular system representation which either can be detected in the system differential equations or may be obtained by a state transformation. The transformation is investigated in detail, and necessary and sufficient conditions for its existence are discussed. Moreover, the method is illustrated by the ball-and-beam example.
TL;DR: It is demonstrated that there exists the best selection of MFF minimizing the error strip bound, and an adaptation procedure is suggested to obtain asymptotically this optimal value using only the available measurements.
Abstract: We suggest an approach to provide time-varying parameter estimates in ARMA (Auto Regression Moving Average) models of a stochastic nature based on the use of the recursive version of the Instrumental Variable Method (IVM) with a Matrix Forgetting Factor (MFF). We demonstrate that there exists the best selection of MFF minimizing the error strip bound. This optimal MFF depends in a complex manner on a group of unknown parameters. An adaptation procedure is suggested to obtain asymptotically this optimal value using only the available measurements. The adaptation procedure is based on one Gaussian smoothing technique. The combination of IVM with adaptive MFF is a tool for estimating the entries of a non-stationary parameter matrix involved in the ARMA model. An asymptotic analysis of the error matrix is presented. Simulation results demonstrate the effectiveness of the suggested approach.
TL;DR: It is shown that the non-exponential iterative decay estimates are less conservative than the exponential and generalized exponential decay estimates and involve only algebraic computation; therefore, they are simple and very easy to use.
Abstract: This paper presents some necessary and sufficient stability conditions and some sufficient stability conditions for general classes of retarded dynamic systems. The stability conditions are established by using the Lyapunov function method. However, attention is paid in this paper to establishing as less conservative exponential, generalized exponential and non-exponential decay estimates for the retarded dynamic systems as possible. As applications of the established stability conditions, a class of retarded dynamic systems which have a linear retard-free term are studied in detail and some exponential, generalized exponential and non-exponential iterative decay estimates for the systems are obtained. It is shown that the non-exponential iterative decay estimates are less conservative than the exponential and generalized exponential decay estimates. In addition, the obtained iterative decay estimates involve only algebraic computation; therefore, they are simple and very easy to use. Two examples are giv...
TL;DR: New definitions of stability are presented, and general sufficient stability conditions and instability conditions are derived, and when applied to the analysis of stability and instability of second-order linear constant coefficients singular systems with delay, the location of a possible bifurcation is discovered.
Abstract: In this paper, the general class of singular systems with delay and second order linear constant coefficients singular systems with delay, is considered First, for singular systems with delay, new definitions of stability are presented, and general sufficient stability conditions and instability conditions are derived Secondly, these results are applied to the analysis of stability and instability of second-order linear constant coefficients singular systems with delay, the location of a possible bifurcation is discovered
TL;DR: Results of simulations show that using the developed policy, any desired inventory levels can be maintained while minimizing costs and satisfying demand without violating capacity constraints.
Abstract: A multi-item model of a production-inventory system incorporating deterioration, shortages and capacity/budget constraints is considered. An optimal control policy for the model is developed using linear quadratic (LQ) theory for the case of deterministic demands. The problem of controlling large-scale production-inventory facilities is also considered, and the interaction prediction method is used to develop optimal policies. Results of simulations show that using the developed policy, any desired inventory levels can be maintained while minimizing costs and satisfying demand without violating capacity constraints.