Archive | ISA Transactions


Hybrid Intelligent Method for Recognition of Common Types of Control Chart Patterns

Abstract: Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the […]

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Stabilization of Linear Time Invariant Fractional Order Switched Systems

Abstract: This paper presents the stabilization problem of a linear time invariant fractional order (LTI-FO) switched system with order 1<q<21<q<2 by a single Lyapunov function whose derivative is negative and bounded by a quadratic function within the activation regions of each subsystem. The switching law is extracted based on the variable structure control with a sliding […]

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An Efficient Decentralized Iterative Learning Tracker

Abstract: In this paper, an efficient decentralized iterative learning tracker is proposed to improve the dynamic performance of the unknown controllable and observable sampled-data interconnected large-scale state-delay system, which consists of NN multi-input multi-output (MIMO) subsystems, with the closed-loop decoupling property. The off-line observer/Kalman filter identification (OKID) method is used to obtain the decentralized linear models […]

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Bilateral Control of Master-Slave Manipulators with Constant Time Delay

  Abstract: This paper presents a novel teleoperation controller for a nonlinear master-slave robotic system with constant time delay in communication channel. The proposed controller enables the teleoperation system to compensate human and environmental disturbances, while achieving master and slave position coordination in both free motion and contact situation. The current work basically extends the passivity […]

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Modified Smith Predictor-Based Cascade Control of Unstable Time Delay Processes

  Abstract: An improved cascade control structure with a modified Smith predictor is proposed for controlling open-loop unstable time delay processes. The proposed structure has three controllers of which one is meant for servo response and the other two are for regulatory responses. An analytical design method is derived for the two disturbance rejection controllers by […]

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Simulation and Stability Analysis of Neural Network Based Control Scheme for Switched Linear Systems

Abstract: This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The […]

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DC Servomechanism Parameter Identification: Closed-Loop Approach

  Abstract: This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control […]

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Robust SDRE Filter Design for Nonlinear Uncertain Systems

Abstract: In order to remedy the effects of modeling uncertainty, measurement noise and input disturbance on the performance of the standard state-dependent Riccati equation (SDRE) filter, a new robust H∞ SDRE filter design is developed in this paper. Based on the infinity-norm minimization criterion, the proposed filter effectively estimates the states of nonlinear uncertain system exposed […]

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Self-Tuning Control Strategies Within Two Adaptive Perspectives

Abstract: This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure – or simply GMV2DOF – within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani […]

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