Stability and robustness of fuzzy adaptive control of nonlinear systems

In this paper, we propose a new approach that guarantees the stability and robustness of an adaptive control law of a nonlinear system.The control diagram proposed contains a Takagi–Sugeno–Kang fuzzy controller (TSK-FC) and a training block allowing the online adaptation of the FC parameters. The adaptation algorithm used is based on the gradient with minimization of the quadratic error between the system output and that desired by using the direct method of Lyapunov. However, our approach considers the gradient step of each adaptive FC parameter to be bound. This approach was applied to the control of an inverted pendulum. The results obtained confirm well the validity of such an adaptation especially the guarantee of the pendulum stability and the robustness of its control with respect to the disturbances introduced on the FC parameters and the pendulum itself.     

Comparative analysis of RF LDMOS capacitance reliability under accelerated ageing tests

This paper presents the results of comparative reliability study of C–V characteristics through three accelerated ageing tests for stress applied to an RF LDMOS: Thermal shock tests (TST, air–air test), thermal cycling tests (TCT, air–air test) and high temperature storage life (HTSL). The two first tests are carried out with a drain current flowing through the device during stress. The investigation findings of electrical parameter degradations after various ageing tests are discussed. Feedback capacitance (Crs) is reduced by 16% and gate–drain capacitance (Cgd) by 42%. This means that the tracking of these parameters enables to consider the hot carrier injection as the dominant degradation phenomenon. A physical simulation software has been used to confirm qualitatively degradation phenomena.     

INTELLIGENT CONTROL SYSTEM FOR STREAM SAMPLING

This article introduces an intelligent sampling controller to assist the actions taken by a plant operator to correct sampling conditions. This hybrid system includes a sampling error filter (SEF), a sampling performance indexer (SPI), a sampling correctness inspector (SCI), and a sampling error evaluator (SEE). First, the SEF upgrades the measured variables in a mineral-processing system by material balance. Then, the SPI employs fuzzy logic to assess the sampling performance. In addition, the expert system SCI checks the correctness of the sampling process. Finally, the sampling error is computed by the expert system SEE.     

Investigation of Be diffusion in InGaAs using Kick-out mechanism

Be diffusion during post-growth annealing has been investigated in InGaAs epitaxial layers. Kick-out mechanisms considering species charges, build-in electric field and Fermi-level effect have been studied. Several forms of Kick-out mechanism have been implemented in our simulation programs. Experimental concentration profiles obtained by SIMS have been compared systematically with the results of simulations. We have deduced that the Kick-out mechanism Be_i⁰ Be⁻ + I_III⁺ is the dominating diffusion mechanism in InGaAs under our experimental conditions (C₀ = 3 × 10¹⁹ cm⁻³).     

KNOWLEDGE-BASED ASSESSMENT OF STREAM SAMPLING

This article presents two novel knowledge-based systems for stream-sampling assessment. The first expert system inspects the stream-sampling correctness in mineral-processing plants. It is called the sampling correctness inspector. The second expert system evaluates sampling errors in mineral-processing plants. It is called the sampling error evaluator. The knowledge of both expert systems is collected from the authors' expertise, in addition to other experts' knowledge of sampling mineral-processing streams. These knowledge-based systems take into account the stream properties, the cutter features, and the sampling manner. They were developed and tested successfully.     

FUZZY EVALUATION OF STREAM SAMPLE RELIABILITY

The operation of a mineral-processing plant is investigated regularly by stream sampling. Sampling errors are generated due to material heterogeneity and cutter features. This article presents an innovative method using fuzzy logic to assess the sample reliability, which is assumed to be influenced by the cutter geometry, speed, layout, and path. Fuzzy logic permits sampling situations to be described and processed in linguistic terms such as very reliable, reliable, adequate, doubtful, and very doubtful. Each sample is assigned a sampling performance index. This is the basis for decision-making concerning sampling strategy and the weighting factors in data-reconciliation techniques.     

A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management

Combined simulation–optimization (CSO) schemes are common in the literature to solve different groundwater management problems, and CSO is particularly well-established in the coastal aquifer management literature. However, with a few exceptions, nearly all previous studies have employed the CSO approach to derive static groundwater management plans that remain unchanged during the entire management period, consequently overlooking the possible positive impacts of dynamic strategies. Dynamic strategies involve division of the planning time interval into several subintervals or periods, and adoption of revised decisions during each period based on the most recent knowledge of the groundwater system and its associated uncertainties. Problem structuring and computational challenges seem to be the main factors preventing the widespread implementation of dynamic strategies in groundwater applications. The objective of this study is to address these challenges by introducing a novel probabilistic Multiperiod CSO approach for dynamic groundwater management. This includes reformulation of the groundwater management problem so that it can be adapted to the multiperiod CSO approach, and subsequent employment of polynomial chaos expansion-based stochastic dynamic programming to obtain optimal dynamic strategies. The proposed approach is employed to provide sustainable solutions for a coastal aquifer storage and recovery facility in Oman, considering the effect of natural recharge uncertainty. It is revealed that the proposed dynamic approach results in an improved performance by taking advantage of system variations, allowing for increased groundwater abstraction, injection and hence monetary benefit compared to the commonly used static optimization approach.

     

MATERIAL BALANCE AND STREAM SAMPLING ERRORS

This article investigates the influence of the data variation on sampling errors throughout a two-stage flotation circuit. The material balance technique is used to upgrade the measured variables. The sampling errors are evaluated before and after material balance. In one case, the covariance terms between the components in a stream and between the streams in the flotation circuit are included. In the other case, these terms are not included. This article proves that by including the covariance terms in the calculation, the variances of the sampling errors are reduced and, therefore, the reliability of the material balance is improved.