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Considers control systems operating under potentially faulty conditions. Discusses the problem of designing a single unit which not only handles the required control action but also identifies faults occurring in actuators and sensors. In common practice, units for control and for diagnosis are designed separately. Attempts to identify situations in which this is a reasonable approach and cases in which the design of each unit should take the other into consideration. Presents a complete characterization for each case and gives systematic design procedures for both the integrated and non‐integrated design of control and diagnosis units. Shows how a combined module for control and diagnosis can be designed which is able to follow references and reject disturbances robustly, control the system so that undetected faults do not have disastrous effects, reduce the number of false alarms and identify which faults have occurred.

An assessment technique that analyzes the servo and regulatory characteristics of the proportional integral derivative controller is designed for time-delayed second-order stable processes.

The minimum theoretical error expression for integral of the absolute errors (IAE_o) is obtained from the preferred servo and regulatory transfer functions dependent on the step changes in reference and load variables.

The error-based index is outlined to estimate the controller that is derived using internal model-based control or direct synthesis method. The ratio between derived IAE_o and the IAE_actual gained from the loop response that experiences step input variations gives rise to a dimensionless error index. This error index measures the behaviour of the controller by considering the index value. If the error index value is larger than 0.8, then the effort taken by the controller is good or else retuning is expected.

The efficacy of the index to validate the controller is verified by applying on a few second-order electrical processes. The results are simulated for both reference tracking and load rejection tasks to demonstrate the rationality of the presented index.

The purpose of this paper is to consider the process of design and implementation of an enhanced fuzzy H_∞ (EFH_∞) estimation algorithm to determine the attitude and heading angles of ground vehicles, which are frequently affected by considerable exogenous disturbances. To detect the changes of disturbances, a fuzzy system is designed based on expert knowledge and experiences of a navigation engineer. In the EFH_∞ estimator, the intensity bounds of disturbances affecting the measurements are updated using a heuristic combination of three change‐detection indices. Performance of the proposed estimator is evaluated by Monte‐Carlo simulations and field tests of three kinds of vehicles using a manufactured attitude‐heading reference system (AHRS). In both simulations and real tests, the proposed estimator results in a superior performance compared to those of the recently developed and standard H_∞ estimators.

Design, implementation and real tests of the EFH_∞ estimator are considered for an AHRS specialized for vehicular applications. In the AHRS, three‐axis accelerometers (TAA) and three‐axis magnetometers (TAM) may be affected by large disturbances due to non‐gravitational accelerations and local magnetic fields. Therefore, the design parameters of EFH_∞ estimator including the theoretic bound of disturbance intensity and the attenuation level are adaptively tuned using a fuzzy combination of three change‐detection indices. Once a sensor is affected by an exogenous disturbance, the fuzzy system will increase the scale factor of the corresponding measurement disturbance to place more confidence on the data of the AHRS dynamics including measurements of gyros with respect to the data coming from the TAA and TAM.

An intelligent fault detector is proposed for considering changes of disturbances to adjust the upper bounds of the estimator's disturbances and the length of data to update the fuzzy system inputs. The EFH_∞ estimator is suitable to attenuate the effects of disturbances changes on accurate estimation of the attitude and heading angles, intelligently.

The paper provides a fuzzy state estimator for adaptively adjusting the theoretic disturbance matrices according to the actual intensity of the disturbances affecting the AHRS dynamics and the measurement sensors.

The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control.

Development of a MATLAB-based MODE suitable for controller synthesis. Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H _∞ -LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance.

The proposed optimized H-infinity control was able to yield set of Pareto-controller candidates with optimal compromise between conflicting stability and time-domain performances required in autonomous helicopter deployment. The result of performance evaluation shows robustness to parameter variation of up to 20 per cent variation in nominal values, and in addition provides satisfactory disturbance rejection to wind disturbance in all the three axes.

The formulated H-infinity controller is limited to hovering and low speed flight envelope. The optimization is focused on weighting function parameters for a given fixed weighting function structure. This thus requires a priori selection of weighting structures.

The proposed MODE-infinity controller algorithm is expected to ease the design and deployment of the robust controller in autonomous helicopter application especially for practicing engineer with little experience in advance control parameters tuning. Also, it is expected to reduce the design cycle involved in autonomous helicopter development. In addition, the synthesized robust controller will provide effective hovering/low speed autonomous helicopter flight control required in many civilian unmanned aerial vehicle (UAV) applications.

The research will facilitate the deployment of low-cost, small-scale autonomous helicopter in various civilian applications.

The research addresses the challenges involved in selection of weighting function parameters for H-infinity control synthesis to satisfy conflicting stability and time-domain objectives. The problem of population initialization and objectives function computation in the conventional MODE algorithm are addressed to ensure suitability of the optimization algorithm in the formulated H-infinity controller synthesis.

The purpose of this paper is to present a neural network approach to control performance assessment.

The performance index under study is based on the minimum variance control benchmark, a radial basis function network (RBFN) is used as the pre‐whitening filter to estimate the white noise sequence, and a stable filtering and correlation analysis method is adopted to calculate the performance index by estimating innovations sequence using the RBFN pre‐whitening filter. The new approach is compared with the auto‐regressive moving average model and the Laguerre model methods, for both linear and nonlinear cases.

Simulation results show that the RBFN approach works satisfactorily for both linear and nonlinear examples. In particular, the proposed scheme shows merits in assessing controller performance for nonlinear systems and surpasses the Laguerre model method in parameter selection.

A RBFN approach is proposed for control performance assessment. This new approach, in comparison with some well‐known methods, provides satisfactory performance and potentials for both linear and nonlinear cases.

Aiming at the positioning accuracy control problem in the running of the assembly machine for assembled camshaft, a kind of position controller based on the feedforward‐feedback control of speed and acceleration is designed.

It combines feedforward‐feedback control with the quartic displacement curve acceleration/deceleration algorithm.

The axial dimension and the phase angle of the cam obtained after being assembled is checked. The result shows that for each type of camshaft, the error of the axial dimension of the cam is less than ±0.2mm and the error of the phase angle of the cam is less than ±30′. In addition, production efficiency is greatly improved (the assembling time is 90‐120S/piece).

The paper combines feedforward‐feedback control with the quartic displacement curve acceleration/deceleration algorithm for the first time.

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.

Taxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.

The techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.

The review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.

The review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

This study aims to establish a robust evaluation framework for suppliers within the automotive supply chain, specifically in the stamping sector. The primary objectives are to elucidate the performance criteria of suppliers, identify indicators and scales for measuring these criteria and find the importance of the criteria.

The evaluation framework comprises a criteria hierarchy and indicators developed based on the evaluation criteria of major automotive manufacturers. Specific indicators and measurement scales are recommended for assessing suppliers. Importance weights for the criteria are assigned based on the input of nine experts using the Analytic Hierarchy Process (AHP). Finally, four sheet metal stamping tooling (SMST) suppliers are evaluated by four specialists using the proposed evaluation framework.

The study introduces a novel classification of criteria, encompassing financial and commercial perspectives, delivery capability, supplier facility and cultural approaches and business process necessities. The findings underscore the significance of financial and commercial stability in the selection of SMST suppliers, emphasizing their role in mitigating risks associated with disruptions, bankruptcies and unforeseen events. Additionally, several SMST evaluation factors identified in this study contribute to the development of resilience capabilities, highlighting the crucial importance of their inclusion and assessment in the proposed evaluation framework.

This research presents a comprehensive model for evaluating SMST suppliers, which tackles the multidisciplinary challenges within the automotive supply chain. Given the inadequacy or nonexistence of current SMTS selection models, this study bridges the gap by exploring potential and necessary criteria, alongside 116 specific indicators and measurement scales.

This study aims to investigate the feasibility of saturated AC heating of magnetic metals. In AC heating of magnetic steel below the Curie temperature, because of the high magnetic permeability, the penetration depth is in the order of 1-6 mm at 50 Hz. Surface heating is then obtained, in practice, if large slabs are processed. The necessity to provide the required surface-to-core temperature uniformity (about 25°C) at the end of the heating process, avoiding excessive thermal stresses which can lead to cracks, thus implies a long heating time.

The penetration depth can be increased if the material is brought to saturation by applying an external DC magnetic field, and a faster in-depth heating can be obtained. The DC saturating field can be produced with no losses over large volumes by means of superconducting (SC) coils.

The feasibility of in-depth induction heating of a 200 × 1,000 × 5,000 mm magnetic steel slab with an applied 2 T DC saturating field is numerically investigated. The results show that the use of a DC saturating field leads to shorter processes which fulfil the heating objectives.

A DC saturating field cannot be produced by means of copper coils because of the large amount of material and the unaffordable power required. However, this field can effectively be produced by means of SC magnets based on state-of-the-art materials.

Superconductivity may be the enabling technology for fast and efficient induction heating of magnetic steel slabs if the increase in productivity can balance the additional costs due to the SC magnet.

Proposes an optimal identification algorithm of time‐varying dynamic processes. Says it is based on applying a linear combination of the recursive least‐squares method equations. Posits that this scheme could be applied to identify and predict the ARMAX model of the on‐line desalting processes. Desalination technology is used to produce fresh water from saline sources. States that the results obtained give useful information on the physical considerations and desalting process efficiency.