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Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.

The purpose of this paper is to study the 2D hybrid linear model, which is a method of describing both continuous‐ and discrete‐time dynamics in one system. Singularity of 2D hybrid linear models is a newly occurred problem and a very important question is how to compute the solution of the singular 2D hybrid linear model.

Computation of the solution of mentioned system is based on Laplace transform, Z‐transform and shifting algorithm. The inverse Laplace transform and inverse Z‐transform are used in two cases.

In this paper, a class of 2D singular hybrid linear systems is introduced. Two methods for computation of solutions of the singular hybrid system with nonzero boundary conditions are proposed. Both methods are illustrated by the examples.

Presented methods are a new way for computing the solution of singular 2D hybrid linear systems.

Healthcare organisations exhibit detail and dynamic complexity. It has been argued that discrete event simulation (DES) is ideal for problems exhibiting detail complexity and system dynamics (SD) lends itself naturally to comprehend dynamic complexity. Appreciating the complexity of healthcare, this paper proposes the use of hybrid simulation wherein both SD and DES are integrated symbiotically. The paper further aims to describe how different forms of hybrid simulation can be applied to different modes of governance in UK healthcare.

In order to find different ways that hybrid simulation can be effectively applied to different problem contexts, a literature review has been conducted to find existing hybrid studies. A meta‐review of literature on different modes of governance in UK healthcare has also been conducted.

It has been induced from the literature review that hybrid simulation can be used in three different formats: hierarchical format, process‐environment format, and integrated format. Literature on different modes of governance in UK healthcare further points out that there are three modes of governance in UK healthcare: top‐down performance hierarchical mode, network partnership mode, and quasi‐market mode.

It is believed that hybrid simulation will aid in forming a synergy between strategic and operational management. One of the limitations of this paper is that it does not provide any guidance with respect to technical automation of integration between SD and DES.

This paper proposes the use of hybrid simulation for complex healthcare problems and the way it can contribute towards effective decision making within different modes of governance.

The purpose of this paper is to develop a generic framework for hybrid (integrated deployment of system dynamics and discrete event simulation) simulation which can be applied in the healthcare domain.

As hybrid simulation in an organisational context is a new topic with limited available data on deployment of hybrid simulation in organisational context, an inductive approach has been applied. On the basis of knowledge induced from literature, a generic conceptual framework for hybrid simulation has been developed. The proposed framework is demonstrated using an explanatory case study comprising an accident and emergency (A&E) department.

The framework provided detailed guidance for the development of a hybrid model of an A&E case study. Findings of this case study suggest that the hybrid model was more efficient in capturing behavioural impact on operational performances.

The framework is limited to only SD and DES; as agent‐based is another simulation method which is emerging as a promising tool for analysing problems such as spread of infectious diseases in healthcare context, inclusion of this into the framework will enhance the utility of the framework.

This framework will aid in the development of hybrid models capable of comprehending both detail as well as dynamic complexity, which will contribute towards a deeper understanding of the problems, resulting in more effective decision making.

It is expected that this research will encourage those engaged in simulation (e.g. researchers, practitioners, decision makers) to realise the potential of cross‐fertilisation of the two simulation paradigms.

Currently, there is no conceptual framework which provides guidance for developing hybrid models. In order to address this gap, this paper contributes by proposing a conceptual framework for hybrid simulation for the healthcare domain.

The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty.

First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform.

Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system.

The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

This paper aims to explore the applicability and strengths of proposing the three-paradigm hybrid simulation (HS) approach to developing and analysing strategies. The objective of the modelling effort is to conceptually illustrate its use in strategic planning by combining with the threat-opportunity-weakness-strength (TOWS) matrix, which builds a bridge between strategic management with the operations research community. The authors also aim to introduce a modelling framework to help model designers to apply HS to their own business issues.

The paper presents a process to develop a HS model associated with the development of strategies using the TOWS matrix.

After developing the model and testing four strategies, the best option for the supermarket to increase market share and sales is implementing the strength–opportunity strategy, which involves online shopping to adapt to the digital world.

First, some modelling assumptions are used to simplify the development process, but they need further validation. Second, the real data collection is limited. Third, the personal learning edition of the simulation software is not a comprehensive version and has some limitations.

The hybrid model and the scenario planning introduced, in this study, could allow decision makers to rehearse the potential strategy before actual implementation. The framework is easy to implement to other business and industry.

This study links HS with strategic management, which has not been performed previously and evaluates the capability of HS in strategic planning. The functionality of the modelling platform has been tested for simulating a completely dynamic system.

The purpose of this research is to propose a hybrid simulation framework which can take into account both the continuous and operational variables affecting the performance of construction projects.

System dynamics (SD) simulation paradigm is implemented for the modelling of the complex inter-related structure of continuous variables and discrete event simulation (DES) is implemented for the modelling of operational influencing factors. A hybrid modelling framework is then proposed through combination of SD and DES to simulate the construction projects.

This paper discusses the deficiencies of two traditional simulation methods – SD and DES – for simulation of construction projects which can be compensated by implementing hybrid SD–DES model. Different types of basic hybrid structures and synchronisation methods of SD and DES models are introduced.

The proposed hybrid framework discussed in this research will be beneficial to modellers to simulate construction projects.

The paper introduces a theoretical framework for a hybrid continuous- discrete simulation approach which can take into account the dynamics of project environment arising from the complex inter-related structure of various continuous influencing factors as well as the construction operations. Different steps required to develop the hybrid SD–DES model and synchronisation of SD and DES simulation methods are illustrated.

The proposed Sliding Mode Control-Global Regressive Neural Network (SMC-GRNN) algorithm is an integration of Global Regressive Neural Network (GRNN) and Sliding Mode Control (SMC). Through this integration, a novel structure of GRNN is designed to enable online and. This structure is then combined with SMC to develop a stable adaptive controller for a class of nonlinear multivariable uncertain dynamic systems.

In this study, a new hybrid (SMC-GRNN) control method is innovatively developed.

A novel structure of GRNN is designed that can be learned online and then be integrated with the SMC to develop a stable adaptive controller for a class of nonlinear uncertain systems. Furthermore, Lyapunov stability theory is utilized to ensure the hidden-output weighting values of SMC-GRNN adaptively updated in order to guarantee the stability of the closed-loop dynamic system. Eventually, two different numerical benchmark tests are employed to demonstrate the performance of the proposed controller.

A novel structure of GRNN is originally designed that can be learned online and then be integrated with the sliding mode SMC control to develop a stable adaptive controller for a class of nonlinear uncertain systems. Moreover, Lyapunov stability theory is innovatively utilized to ensure the hidden-output weighting values of SMC-GRNN adaptively updated in order to guarantee the stability of the closed-loop dynamic system.

The purpose of this paper is to investigate the stabilization of unstable periodic orbits of Chua’s system using adaptive fuzzy sliding mode controllers with moving surface.

For this aim, the sliding mode controller and fuzzy systems are combined to achieve the stabilization. Then, the authors propose a moving sliding surface to improve robustness against uncertainties during the reaching phase, parameter variations and extraneous disturbances.

Afterward, the authors design a sliding observer to estimate the unmeasurable states which are used in the previously designed controller.

Numerical results are provided to show the effectiveness and robustness of the proposed method.

The purpose of this paper is to explore the dynamics and stability of switched supply system considering the influence of the retailer competition and deteriorating items.

A discrete dynamic switched model is developed to analyze the evolution process of the switched supply chain. The existence and the local stability of the switched supply chain are analyzed using an analytical method and a parameter plot basin.

The author finds the switched supply chain will exhibit stable, periodic, and divergent behaviors with different parameters due to the system’s switching mechanism and the switched supply chain presents complex dynamics when the stable and unstable subsystem coexist.

The originality and value of the research rests on this paper considering the influence of the retailers’ competition and deteriorating items on the supply chain dynamics under stock-dependent demand. The obtained results provide the decision maker with some guidelines on how to make stable designs for the switched supply chain design according to the parameter values.