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The purpose of this paper is to study the parameter estimation problem of nonlinear multivariable output error moving average systems.

A partially coupled extended stochastic gradient algorithm is presented for nonlinear multivariable systems by using the decomposition technique.

The proposed algorithm can realize the coupled computation of the parameter estimates between subsystems.

This paper develops a coupled parameter estimation algorithm for nonlinear multivariable systems and directly estimates the system parameters without over-parameterization.

As the excessive lifting force can lead to catwalk rollover and well site accidents, the lifting process boundary conditions and structural parameters have a significant effect lifting force, it is important to analysis the structural parameters on the maximum lifting force in the lifting process of power catwalk.

A new model is proposed to analyze the influence of structure parameters on its lifting force for lifting power catwalk in this paper, and the geometric and dynamic equations are established according to the different boundary conditions in different stages. In addition, the establishment of dynamics equations is based on D'Alembert's principle. To solve the model, dynamic analysis software is developed, which uses c # call MATLAB to solve the geometric and dynamic equations. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

The best value of offset e is 0. The length of L22 should as small as possible while the installation size of the end of the conveying arm are guaranteed. The length of L1 should as small as possible while ensuring the not exceed the maximum value. The maximum lifting force remain the same in the second phase, the maximum lifting force decreases with the increase of Lcp, Lcpshould as small as possible. The maximum pressure of the hydraulic oil dropped by an average of 13.62% under optimized parameters.

This paper provides a theoretical basis for the selection of hydraulic winch, which also provides the theoretical basis and data support for the design and optimization of the structural parameters of the power catwalk.

This research has industrial applications in SJ Petroleum Machinery CO.LTD, SINOPEC (China) .CANRIG, North Rig, TESCO, Sichuan HONGHUA petroleum equipment CO.LTD of CNPC., Baoji Oil field Machinery CO.LTD, SJ Petroleum Machinery Co. LTD of SINOPEC, Yantai Jereh Oilfield Services Group CO.LTD, Nanyang clips oil equipment (group) CO. LTD, etc are the likely users.

A new model is proposed to analyze the lifting force of lifting power catwalk. The model takes into account the inertia force of the structure, development of dynamics software and analysis and optimization of structural parameters. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

The purpose of this paper is to study the identification methods for multivariable nonlinear Box‐Jenkins systems with autoregressive moving average (ARMA) noises, based on the auxiliary model and the multi‐innovation identification theory.

A multi‐innovation generalized extended least squares (MI‐GELS) and a multi‐innovation generalized ex‐tended stochastic gradient (MI‐GESG) algorithms are developed for multivariable nonlinear Box‐Jenkins systems based on the auxiliary model. The basic idea is to construct an auxiliary model from the measured data and to replace the unknown terms in the information vector with their estimates (i.e. the outputs of the auxiliary model).

It is found that the proposed algorithms can give high accurate parameter estimation compared with existing stochastic gradient algorithm and recursive extended least squares algorithm.

In this paper, the AM‐MI‐GESG and AM‐MI‐GELS algorithms for MIMO Box‐Jenkins systems with nonlinear input are presented using the multi‐innovation identification theory and the proposed algorithms can improve the parameter estimation accuracy. The paper provides a simulation example.

Past studies show that companies’ connection with the government (or politically connected companies (PCCs)) contributed negatively to their financial performance. The grabbing hand theory suggests that political connection demand companies to serve political and social obligation that exhaust companies’ financial resources. The purpose of this paper is to extend the previous studies by examining the role of monitoring mechanisms, specifically corporate governance mechanism and institutional ownership (IO), whether they weaken or strengthen the financial performance of PCCs in Malaysia.

The sample consists of all companies listed on the Main Board of Bursa Malaysia (previously known as Kuala Lumpur Stock Exchange) for the year of 2004-2007. The time periods were chosen because there were no significant economic and political events that could possibly distorted the financial and non-financial data.

The findings show that companies’ political connection (the presence of political figure or government representative as members of board of director) has consistently showing negative relationship with performance. The result is consistent with the grabbing hand theory that argues that companies’ connection with government would actually destroy companies’ value. The monitoring role of corporate governance as measured by the percentage of independent board members does not have any significant effect on firm’s performance. The monitoring role of corporate governance as measured by the composition of independent board members have shown a positive significant effect on the company’s performance. However the second monitoring mechanism, the percentage of institutional investors, have a tendency to weaken the company’s performance.

The findings of this study provide an additional understanding of the consequence of government intervention on companies’ performance. This study also highlights the role of monitoring mechanism (independence board members and IO) in strengthening or weakening the performance. The findings suggest that the proper appointment criteria for board members should be seriously considered to ensure better corporate governance structure. Therefore, the formation of the nomination committee as suggested by the current Malaysian Code of Corporate Governance play an important contribution to ensure candidates nominated as board members have proper credentials and qualifications to carry out responsibilities as board members.

Disturbing increase in the use of virgin resources to produce new products has threatened the environment. Many countries have reacted to this situation through regulations which aim to eliminate negative impact of products on the environment shaping the concept of environmentally conscious manufacturing and product recovery (ECMPRO). The first crucial and the most time-consuming step of product recovery is disassembly. The best productivity rate is achieved via a disassembly line in an automated disassembly process. In this chapter, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) with multiple objectives that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent time increments among disassembly tasks. Due to the high complexity of the SDDLBP, there is currently no known way to optimally solve even moderately sized instances of the problem. Therefore, an efficient methodology based on the simulated annealing (SA) is proposed to solve the SDDLBP. Case scenarios are considered and comparisons with ant colony optimization (ACO), particle swarm optimization (PSO), river formation dynamics (RFD), and tabu search (TS) approaches are provided to demonstrate the superior functionality of the proposed algorithm.

This paper aims to provide organizations with a new tool to make decisions related to a facility (building) selection process. Traditionally, value engineering (VE) applies the Value = Function/Cost formula to evaluate the worth of a product. In this paper, the VE-based facility-selection approach is proposed, where the cost of a facility is expressed in net present value (NPV) as it contains the net expense of purchasing or leasing a building as well as the time value of money. Also, a method of quantifying functions and involved risks of different facility choices is proposed.

The framework of the VE-based facility-selection process is broken down into three steps: preparation, calculation/analysis and assessment. In the latter part of this paper, the authors share a sample analysis by illustrating the analysis and decision-making process when three hypothetical facility-selection options are available.

The sample analysis indicates that companies can get the lowest cost and risk while improving their functions to achieve the highest value by using the modified VE formula to drive an optimal option for company’s business expansion and facility-selection process.

This paper provides organizations with a strategic system and process to select proper facilities or buildings for business expansion. The VE approach suggested in this study can allow facility/real estate portfolio decision-makers to analyze financial and functional aspects of the facility at the same time and obtain the value coefficient when they choose a new facility from different options. Finally, they can select the best option, which has the highest value coefficient, given financial and functional considerations.

The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes.

A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes.

A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies.

The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method.

This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

The purpose of this study was to find whether there was any significant difference in performance between government-linked companies (GLCs) and private-owned companies (POCs) and there was any significant improvement in performance of GLCs after Malaysian Government ' s initiatives to transform the GLCs to high-performance companies.

Panel data estimation techniques were used to run the regression in this study.

It was found that there was no significant difference in performance level between GLCs and POCs. It was also found that the performance level of GLCs had improved significantly after the initiation of GLCs ' transformation programme by the Malaysian Government.

The implication of the results of this study is that state-owned enterprises in developing countries like Malaysia can be relevant and important to take care of social responsibilities and needs, as also they can perform at par with private companies. There is no need for privatization of government-owned enterprises; rather, it needs corporatization. Government-owned enterprises can play an important role to drive national development.

The purpose of this paper is to study the effect of Malaysian Code on Corporate Governance (MCCG) on the performance of the listed companies in Malaysia.

Panel data estimation techniques were used to run the regression in this study, following Baltagi (1995). The authors have selected 116 listed companies to Bursa Malaysia during the period 1996-2014, to study the effect of corporate governance on firm performance. Listed companies in Malaysia are mandatory to comply with MCCG rules and regulations.

It was found that there was a significant improvement in the performance of listed companies after Malaysian Government’s implementation of MCCG (2000) which means that MCCG matters for firm performance in Malaysia. It was also found that there was no significance difference in the overall impact of implementation of MCCG on performance level between government-linked companies (GLCs) and private companies (PCs).

The authors have selected only 116 listed companies to Bursa Malaysia during the period 1996-2014, to study the effect of corporate governance on firm performance. The selection of the data was based on the availability of data in Thomson data stream.

The findings had contributed to the understanding that the MCCG has improved significantly the performance of listed companies in Malaysia.

In this paper, with the goal of reducing the fuel consumption of UAV, the engine performance optimization is studied and on the basis of aircraft/engine integrated control, the minimum fuel consumption optimization method of engine given thrust is proposed. In the case of keeping the given thrust of the engine unchanged, the main fuel flow of the engine without being connected to the afterburner is optimally controlled so as to minimize the fuel consumption.

In this study, the reference model real-time optimization control method is adopted. The engine reference model uses a nonlinear real-time mathematical model of a certain engine component method. The quasi-Newton method is adopted in the optimization algorithm. According to the optimization variable nozzle area, the turbine drop-pressure ratio corresponding to the optimized nozzle area is calculated, which is superimposed with the difference of the drop-pressure ratio of the conventional control plan and output to the conventional nozzle controller of the engine. The nozzle area is controlled by the conventional nozzle controller.

The engine real-time minimum fuel consumption optimization control method studied in this study can significantly reduce the engine fuel consumption rate under a given thrust. At the work point, this is a low-altitude large Mach work point, which is relatively close to the edge of the flight envelope. Before turning on the optimization controller, the fuel consumption is 0.8124 kg/s. After turning on the optimization controller, you can see that the fuel supply has decreased by about 4%. At this time, the speed of the high-pressure rotor is about 94% and the temperature after the turbine can remain stable all the time.

The optimal control method of minimum fuel consumption for the given thrust of UAV is proposed in this paper and the optimal control is carried out for the nozzle area of the engine. At the same time, a method is proposed to indirectly control the nozzle area by changing the turbine pressure ratio. The relevant UAV and its power plant designers and developers may consider the results of this study to reach a feasible solution to reduce the fuel consumption of UAV.

Fuel consumption optimization can save fuel consumption during aircraft cruising, increase the economy of commercial aircraft and improve the combat radius of military aircraft. With the increasingly wide application of UAVs in military and civilian fields, the demand for energy-saving and emission reduction will promote the UAV industry to improve the awareness of environmental protection and reduce the cost of UAV use and operation.