Cold rolling mill thickness control using the cascade-correlation neural network

The improvements in thickness accuracy of a steel strip produced by a tandem cold-roIling mill are of substantial interest to the steel industry. In this paper, we designed a direct model-reference adaptive control (MRAC)  scheme that exploits the natural level of excitation existing in the closed-loop with a dynamically constructed cascade-correlation neural network (CCNN) as a controller for cold roIling mill thickness control. Simulation results show that the combination of a such a direct MRAC scheme and the dynamically constructed CCNN significantly improves the thickness accuracy in the presence of disturbances and noise in comparison with to the conventional PID controllers.

Eccentricity and hardness control in cold rolling mills with a dynamically constructed neural controller

The main objective of a steel strip rolling process is to produce high quality steel at a desired thickness.  Thickness reduction is the result of the speed difference between the incoming and the outgoing steel strip and the application of the large normal forces via the backup and the work rolls.  Gauge control of a cold rolled steel strip is achieved using the gaugemeter principle that works adequately for the input gauge changes and the strip hardness changes.  However, the compensation of some factors is problematic, for example, eccentricity of the backup rolls.  This cyclic eccentricity effect causes a gauge deviation, but more importantly, a signal is passed to the gap position control so to increase the eccentricity deviation.  Consequently, the required high product tolerances are severely limited by the presence of the roll eccentricity effects.
In this paper a direct model reference adaptive control (MRAC) scheme with dynamically constructed neural controller was used.  The aim here is to find the simplest controller structure capable of achieving an optimal performance.  The stability of the adaptive neural control scheme (i.e. the requirement of persistency of excitation and bounded learning rates) is addressed by using as the inputs to the reference model the plant's state variables.  In such a case, excitation is due to actual plant signals (states) affected by plant disturbances and noise.  In addition, a reference model in the form of a filter with a desired transfer function using Modulus Optimum design was used to ensure variance in the desired dynamic characteristics of the system.  The gradually decreasing learning rate employed by the neural controller in this paper is aimed at eliminating controller instability resulting from over-aggressive control.  The moving target problem (i.e. the difficulty of global neural networks to perfrom several separate computational tasks in closed -loop control) is addressed by the localized architecture of the controller.  The above control scheme and learning algorithm offers a method for automatic discovery of an efficient controller.
The resulting neural controller produces an excellent disturbance rejection in both cases of eccentricity and hardness disturbances, reducing the gauge deviation due to eccentricity disturbance from 33.36% to 4.57% on average, and the gauge deviation due to hardness disturbance from 12.59% to 2.08%.

Adaptive intelligent systems for energy management of vehicles

The thesis demonstrated the architecture of adaptive intelligent systems for energy management that is capable of interacting with complex systems including the vehicle, environment, and driver components, as well as the interrelationships between these variables, to deliver fuel consumption improvements.

A robust learning control for SISO Nonlinear systems with T-S Fuzzy Model : C02-robust control

In this paper, a robust learning control is developed for a class of single input single output (SISO) nonlinear systems with T-S fuzzy model. It is seen that the proposed sliding mode learning control with the powerful Lipshitz-like condition can guarantee the stability, convergence and robustness of the closed-loop system without involving any assumptions on uncertain system dynamics. In addition, theconcept that the local system with the maximum membership function dominates the system dynamic behaviours helps to greatly simplify the control system design. It will be further seen that the continuous learning control ensures the advantage of chattering-free that may occur in conventional sliding mode systems. Simulation examples are presented to demonstrate the effectiveness of the proposed learning control through the comparison with the H-infinity control.

Agency theory, national culture and management Control Systems

Management control system of an organization is the structured facet of management, the formal vehicle by which the management process is executed. In most organizations, systems exist for planning, organizing, directing, controlling and motivating. Depending on the level of appropriateness and quality of the management control systems, the task of management is either facilitated or hindered. The end goal of a management control system is achieving organizational objectives. Because employees (agents) do not always give their best efforts for achieving organizational objectives, management control systems need to strive for aligning goals of agents (e.g., employees, subordinates) with that of principals (e.g., senior management, owners). Agency theory and its extension, principal agent model, provide insights to the problem of goal congruence and suggest remedies, at least in the Western cultural context. Whether the agency theory presumptions, predictions and prescriptions are universally applicable is an important issue in management. Their validity in different cultural contexts is largely unknown. The available literature to date indicates the possibility that agency theory may not be valid in non-western cultures. However, further empirical research is needed in non-western cultures to shed more light to this issue.

Management control systems use, organisational capabilities and performance in universities: application of the resource-based view

Invoking the resource-based view (RBV), this study investigates relationships between management control systems (MCSs) use, including information use from performance measurement systems (PMSs), and organisational capabilities in the context of academic units of Australian universities. Increased competition and attention to distinctive capabilities amongst universities, particularly at their strategic operating unit level of Schools 1, provides the setting for application of this theoretic perspective. The objective of this study is to model various relationships between diagnostic and interactive use of MCSs, attention given to centrally-imposed and discretionary types of PMS information, the strength of capabilities of the academic unit and, in turn, performance of the academic units. This objective is investigated using a field survey in which a mail survey instrument is administered to a census of all Heads of Schools in all 39 universities in Australia. Valid responses were received from 166 Heads. Principal components factor analysis finds that Heads conceived capabilities of their unit in functional dimensions, not in generic dimensions as found in prior literature; Heads also considered performance measures in terms of their importance (critical or discretionary) rather than type (financial versus non-financial). Partial least-squares analysis is then used for path modelling, and several significant results are obtained. Highlights are that diagnostic MCS use and centrally-imposed performance measures, i.e., key performance indicators, but not interactive MCS use or discretionary performance measures, significantly relate to some or all of the strength of capabilities in the fields of teaching, research and networking, and in turn indirectly relate to performance of the academic units. The findings have practical implications for styles of control systems use; focus on selected key performance measures; and development of organisational capabilities for achievement of superior performance by academic schools in universities.

Agency theory and culture : implications for research in management control systems

The objective of this paper is to encourage further research into the applicability of agency theory for the study of management control issues of organisations in Asian societies.

Management control systems and effectiveness of knowledge sharing

Numerous empirical studies on knowledge management have examined the relative effectiveness of various enablers, such as organizational structure (Bennett and Gabriel, 1999; Gold et aI., 2001), technology (Gold et aI., 2001; O'Dell and Grayson, 1998), culture (DeLong and Fahey, 2000; Gupta and Govindarajan, 2000), managerial system (Nonaka, 1994; Sveiby, 1997) and strategy (Bierly and Chakrabarti, 1996; Holsapple and Joshi, 2001) on knowledge creation and sharing in organizations. Little research has focused on the role of management control systems (MCS) in facilitating knowledge sharing in knowledge-intensive firms (Ditillo, 2004). This study examines how the interactive use of management control systems (MCS) could facilitate the different modes of knowledge sharing among accounting professionals in Malaysia. Based on Nonaka's (1994) knowledge sharing mode, this study found a highly significant relationship between an interactive use of MCS and knowledge sharing to suggest that a more open, less fmancial-oriented and more interactive type of MCS tends to interlink and underpin organizational social process which is the central part of the knowledge sharing process. While professional accountants are generally keen to gain access to knowledge databases to source for possible task solutions, they are generally hesitant to share their tacit knowledge by transforming that knowledge into explicit form. The fmding suggests that there may be cultural-related factors that inhibit sharing of one's tacit knowledge totally and completely.

Improvement on delay dependent absolute stability of Lurie control systems with multiple time delays

Absolute stability of Lurie control systems with multiple time-delays is studied in this paper. By using extended Lyapunov functionals, we avoid the use of the stability assumption on the main operator and derive improved stability criteria, which are strictly less conservative than the criteria in [2,3].