Experimental Nonlinear Model Based Predictive Control for a Class of Semi-Batch Chemical Reactors

This paper investigates experimentally the application of a nonlinear model based predictive control (NLMBPC) to a class of semi-batch chemical reactors equipped with a mono-fluid heating/cooling system. We present the experimental results dealing with a strongly exothermic reaction carried out in a small pilot plant according to a procedure commonly used in industry. The application of the NLMBPC is based on a constrained optimisation problem solved repeatedly on-line. The control objective is to keep the reactor temperature within safe operating specifications by manipulating the heating power. Experimental results demonstrate that this control strategy works well in the presence of hard constraints and load dis-turbances.     

Feasibility analysis of stand-alone renewable energy supply options for a large hotel

This paper provides a feasibility analysis of renewable energy supply (RES) for a stand-alone supply large-scale tourist operation (with over 100 beds). The analysis utilises the power load data from a hotel located in a subtropical coastal area of Queensland, Australia. The assessment criteria of the analysis are net present cost, renewable factor and payback time. Due to the limited number of RES case studies in tourist operations and the absence of studies for large resorts, requiring facilities with a higher degree of comfort such as air-conditioning, it is not possible to establish with confidence the viability of RES in this industry. The specific operational characteristics of the tourism accommodation sector, such as 24-h operation, comfort provision and low tolerance for failure necessitates a separate assessment of RES viability for this sector, rather than relying on similar assessments from other commercial sectors. This study uses RES assessment software tools, HOMER (National Renewable Energy Laboratory, US) and HYBRIDS (Solaris Homes, Queensland, Australia), in order to compare diesel generator-only, RES-only and RES/diesel hybrid technologies. HOMER uses hourly load data, whilst HYBRIDS uses average daily energy demand for each month. The modelling results demonstrate that RES, in principle, has the potential to adequately and reliably meet power demand for a stand-alone large-scale tourist accommodation. Optimisation modelling demonstrates that 100% of power demand can be supplied by a RES-only configuration. A hybrid diesel/RES configuration provides the lowest NPC result with a resultant RF of 76%. In comparison to the diesel generator-only configuration, NPC is reduced by 50% and Greenhouse Gas (GHG) emissions by 65%. The payback time of the hybrid RES scenario is 4.3 years. Results indicate that wind energy conversion systems (WECS), rather than photovoltaics, are the most economically viable RES for large-scale operations. Large-scale WECS (over 1000 kW) are more efficient and economical than multiple small-scale WECS (0.1–100 kW). Both modelling tools produced similar results, with HYBRIDS producing on average slightly higher NPC results than HOMER. The modelling and resulting data from the analysis indicate that RES is technically feasible and economically viable as a replacement for conventional thermal energy supply for large-scale tourist operations dependent on stand-alone power supplies.     

Batch-to-batch optimal control of a batch polymerisation process based on stacked neural network models

A neural network based batch-to-batch optimal control strategy is proposed in this paper. In order to overcome the difficulty in developing mechanistic models for batch processes, stacked neural network models are developed from process operational data. Stacked neural networks have enhanced model generalisation capability and can also provide model prediction confidence bounds. However, the optimal control policy calculated based on a neural network model may not be optimal when applied to the true process due to model plant mismatches and the presence of unknown disturbances. Due to the repetitive nature of batch processes, it is possible to improve the operation of the next batch using the information of the current and previous batch runs. A batch-to-batch optimal control strategy based on the linearisation of stacked neural network model is proposed in this paper. Applications to a simulated batch polymerisation reactor demonstrate that the proposed method can improve process performance from batch to batch in the presence of model plant mismatches and unknown disturbances.     

Fatty acid esterification by reactive distillation: Part 2—kinetics-based design for sulphated zirconia catalysts

In a previous study on the basis of reaction equilibrium, it was demonstrated that the synthesis of fatty acids esters of heavy alcohols by catalytic reactive distillation (RD) is basically feasible. Presently, the analysis is expanded to the kinetics-based design applied to the synthesis of 2-ethylhexyl dodecanoate. Experimental data for a super-acidic sulphated zirconia catalyst are employed. It is shown that this catalyst is highly selective even for the high alcohol/acid ratios as prevail in a RD column. To avoid catalyst deactivation, liquid-liquid segregation into an organic and an aqueous phase must be prevented, and operating temperatures beyond must be chosen. A kinetic model based on liquid activities is proposed, with parameters determined from both kinetic and equilibrium measurements. A typical column design has 13 reactive stages with a catalyst loading of , temperature profile of 400-, and a space velocity of for 99.9% purity product ester. A modified Damköhler number is proposed.     

An efficient evolutionary optimisation framework applied to turbine blade firtree root local profiles

In this paper, an efficient evolutionary optimisation of a turbine blade firtree root local profile is presented. The firtree geometry is designed using an intelligent rule-based computer-aided design system (ICAD) and analysed using an industrial-strength finite element code. A large number of geometric and mechanical constraints drawn from past experience are incorporated in the design of the model. The high computational cost associated with finding optimal designs using high-fidelity codes is addressed using a surrogate-assisted genetic algorithm. The initial surrogate model is first built based on points sampled with a design-of-experiment method. A database of designs analysed using the high-fidelity code is built and augmented while the genetic algorithm progresses. In the procedure for deciding whether the high-fidelity code should be run, a simple 3 principle is used instead of searching for the point with maximum expected improvement. This is combined with an appropriate ranking of the design points within the database. Some benchmark test problems are first used to illustrate the effectiveness and efficiency of the framework. When applied to the problem of local shape optimisation of a turbine blade firtree root, significant improvement is achieved using a limited computational budget.     

A review and critique on integrated production–distribution planning models and techniques

Optimisation modelling of integrated production–distribution (P–D) plans has raised significant interest among both researchers and practitioners over the past two decades. This paper provides the readers with a comprehensive review and critique on the current P–D planning and optimisation literature. We classify the published P–D planning models into seven categories based on their degree of complexity and hence capability in addressing real-life scenarios. Summary tables highlight the main characteristics of the selected models at each category. Next, the paper reclassifies and evaluates the proposed models based on the solution techniques used. Lastly, the unaddressed areas in the current literature are highlighted, important managerial implications are proposed and directions for future research in the area are suggested.     

Using control theory to optimise profit in APVIOBPCS inventory systems

This paper describes an investigation of the effects on the variation of profitability with time caused by the choice of control formulation in a model for an Automatic Pipeline, Variable Inventory and Order Based Production Control System (APVIOBPCS) production system. The improvements are demonstrated using an example of electronic RAM production used by Deif and ElMaraghy [26]. The investigation using a SIMULINK™ model, includes varying the “order up to inventory” values, and “work in progress” values (WIP).