Economic hybrid non-linear model predictive control of a dual circuit induced draft cooling water system

Petrochemical plants require the addition and removal of energy to and from the process and the movement of material to, from, and within the process piping and vessels. These fundamental mass and energy transfer requirements are typically achieved through the use of process utilities, which include electricity, steam, fuel gas, cooling water and compressed air. Utilities are responsible for a significant portion of the operating cost of a plant. Therefore, reduction in the consumption of utilities is a common process optimisation area. The situation is different when it comes to the generation and transportation of these utilities, which are often overlooked with regard to optimisation. In this paper, the potential benefits of utility optimisation are illustrated with particular focus on the generation and transportation areas. The main objectives are reductions in electrical energy consumption and cost and are illustrated for a dual circuit cooling water system. This system is non-linear and also hybrid in the sense that it contains both continuous and discrete input variables, which significantly complicates the design and implementation of control and optimisation solutions. This paper illustrates how the cost and energy consumption of a hybrid system can be reduced through the implementation of hybrid non-linear model predictive control (HNMPC) and economic HNMPC (EHNMPC). The results are compared to that of a base case and an Advanced Regulatory Control (ARC) case, showing that significant additional benefit may be achieved through the implementation of these advanced control and optimisation techniques. The paper further illustrates that additional capital is not necessarily required for the implementation of these techniques.     

Modelling and Optimal Design of a Carbon Fibre Reinforced Composite Automotive Roof

Structural optimisation was used to carry out the design of an all-composite roof for a late model passenger car. CAD modelling procedures were used to develop the simplified geometric model of the composite roof starting with production CAD data and to create a shell mesh. The shell element roof model was combined with a beam model of the entire body in order to carry out the full-body optimis-ation. Optimisation results yielded a roof which was 71% lighter than the steel automotive roof, which weighed 94 lb (42.7 kg). Although this paper focuses on the use of commercially available software, it demonstrates a level of automation which is not typically used in the automotive industry.     

A systems model combining process-based simulation and multi-objective optimisation for strategic management of mine water

This paper presents a hierarchical systems model, which integrates a simulator of the mine water use process with a multi-objective optimiser for assessing mine water management strategies. The simulator advances prior tools in simulating complicated strategies by placing operation rules on model objects and process states. An optimisation framework that interacts with the simulator is used to identify optimal strategies for water storage, use and reuse that are ‘fit-for-purpose’, easy to handle, and economic. The model has been used to assess mine water use strategies in a coal mine in Queensland, Australia. The simulation results indicate that some tested strategies could reduce water use costs by more than 40%, and raw water needed by more than 50%. Further, the optimisation revealed more easy-to-handle strategies that could save more than 40% of pipeline water and reduce the risks of penalties associated with discharge and of losing production due to insufficient water.     

Simple control rules in a cooperative system for dynamic optimisation problems

The use of centralised, multi-threads cooperative systems, has emerged as a successful alternative to deal with static optimisation problems, avoiding the problem of selecting a particular, isolated strategy. However, when the problem to deal with becomes dynamic in some sense, the question as to whether those systems and the type of control rules employed to control the threads are useful or not remains open.

In this article, we depart from a strategy that joint uses a set of solutions and a set of simple agents, and we propose, compare and test two control rules for updating the former. The rules are a simple replacement frequency mechanism and a fuzzy set based one.

Computational experiments are performed on the moving peaks benchmark problem under different scenarios and the main conclusions are: first, the fuzzy set based rule is better than the frequency based rule and second, both rules are competitive when compared with a state-of-the-art algorithm.     

Safety verification and reachability analysis for hybrid systems

Safety verification and reachability analysis for hybrid systems is a very active research domain. Many approaches that seem quite different, have been proposed to solve this complex problem. This paper presents an overview of various approaches for autonomous, continuous-time hybrid systems and presents them with respect to basic problems related to verification.     

Modeling and control of a single-phase marine cooling system

This paper presents two model-based control design approaches for a single-phase marine cooling system. Models are derived from first principles and aim at describing significant system dynamics including nonlinearities and transport delays, while keeping the model complexity low. The two approaches investigated are: a baseline design for performance comparison and a nonlinear robust control design. Performance and robustness of performance for the two control designs are evaluated through a simulation example. Both designs show good robustness towards parameter variations, while the nonlinear robust design performs better in terms of disturbance rejection.     

Ant search based control optimisation strategy for a class of chaotic system

In this paper the authors propose a logistic mapping using chaotic model to describe the time-variable pest population. Two kinds of fuzzy rule embedded control strategies are investigated, three segment control and five segment control. They are designed to reduce the pest population. The simulation results show that the objective function is non-convex and anomalous along the control parameters. To find the optimal parameter combinations we develop an ant search approach. By imitating the food hunting and nest moving behaviours of Pachycondyla apicalis ants, this method can adaptively and effectively explore solution areas and arrive at the optimal solution. When we compared the performance curves with the one without control strategy, the method is better and can be used for a wide range of pest control problems in real life.     

A new model based approach for the prediction and optimisation of thermal homogeneity in single screw extrusion

In polymer extrusion, delivery of a melt which is homogenous in composition and temperature is important for good product quality. However, the process is inherently prone to temperature fluctuations which are difficult to monitor and control via single point based conventional thermocouples. In this work, the die melt temperature profile was monitored by a thermocouple mesh and the data obtained was used to generate a model to predict the die melt temperature profile. A novel nonlinear model was then proposed which was demonstrated to be in good agreement with training and unseen data. Furthermore, the proposed model was used to select optimum process settings to achieve the desired average melt temperature across the die while improving the temperature homogeneity. The simulation results indicate a reduction in melt temperature variations of up to 60%.     

Design, implementation, and experimental validation of optimal power split control for hybrid electric trucks

Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split algorithm. The presented strategy is adaptive for vehicle mass and road elevation, and is implemented on a standard Electronic Control Unit of a parallel hybrid electric truck. The implemented strategy is experimentally validated on a chassis dynamo meter. The fuel consumption is measured on 12 different trajectories and compared with a heuristic and a non-hybrid strategy. The optimal control strategy has a fuel consumption lower (up to 3%) than the heuristic strategy on all trajectories that are evaluated, except one. Compared to the non-hybrid strategy the fuel consumption reduction ranged from 7% to 16%.     

Binary particle swarm optimisation with quadratic transfer function: A new binary optimisation algorithm for optimal scheduling of appliances in smart homes

Demand response (DR) is the response of electricity consumers to time-varying tariffs or incentives awarded by the utility. Home energy management systems are systems whose role is to control the consumption of appliances under DR programs, in a way that electricity bill is minimised. While, most researchers have done optimal scheduling only for non-interruptible appliances, in this paper, the interruptible appliances such as electric water heaters are considered. In optimal scheduling of non-interruptible appliances, the problem is commonly formulated as an optimisation problem with integer decision variables. However, consideration of interruptible appliances leads to a binary optimisation problem which is more difficult than integer optimisation problems. Since, the basic version of binary particle swarm optimisation (PSO) does not perform well in solving binary engineering optimisation problems, in this paper a new binary particle swarm optimisation with quadratic transfer function, named as quadratic binary PSO (QBPSO) is proposed for scheduling shiftable appliances in smart homes. The proposed methodology is applied for optimal scheduling in a smart home with 10 appliances, where the number of decision variables is as high as 264. Optimal scheduling is done for both RTP and TOU tariffs both with and without consideration of consumers’ comfort. The achieved results indicate the drastic effect of optimal scheduling on the reduction of electricity bill, while consumers’ comfort is not much affected. The results testify that the proposed QBPSO outperforms basic binary PSO variant and 9 other binary PSO variants with different transfer functions.     

Energy-based control for hybrid port-controlled Hamiltonian systems

In this paper we develop an energy-based hybrid control framework for hybrid port-controlled Hamiltonian systems. In particular, we obtain constructive sufficient conditions for hybrid feedback stabilization that provide a shaped energy function for the closed-loop system, while preserving a hybrid Hamiltonian structure at the closed-loop level. Furthermore, an inverse optimal hybrid feedback control framework is developed that characterizes a class of globally stabilizing energy-based controllers that guarantee hybrid sector and gain margins to multiplicative input uncertainty of hybrid Hamiltonian systems.     

Modelling and control of a Fuel Cell System and Storage Elements in transport applications

This paper presents in a first step, a modelling approach to control auxiliaries of a PEM Fuel Cell and the design of control laws. Anode and Cathode compartments are considered to derive the voltage behaviour of the Fuel Cell and to control air and hydrogen flow rate as well as pressure. In a second step, the structure specification of an electrical power train with Fuel Cell for high power transport applications is presented. Two choppers are designed and controlled to deliver the power demand from the Fuel Cell itself and Storage Elements added. This work shows that we can characterise and adjust the system control on an actual operating cycle.     

Advanced Features of Duration Calculus and Their Applications in Sequential Hybrid Programs

Duration Calculus was introduced as a logic to specify real-time requirements of computing systems. It has been used successfully in a number of case studies. Moreover, many variants were proposed to deal with various features of real time systems, including sequential communicating processes, sequential hybrid systems and imperative programming languages. This paper aims to integrate several variants of Duration Calculus, and to provide a semantic framework for real-time programming languages and sequential hybrid programs. A shortversion of this paper appeared in J. Davis, A.W. Roscoe and J.C.P. Woodcock editors, Millennial Perspectives in Computer Science,Proceedings of the 1999 Oxford-Microsoft Symposium in Honour ofProfessor C.A.R. Hoare.     

A simulation model of a sulphuric acid production process as an integrated part of an energy system

Power plant process simulation software is well-suited for the modelling of energy systems and more importantly, tools for analysing the energy efficiency are often built into the software. This work presents the development of a simulation model for a sulphuric acid plant using a commercial software package for power plant process simulation. This will be of value to for instance small consultant and engineering companies involved with audits and analysis of energy systems. For small sized companies the cost of acquiring and maintaining many different specialised software packages will be noticeable. However, companies involved with audits and analysis of energy systems will in most cases have access to at least one software package for power plant process calculations. The use of this kind of software for also modelling chemical plants would be valuable to these companies. The results of this work shows that it is possible to use an inexpensive but powerful power plant process simulation software for modelling a common chemical process as a part of a large energy system.     

An impulse-to-impulse discrete-time mapping for a time-delay impulsive system

It is shown that an impulsive system with a time-delay in the continuous part can be equivalently represented by discrete dynamics under less restrictive conditions on the time-delay value than considered previously.     

A requirements-based programming approach to developing a NASA autonomous ground control system

A new requirements-based programming approach to the engineering of computer-based systems offers not only an underlying formalism, but also full formal development from requirements capture through to the automatic generation of provably-correct code. The method, Requirements-to-Design-to-Code (R2D2C), is directly applicable to the development of autonomous systems and systems having autonomic properties. We describe both the R2D2C method and a prototype tool that embodies the method, and illustrate the applicability of the method by describing how the prototype tool could be used in the development of LOGOS, a NASA autonomous ground control system that exhibits autonomic behavior. Finally, we briefly discuss other possible areas of application of the approach.     

A singularity-free motion control algorithm for robot manipulators—a hybrid system approach

This paper presents the design and implementation of a singularity-free tracking algorithm for robot manipulators using a hybrid system approach. A hybrid robot motion controller is designed to ensure feasible robot motion in the neighborhood of kinematic singularities. The hybrid control system has a two-layered hierarchical structure, a discrete layer and a continuous layer. The robot workspace is partitioned into subspaces based on the singular configurations of the robot. Switching between continuous controllers is involved when the robot travels across the subspaces. With the hybrid controller, the robot can work at the vicinity of singular configurations, but also can go through and stay at the singular configurations. The stability of the hybrid system is investigated using multiple Lyapunov function theory. Experimental results have demonstrated the advantages of the hybrid robot motion control method.     

Algorithmic analysis of polygonal hybrid systems,Part II: Phase portrait and tools

Polygonal differential inclusion systems (SPDI) are a subclass of planar hybrid automata which can be represented by piecewise constant differential inclusions. The reachability problem as well as the computation of certain objects of the phase portrait is decidable. In this paper we show how to compute the viability, controllability and invariance kernels, as well as semi-separatrix curves for SPDIs. We also present the tool SPeeDI⁺, which implements a reachability algorithm and computes phase portraits of SPDIs.     

Non-linear system control using a recurrent fuzzy neural network based on improved particle swarm optimisation

This article introduces a recurrent fuzzy neural network based on improved particle swarm optimisation (IPSO) for non-linear system control. An IPSO method which consists of the modified evolutionary direction operator (MEDO) and the Particle Swarm Optimisation (PSO) is proposed in this article. A MEDO combining the evolutionary direction operator and the migration operation is also proposed. The MEDO will improve the global search solution. Experimental results have shown that the proposed IPSO method controls the magnetic levitation system and the planetary train type inverted pendulum system better than the traditional PSO and the genetic algorithm methods.