Search

The topics of recovering of materials, quality control, and environmental impact have gained a raising attention in industrial activities, in order to enforce the quality parameters imposed by the new laws. An innovative approach to control and optimisation of the manufacturing process becomes necessary to cut the industrial costs. For this reason, the interest for the intelligent methods for monitoring and control several process phases has been growing since 80's. This paper deals with the development a Neuro-Fuzzy (NF) system for the corrosion control in Pulp & Paper production. Furthermore, the performance of the NF expert system has been compared with that of the classical Neural Network MLPs (NN).

The pressurized headbox is one of the most important pieces of equipment on a modern paper machine. It is a special two-inputs-twooutputs process, and proper matching of input and output of control loops is very important. Relative gain analysis and computer simulation based on a mathematics model of the pressurized headbox shows that the common used configuration in paper industry is not the best. For this kind of configuration, a multi variable predictive control algorithm is designed. Computer simulation shows that this kind of control algorithm can deal with the headbox control very well. A control system with this kind of controller for full scale pressurized headbox has a good performance with excellent control precision, very short response time and very small offsets.

Whereas condition monitoring as applied to the mechanical processes of papermaking are well established, the complex situation in the wet end is only beginning to be considered. Examples of the effect of retention on mean time, pH measurement and sizing are commented on. A simple model which can be used for thinking about and developing sophisticated control procedures is presented

This paper presents the results of a project aimed at minimising fuel usage while maximising steam availability in the power and steam plant of a large newsprint mill. The approach taken was to utilise the better regulation and plant wide optimisation capabilities of Advanced Process Control, especially Model Predictive Control (MPC) techniques. These have recently made their appearance in the pulp and paper industry but are better known in the oil and petrochemical industry where they have been used for nearly 30 years. The issue in the power and steam plant is to ensure that sufficient steam is available when the paper machines require it and yet not to have to waste too much steam when one or more of the machines suffers an outage. This is a problem for which MPC is well suited. It allows variables to be kept within declared constraint ranges, a feature which has been used, effectively, to increase the steam storage capacity of the existing plant. This has resulted in less steam being condensed when it is not required and in significant reductions in the need for supplementary firing. The incidence of steam being dump-condensed while also supplementary firing the Combined Heat & Power (CHP) plant has been reduced by 95% and the overall use of supplementary firing is less than 30% of what it was. In addition the plant runs more smoothly and requires less operator time. The yearly benefit provided by the control system is greater than £200,000, measured in terms of 2005 gas prices

By focusing on core competencies and the utilization of international location advantages such as access to low-wage labor and local sales markets, global production networks are becoming increasingly complex. Additionally, turbulent times with great uncertainty forces globally acting enterprises to adapt their production networks. Therefore, it is crucial to determine the right point in time for change and also to identify the beneficial production network alternatives. In other words, globally acting enterprises have to answer the two questions of what to change and when to change. The presented method describes an approach for the strategic planning of global changeable production networks, based on future scenarios and a multi-objective optimization to identify the most favorable network configuration during the planning horizon. The multi-objective optimization is modeled as a mixed-integer MODM problem (multiobjective decision making) including seven criteria i.e. costs, delivery time, quality, flexibility, customer proximity, coordination and plant qualification.

Paper manufacturing involves the sequential removal of water from pulp by means of gravity, vacuum dewatering, mechanical pressing and thermal drying. This research proposes a new control topology for moisture content using surrogate measurements to infer in-process moisture content, and the pressure settings in the vacuum dewatering section as actuators. The new topology has the potential to overcome the performance, robustness and energy efficiency limitations that the current process control topology has, due to a long dead-time and excessive use of the dryers. A preemptive control law was previously proposed for the new topology to decouple the upstream disturbances from propagating downstream in the process. In this paper, we develop an adaptive version of this pre-emptive controller to alleviate the need to know the dewatering coefficients precisely. The adaptive control problem has the interesting aspects that the unknown parameters are nonlinearly embedded in the error dynamics, and there is a time delay before the error in the estimated parameters can be observed.

The paper discusses practical solutions and experiences of an Energy Management Systems installed in Enso-Gutzeit Oyas Tainionkoski Mills, in Eastern Finland. The project started in the autumn of 1980 as a co-operation project between Enso-Gutzeit Oy and Oy Advanced Forest Automation Ab as a supplier. The system was brought on line in the beginning of 1983. This Energy Management System is specially developed for integrated pulp and paper mills, where the energy cost is a fast growing part of production costs, the fluctuations in energy demand are continuous and where the variety of energy producers and users gives cause for a mill-wide coordination and information system.

The first applications of real-time digital control to pulp and paper industry stem from early 60’s. Then a centralized hardware was applied to quite large and poorly defined problems. These early projects were not very successful; one of the main reasons being the unreliable and limited hardware. During 70’s the so-called packaged systems entered into the market. These were built by using the existing minicomputers and those systems were dedicated to smaller and well-defined problem areas; for example dry end controls of paper machine, batch-digesting, Kamyr digester, bleach plant etc. Today we are ahead a third generation of these systems in the Pulp and Paper Industry. The microprocessor technology has created the powerful microcomputers and the distributed digital instrumentation systems. This has lead to the concept: decentralized control and centralized reporting and supervision. This means that the lowest level of the control hierarchy will be handled by a digital instrumentation system and with a local datanetwork (data highway, bus) a hierarchical structure including area control and coordination, production planning and scheduling and management information system at the higher levels a total mill-wide hierarchy will be built. There is also clearly a trend towards more integration between process control functions and other EDP activities inside the organization. These existing systems and future needs and trends are discussed in the paper.

A new method is proposed for the synthesis of an optimal control system by a combined criterion “energy-time”. It is illustrated on a concrete object in paper industry - paper machine producing wrapping paper. As an example of control, one of the channels for regulation of the steam pressure coming in the machine, is chosen. The model is a consecutive combination of an aperiodic and an integrating unit with a pure time delay. The optimal criterion is a minimum steam expenditure per a fixed time of the transition process. The synthesis applies the phase plane method. The original quality of the method applied for the synthesis of optimal control is that another modified switch-off line is used, invariant to input effects. The new switch-off line depends only on the time given to the transition process and the parameters of the object. An equation is deduced for the modified switch-off line in the case in discussion. Its construction is represented by a graphic method which may be used for all second order systems. A method can be applied for compensation of time delay where the parameters of auto-variations are minimal in the system. The control lines for switch-off and -on are approximated by some sequences by the method of the equivalent signurn functions. This formulation facilitates considerably the technical realization of the system. A digital modelling is made to the transition process in the steam regulating channel with a synthesized control equipment. It is shown, that the synthesized quasi-optimal control equipment forms effects close to the optimal in form and duration, for the whole range of variation of input effects. The comparison made between the optimal and the quasi-optimal systems shows that the steam expenditure does not differ for the two systems. The time of completion of the process remains constant at that.

This paper tells about a computer application in the control and supervision of paper manufacture. The operating system and the control program modules as well as the opportunities of the process operator to interact with the execution of the programs are described in addition to the computer equipment. Control objects are the basis weight, humidity, machine speed and headbox level and pressure. Their essential features are described together with a description of the supervision, which consists of quality and production reports.

Construction of distributed control systems for pulp and paper production is under consideration. The complex object is interpreted through functional decomposition as a number of interconnected elementary units. Mathematical description of control objects with decentralized structure and certain mathematical production models are presented. Discussion concerns system structure characteristics and application of distributed systems in industry in terms of economy.

The pulp and paper industry produces and consumes a remarkable amount of energy in its processes. Thus energy management is very important in a paper mill. There are many control problems in different types of power plants. The coordination of the power generation and consumption also has to be considered carefully. We here present five cases in which estimation, control and coordination problems in peat, coal, bark, recovery and multi-fuel boilers are examined. The main idea is to formulate the control structure so that the active functions in and between different subprocesses along the production line are directed at the same goal. Thus the controlled variables in a power plant are e.g. fuel power, heat power in the furnace, steam power and electric power. In the fuel power and heat power control this leads to a cascade type control strategy. As an example of a solution of the coordination we present a specialized hierarchical control structure of a multi-fuel boiler house.

This paper outlines new development in the design of Decision Support Systems and Mill Wide control. These developments have been implemented .in a system for a board mill at Thames Purfleet whose management worked closely with the university based Systems Group at Imperial College. The system design to control a multiproduct plant producing a range of reels, sheet and board in various dimensions, consistency, colour and surface finish. It uses advanced procedures for scheduling, deckling, sales forecasting and stock control and employs an advanced “what-if” evolutionary simulation for prediction, management decision support and production control via a terminal network. The system has rapid “conversational” response.

When industrial processes operate under variable production conditions, linear models and linear controllers are generally not efficient. When a paper machine operates at variable speed, the control of the headbox must be efficient for large operating point transitions. We present a dual model reference adaptive controller (DMRAC) that allows the control of linear time varying systems and the explicit on line identification of the process with delayed inputs. The application of the DMRAC to a pressurized headbox when large operating point transitions are applied is presented. Finally a functional decomposition of the DMRAC algorithm for its implementation in a multi-microprocessor system is presented.

The general capabilities and some operational results obtained by two new important control developments with immediate applications in paper making are described. SADACOLOR - the first system to be described is based on Reed’s original stand-alone sampled data controller SADAC, but includes colour display of cross machine variables and multirate sample and control techniques. The successful application of these techniques has led to the development of a new stand-alone sampled data controller, SADAC-M, which is the second system to be described. It is essentially a low cost, partially programmable multivariable controller based on a microprocessor.

Papermaking is considered as an energy-intensive industry partly due to the fact that the machinery and procedures have been designed at the time when energy was both cheap and plentiful. A typical paper machine manufactures a variety of different products (grades) which impose variable per-unit raw material and energy costs to the mill. It is known that during a grade change operation the products are not market-worthy. Therefore, two different production regimes, i.e. steady state and grade transition can be recognised in papermaking practice. Among the costs associated with paper manufacture, the energy cost is ‘more variable’ due to (usually) day-to-day variations of the energy prices. Moreover, the production of a grade is often constrained by customer delivery time requirements. Given the above constraints and production modes, the product scheduling technique proposed in this paper aims at optimising the sequence of orders in a single machine so that the cost of production (mainly determined by the energy) is minimised. Simulation results obtained from a commercial board machine in the UK confirm the effectiveness of the proposed method.

Real-time optimization (RTO) is applied for the broke recirculation in the stock approach system of an integrated newsprint mill simulation. New optimal broke ratio profiles are set for the paper machine recipes each time the process is confronted with an important disturbance. The variability in the four paper machine headboxes is minimized while the inventory management is handled. The proposed approach is compared to the actual mill operation, making use of a detailed plant simulation. While maintaining broke tank level within an acceptable range, RTO brings the pulp variability down about an order of magnitude. It is expected that it could significantly reduce the sheet break occurrence in a real plant and therefore enhance its economical efficiency.

Recycling of paper is typically performed in a chain of processes. An important process is the peroxide bleaching implementing the means to achieve a high brightness quality. As this process step requires consumption of various chemicals, it is quite cost intensive. This paper presents means to optimize the bleaching stage to achieve an (adaptable) trade-off between cost and brightness: First, the time-varying deadtime of the bleaching stage is estimated using a Kalman filter. Second, the bleaching stage is modelled by Gaussian processes aiming to be used for optimization of the bleaching stage by application of a model predictive controller.

The production processes are becoming increasingly complex and the responsibilities of the operators and the engineers are widening. Tools to manage this complexity under dynamic conditions are needed. The dynamic optimization integrated to operator and engineer decision support has a high potential in everyday use. As a result of an EU Commission funded research project a toolset for supporting continuous decision making has been developed. This paper presents a case study, where this toolset is used to reduce grade change time on a paper machine.

Abstract Variations in the pulp quality are mainly due to variations in the quality of wood chips used for pulping. Moisture content of chips, chip size and chip composition vary, and the measurements to reflect these variations do not always exist. Kappa number is the usual way of describing the pulp quality and it measures the residual lignin content in the pulp. In batch digesting, the main difficulty in maintaining consistent Kappa number is the lack of on-line Kappa number measurement. The most common way is to use the calculated H-factor to define the cooking end-point. Kappa number cannot be measured on-line in batch digesters, but there are many approaches to model, or predict, it from the existing measurement, and use the predicted Kappa to complement the H-factor control. Both mechanistic and data-based model are in use, but due to the complexity of fundamental models, current industrial practices rely almost exclusively on simple empirical or semi-empirical models. Several intelligent methods (neural networks and fuzzy logic) together with advanced controls have found applications also on this arena. This paper concerns with using recurrent Elman network together with alkali measurement and H-factor in Kappa number modelling.

In this short paper for the panel discussion on „Experience and challenges in identification of non-linear systems„ some major issues with respect to identification of non-linear biochemical and environmental systems are presented.

Diagnostic strategies for Fault Detection and Isolation in a continuous pulp digester are presented. Several methodologies for Fault Detection and Isolation are compared for accuracy and real-time implementation potential. A Gross Error Detection methodology for biased and noisy measurements is initially examined. Next, a Gaussian Radial Basis Function neural network approach for detection of product quality related changes is also used. Changes in feedstock composition using an additional neural network approach is also developed. The efficiency and limitations of all methods are demonstrated using a first principles model.

This paper describes a hierarchy of models and information systems being developed by integrated producers of corrugated containers to aid in the process of planning and scheduling their operations. The initial focus is on eight easily identifiable decision areas and the tools available to deal with them. The eight decision areas are paper machine loading, master scheduling, trimming, boxcar loading, stock size selection, inventory replenishment, corrugator combining and finishing and shipping scheduling. The remainder of the paper identifies the major interactions among these decision areas and the systems required to deal with them.

In recent years the pulp industry, like any other industry, has been obliged to pay more attention to the problem of effluents. For the most part this has been necessary in order to meet legislative requirements; but the chemical and energy losses due to these effluents are in themselves considerable enough to make their minimization important. This paper presents the results and experiences gained in co-operative projects with the University of Oulu and the Finnish Pulp Industry. The target in these projects has been to develop comprehensive models and advanced control systems for different processes in kraft mills. As a result of these projects the first computer control system in Finland for a recovery boiler has now been in operation since spring 1976 and the first system for a causticizing plant and lime kiln will be implemented in the very near future. In the development of these systems special attention has also been paid to emission monitoring and control. The experiences gained from the recovery furnace system show a remarkable decrease in S02 and H2S emissions, for example. A detailed description of the recovery control system with practical experiences will be given.

The consistency measurement of the pulp is not completely solved problem in pulp and paper industry. Pult is not a newtonian fluid and thus several different problems exist. For example flow and temperature variations of the pulo disturb most measuring systems. Moreover the quality of the pulp and the range of the pulp consistency measurement have an effect to the linearity of the measuring devices. Pulp diluting is usually a control problem of a zero capacity process. There is a dead time between the supplying point of the diluting water and the measurement point of the consistency. Thus the exact and stable control of the consistency is quite a difficult task with traditional analog devices. An industrial compensated measurement and control system for pulp consistency is presented, where the effects of temperature, flow and mass quality variations are compensated. The control strategy is based on the feedforward control and on the Dahlin algorithm. Moreover an advanced system, where the consistency is estimated with a Kaiman filter, is described.

Summary Pulp bleaching is a contiuous process carried out in a number of reactors arranged in succession. The object of the bleach plant control system is directed towards stabilizing the operating conditions as present by temperature, consistency and the reaction time at each bleaching stage as well as by the output pulp quality properties. The cooking degree and the pulp flow at the inlet of the department are the main disturbances The computer solve two tasks: 1. Evaluation of the clorine requirement at the chlorination stage input. The calculation is carried out with the use of the magnitude of the oxidation-reduction potential measured value, the time transport lag and the real clorine consumption value at the moment of measuring. 2. Stabilization of the reaction time at variable pulp flow at the input of the department is the second task. To solve it a highcapacity computer memory is required. The calculation algorithm of levels in the bleach towers involves the probable flow limitations at the input of the individual towers and ensures filling of the memory to switch it quickly for the monitoring procedures. The system is applied at one of the mills in the U.S.S.R.

Wave energy converters (WECs) require active control to maximise energy capture over a wide range of sea conditions, which is generally achieved by making the device resonate. The exaggerated device motion arising at resonance, however, may result in nonlinear effects that are ignored by the linear models that are typically employed. In particular, nonlinear viscous forces are significant for particular device types, such as hinged flaps, which we take as a case study in this paper. The paper develops a general nonlinear WEC control methodology based on pseudospectral methods. The continuous time energy maximization problem is fully discretised (both state and control), and the optimal solution is obtained by solving the resulting finite dimensional optimization problem. By way of example, the nonlinear viscous damping for a hinged flap WEC is incorporate into the control model. It is shown that the ratio of energy captured to energy dissipated is significantly increased with the nonlinear controller, compared to the linear case.

This paper contains a control scheme for power sharing in islanded microgrids with inverter-sourced distributed energy resources that combines robust control and droop control. As the load within the microgrid changes, the inverter-sourced generators share the change in the load; this paper shows that the uncontrolled load sharing among the generators will be arbitrary and methods such as droop control achieve a regulated change. This paper includes a background on control schemes for power sharing and highlights the difficulty in exact reactive power sharing. The performance of the proposed controller is demonstrated using a test microgrid system.

This paper introduces a topic which is of growing interest in the traffic control and management community, namely the relation between traffic data quality and the efficiency of traffic management. After some explanatory background and state of the art, it will become clear that no standard approach is available for traffic engineers to determine which accuracy of traffic data is needed for a certain traffic management application. In this paper we will show how the effect of inaccurate measurements on network level can be quantified by determining information utility functions. This approach is illustrated by presenting the results of a simulation study into the effect of inaccurate loop detector measurements on a ramp metering system. The relation between different accuracies of flow and speed measurements as input for a ramp metering system and the corresponding effect on the network performance is studied with a micro simulation model. The results of the simulation are used in a cost-benefit analysis for a case comparing loop detectors with camera measurements, where loop detectors are considered more accurate but also more expensive. We will show that higher measurement accuracy will lead to a better performance of the ramp metering system, resulting in a higher average network speed, and also quantify this relationship. © IFAC.

This paper deals with the compensator design of launch vehicle attitude control in atmospheric phase using optimization algorithm. Traditionally compensator design is carried out intuitively based on physical parameters of launch vehicle. It is arrived at after a long trial and error procedure to fulfil frequency domain requirements. In this paper a multi-constraint satisfaction algorithm is used to design compensator for attitude control, which takes into account the frequency and time domain requirements. The effect of actuator non-linear behavior on slosh dynamics is investigated and the analytical expression for slosh response with respect to actuator amplitude is derived. The slosh closed loop pole migration with the variation in actuator command amplitudes in root locus is discussed and the implication of acceptable actuator limit cycle amplitude on vehicle body rate is brought out.

This paper presents a new technique for a reconfigurable exoskeleton which consists of a connected network of small sized holonic robots enwrapping the human body limbs and more specifically, in this paper, the human arm. The connection control of the reconfigurable exoskeleton decides upon the necessity of a “disconnect”,” reconnect” for chosen holons so as to balance any new load at the human joints. The intelligent controller carries out its decisions on the evaluation of stress at connections between holons of a previous configuration comparing them for a new actual need. This decision is based on a graph theoretic method, where stress calculations are carried out using finite element method. The paper demonstrates the performance of our approach on a simulation of hyper redundant network of holons wrapping a human arm.

In this paper experiment design for identification of ill-conditioned systems is studied. A short overview of recently proposed techniques is presented. These are mainly based on a singular value decomposition (SVD) of an estimated gain matrix. A summary of this approach with some extensions is given. Another approach is to find a D-optimal solution; the result is essentially the same as found by SVD methods. A result is that it is very important properly to excite the so-called low-gain direction of the system. The methods are motivated by the desire to guarantee integral controllability in model based control designs such as model predictive control (MPC). The dynamics of the process have not been a consideration in these works. However, it is well known from practical studies and simple models that high gains tend to be associated with slow dynamics and low gains with fast dynamics. For experiment design, it is useful to know how general this behaviour is. In this paper it is shown analytically that this indeed is a general property. Simple examples from the literature are used to support the result. Some possible modifications to existing design methods are given for situations, where the dynamics are not aligned with the gain directions.

Fly-back phase of any Reusable Launch Vehicle (RLV), with wings, encounters ballistic flight in the absence of aerodynamic forces, in rare atmosphere at high re-entry altitude. Lifting vehicles enter the atmosphere at high angle of attack to increase the drag so that the vehicle velocity can be reduced. High angle of attack also increases the lift to balance the weight for equilibrium glide flight. During high altitude flight, angle of attack and side-slip estimations based on information from inertial sensors and modeled wind, are accurate enough to be used for feedback in attitude control. Once RLV descends below certain altitude and Mach number reduces below certain value, wind's contribution in angle of attack and side-slip becomes prominent and inertial navigation based estimates of these angles, no more remain accurate for their use in attitude control. To overcome this problem, normal and lateral accelerations are directly used in place of angle of attack and side-slip angle, respectively. Two aspect of control law design are covered in this paper which are applicable to descent flight of a typical RLV. First aspect is the impact of change in feedback signals from side-slip angle to lateral acceleration, on stability of lateral-directional dynamics. It is seen that the selection of feedback variables or sensors, significantly changes the achievable stability margins. Second aspect is the role of sensor placement w.r.t. CG, especially lateral accelerometer, on the stability of lateral-directional dynamics. This aspect of sensor placement is being discussed for the first time in any paper. It is seen that proper placement of accelerometer results in better stability margins.

This paper presents a novel approach to adapt a behavioral model in order to satisfy a requirement in Hennessy-Milner Logic, including an additional box modality operator, expressing an invariant formula. Control system synthesis, as defined in this way, retains all non-invalidating behavior, and thereby guarantees maximal permissiveness for supervisory control. This research extends earlier work by embracing a broader synthesized logic, enabling synthesis with respect to invariant formulas for non-deterministic behavioral models. All definitions and proofs in this paper have been computer verified using the Coq proof assistant.

Experiment results are often worthy and would be a great topic of discussion. Since many years, research on automatic ship berthing had already been going on to make it actually possible so that one can minimize the annual cost of dock damage as well to ensure safe operation for such sophisticated multi input-multi output phenomenon. But, success up to the extent to execute it in real cases not yet possible. Recently upon developing the unique concept named 'virtual window', the authors of this paper had already challenged the automatic ship berthing for Esso Osaka 3-m model even considering wind disturbances up to 1.5 m/s which is 15 m/s for full scale ship and considered as dead end for most ports in Japan. After getting success, for the first time using this concept, automatic ship berthing is planned and executed for free running experiment. This paper is aimed to publish some of valuable experiment results in categorised way depending on behavior of Artificial Neural Network which is used as a controller during the berthing manoeuvre.

This paper design a method for fault detection and isolation based on observers for systems modelled as Descriptor-Linear Parameter Varying (D-LPV) with Unmeasurable Scheduling Functions (USF). The first contribution of the paper is deal with the USF problem by transforming the into an uncertain D-LPV system with an estimated scheduling parameter. As a second contribution, a robust LPV observer is designed with H ∞ performance to supply a robust state estimation against uncertainties provided by USF. Sufficient conditions to guarantee the robustness and convergence are obtained via linear matrix inequalities (LMIs). Finally, an observer bank based on robust H ∞ observers is used to generate residuals and perform sensor fault detection and isolation. A numerical example demonstrates the effectiveness of our methods.

This paper proposes a heuristic approach for planning the activity of multiple carriers cooperating with the goal of eliminating empty truck trips while maximizing the cost saving resulting from their collaboration. The approach foresees three main phases: in the first step, the transportation demand is decomposed in two parts based on freight flows trade-off; in the second step, a linear optimization model, which takes into account compensation mechanisms among carriers, allows to combine two by two trips belonging to different carriers in order to decrease the number of empty movements. In this second phase, the importance of customers is explicitly taken into account by assigning to each trip a preference value. Finally, in the third step, a second optimization problem enables assigning, for each carrier, trucks to trips with the goal of minimizing their travel costs. The proposed heuristic approach has been tested on some instances and the results obtained are analyzed and discussed in the paper.

In this paper, a robust H ∞ fault detection filter is designed for a class of discrete-time nonlinear networked control systems via T-S fuzzy model with multiple bounded state delay and random packet dropout induced by the limited bandwidth of communication networks. Our aim in this paper is to analyze and design a robust H ∞ full-order fault detection filter, such that the filtering error dynamics is asymptotically mean-square stable with a prescribed H ∞ performance level. Sufficient conditions for the existence of the desired filter are presented. Finally, an example is given to illustrate the effectiveness and applicability of the proposed new design method.

This paper presents an analysis to investigate the critical factors which affect the dynamic stability of wind energy conversion systems (WECSs) with permanent magnet synchronous generators (PMSGs). In this paper, at first the detail mathematical model of a WECS with a PMSG is developed and then the modal analysis technique is used to identify the critical factors. The sensitivity of these critical factors on the dynamic stability of WECSs with PMSGs, is analyzed in terms of damping ratio with changes in critical factors. The proposed approach is tested on a WECS with single PMSG for different level of wind energy penetration.

A nonlinear controller design technique, for the enhancement of power quality and power system stability in a vehicle-to-grid (V2G) system, is proposed in this paper. The dynamical model of a V2G system is first developed and then the controller is designed based on the partial feedback linearization of the developed model. The control scheme is developed in such a way that converters in V2G systems are capable of injecting both active and reactive power into the grid. The implementation of the proposed controller requires the stabilization of internal dynamics of V2G systems as it transforms the system into a partly linear and an autonomous system with internal dynamics. The stability of internal dynamics of V2G systems is also discussed in this paper. Finally, the performance of the proposed control scheme is evaluated on a simple test system in terms of power quality and system stability enhancement. From the simulation result it is found that the designed nonlinear controller provides excellence performance in improving power quality and stability of whole system.

Apart from the 20-year anniversary in 2014 of the first publication of the GERAM (‘Generalised Enterprise Reference Architecture and Methodology’) Enterprise Architecture Framework, the timeliness of this paper lies in the new interest in the use of systems theory in enterprise architecture (EA), and consequently, ‘light-weight’ architecture frameworks (AFs). Thus, this paper is about the use of systems thinking and systems theory in EA and about how it is possible to reconcile and understand, based on a single overarching framework, the interplay of two major enterprise change endeavours: on one hand enterprise engineering (i.e. deliberate change) and on the other hand evolutionary, organic change. The paper also demonstrates how such change processes can be illustrated by employing systems thinking to construct dynamic business models; the evolution of these concepts is exemplified using past applications in networked enterprise building, and more recent proposals in environmental-, disaster- and healthcare management. Finally, the paper attempts to plot the way GERAM, as a framework to think about the creation and evolution of complex socio-technical systems, will continue to contribute to the society in the context of future challenges and emerging opportunities.

This paper considers fault-tolerant control of a class of uncertain switched linear time-delay systems and its application to water pollution control. Due to the nature of average dwell-time techniques and the representation of actuator faults, this paper has the following features compared with the existing methods in the literature: 1) the proposed method is independent from switching polices provided that switching is on-the-average slow enough; 2) the proposed controller exponentially stabilizes this class of time-delay systems with actuator faults and its nominal systems (i.e., without actuator faults) without necessarily changing any structures and/or parameters of the proposed controllers; 3) the proposed method treats all actuators in a unified way without necessarily classifying all actuators into faulty actuators and healthy ones. Simulation results are provided to illustrate the effectiveness of the proposed method.

Stability and convergence properties of large-scale integrated systems are essential aspects of the development of truly useful and well-designed cyber-physical systems (CPS). Because of the desire for flexible, adaptive and reactive cyber-physical systems, i.e., global operation, nonlinear analyses and tools are especially important in CPS. Hence, Lyapunov methods are at the core of many critical control methodologies for such systems. This paper considers Lyapunov stability for approximately symmetric systems. Many robotic systems, such as swarms and fleets of mobile robots, distributed sensor networks, highly integrated cyber-physical systems, etc. , are comprised many identical interacting agents, and our prior work has developed computationally efficient stability analyses of the control and dynamics of such symmetric systems. This paper extends those results to the important case where all the agents are not identical, which is important for real-world applications where it is not possible to have exactly identical agents. Importantly, these results do not require the components to have small differences. However, the bounds on the nature of the solutions will obviously depend on how different the agents are.

This paper describes a virtual online monitoring of the non-measurable conditions inside a real-life industrial reactor for the production of polyvinyl acetate. These non-measurable conditions are the conversion, the polymerization rate, the viscosity and the solids content. The goal of this paper is to use them for control strategies, which can be implemented and solved in real time on common industrial programmable logic controllers (PLCs). Currently, these non-measurable conditions can be estimated from the measured variables by a detailed dynamic model, which is composed of a set of differential and algebraic equations, which can only be solved by means of iterative numerical methods. In this work, this model has been simplified and discretized to allow its implementation in industrial PLCs, which is the common practice in the industry. As a result, the PLC available at the factory can estimate the internal status of the reactor in real time with a high accuracy.

This paper deals with the design and evaluation of the performance of fuzzy predictive controller in supervisory mode for a solar-concentration-based power plant, with cylindrical-parabolic solar collectors. For the design of the controller, the inner control loops present in this solar platform are included in the model of the plant. That is, a control loop consisting of a PI plus a feed-forward controller is considered for modeling the closed-loop behavior of the plant. With this purpose, an ARIX and a Takagi-Sugeno model are compared. As expected, the Takagi-Sugeno model performs better than the ARIX model. Therefore, Takagi-Sugeno model is used for designing the supervisory control strategy. The proposed control scheme is tested in the ACUREX simulator (the simulator of the Almeria Solar Platform). The tests included in this paper are: set-point changes, variations in the solar radiation, and modifications in the parameters of the inner control loop.

It is well known that in most bilateral teleoperation systems, variable time-delays arise in the communications. Motivated by this fact, the present work reports the extension to the (asymmetric) variable time-delays case of the adaptive controller for bilateral teleoperators with uncertain parameters and constant time-delays, reported in Nuno et al (2010) [Nuno, E., Ortega, R. and Basanez, L. (2010). An adaptive controller for nonlinear teleoperators. Automatica, 46(1), 155–159]. Compared to the previous work, the stability analysis does not rely on the cascade interconnection structure of the local and remote nonlinear dynamics and the linear interconnection map. Instead, the paper employs a different Lyapunov candidate function that incorporates a strictly positive term, the local and remote position error. With the only assumption that a bound of the time-delays is known, the paper also presents a sufficient condition that ensures the asymptotic convergence of position errors and velocities to zero. Some simulations, in free space and interacting with a stiff wall, illustrate the performance of the proposed control scheme in the presence of variable time–delays.

Motion planning of an autonomous robot in an unknown environment is a challenging task. The prerequisite of any motion planning task is collision avoidance. This paper aims on designing a steering control-law for constructing Generalized Voronoi Diagram (GVD) of an unknown environment. The GVD is a roadmap which offers a maximum clearance path and hence a reliable method to avoid collisions. The GVD comprises of edges and nodes. The GVD node is considered a primary feature of topological localization. This paper proposes a modification in the steering control law for smooth tracing of GVD edge using curvature information at closest points on the obstacle. The proposed modification leads the mobile robot to reach the unknown GVD node. This modification is necessary without which the robot leaves a GVD edge and traces another GVD edge bypassing the GVD node. The modification is suggested based on the geometry of the GVD construction. The proposed steering law is verified using simulations. The simulation result shows that the mobile robot reaches the GVD node with an accuracy of ±0.001 unit distance.

In this paper, a model-based strategy for the air-path, fuel injection timing, and fuel pressure control of a heavy-duty Diesel engine is presented. The engine system is a six-cylinder Diesel engine, equipped with a dual-stage fixed geometry turbo system and a variable valve actuation (VVA) system. The VVA operates on the intake valves, and realizes a late Miller combustion cycle. The control strategy implemented is a multilinear - model predictive control (MPC), which manipulates the intake valve hold and closure timing, the fuel injection timing, and the needle opening pressure. The MPC objectives are: (i) to keep NOx emissions under a reference level, (ii) to keep the air-fuel ratio over a certain reference, while (iii) minimizing fuel consumption under other constraints. The use of a model predictive control strategy is motivated by the fact that the system is a multi-input multi-output system, with several constraints applied to it. This paper presents the applied control strategy and simulation results illustrating the potential of the proposed control. The simulation results show that the control strategy is applicable, and that the fuel consumption is minimized, but also that further refinements are required.