Nonlinear model based control schemes are increasingly being used in industrial applications. Development of a control relevant dynamic model can be singled out as the most important step in the process of synthesizing such controllers. While a mechanistic / grey-box model has better extrapolation ability and portability, development of a nonlinear black box model, directly from perturbed plant data, can be a relatively easy and economically attractive alternative in many situations. Over the last two decades, there has been a growing interest in the use of orthonormal basis filters (OBF) for developing black box models. The OBF based representation seeks to parameterize stable transfer functions using filters Fk(z-1), which are orthogonal rational polynomials in z-1. As a consequence, when compared with the conventional approach, a substantial dimensionality reduction can be achieved through OBF parameterization. Moreover, the orthonormal filters, because of their similarity to the Padé approximation, can model systems that exhibit long time delays. Due to these advantages, several authors have recently resorted to OBF based parameterization of block oriented nonlinear black box models. The resulting models are parsimonious in parameters and, consequently, the data length requirement is moderate. This paper presents a review of nonlinear output error (NOE) and nonlinear ARX (NARX) model development using OBF. To begin with, the linear time series modelling using OBF parameterization is briefly reviewed. The methods available in the literature for the development of models with Wiener, Hammerstein and Wiener-Hammerstein structures are presented next. Features and properties of different model structures are examined in the light of their abilities to model the unmeasured disturbances and to capture complex nonlinear behaviour, such as input and output multiplicities.

In the refineries and petrochemical industries, the large-scale plants are established for high productivity and the plants are integrated to reduce waste material and energy consumption. As the large-scale and complex plants require the difficult operation, automatic control or operator support is expected. Furthermore the plant safety is a big issue and the operators are requested to address the plant abnormality. One of the key solutions for such problems is the process simulation technology, which is useful for analyzing plant behavior and solving optimal and safe plant operations for energy-saving and high-efficiency because the plant with recycle loops and heat integrations is difficult to operate and predict the future behavior. Recently the simulation technology is used for multi-purposes such as plant design, control system design, checking the control loop and control logic, operator support and operator training. This talk will address the recent progress of process simulation technologies in process industry and its availability and the future trend. One of the new trends is multi-purpose online dynamic simulator. Even if the rigorous model based on physical and chemical laws are developed for process simulation, the model adjustment to actual process measurements is necessary for high fidelity simulation because the dynamic characteristics of the process changes according to the operation condition and the feed properties. Dynamic model adaptation and tracking to actual processes enables the real time optimizer of the process with high fidelity process model.

Recent developments in automotive systems have experienced significant increases in complexity and volume associated with high performing functionalities. These technological trends have yet to exhibit any signs of stagnation, and automakers are faced with the challenge to comply with the stringent demands for a better, faster solution in developing the latest cutting-edge automotive technology. With that being said, it has become inevitable for automakers to incorporate a model-based development approach to satisfy these challenges. Mazda乫s SKYACTIV technology, featuring the world乫s highest compression ratio SKYACTIV-G engine has achieved fuel efficiency performance unprecedented in the automotive industry, rivaling that of hybrid electric vehicles. In order to achieve such demanding requirements in a short timeframe, Mazda has utilized the full potential of a model-based development approach from the infant stages of SKYACTIV development, with emphasis in plant and control model design, as well as interactions with other CAE technologies for a complete system validation environment. This presentation will first cover Mazda乫s accomplishments that were achieved from the strategic plan-structure for technology development. Afterwards, the general automotive control design principle and the importance for a model-based development approach will be revisited, and lastly, the specifics behind Mazda乫s fundamental approach, model-conceptualization, and commitment to establish a complete system validation environment in the development of SKYACTIV-G engine will be mentioned to conclude this presentation.

Li⁺-ion batteries are widely used in a variety of products ranging from consumer gadgets such as cell phones and laptops to electric vehicles. Their popularity can be attributed to high energy density and minimal maintenance. Charging these batteries can take anywhere from a few hours for low powered gadgets to many hours for high powered automobiles. Although theoretically possible, fast charging is not preferred because it can lead to unsafe operating temperatures and side reactions that degrade the life of a battery. An optimal algorithm to charge these batteries must therefore account for these constraints in addition to the complex battery dynamics. The battery dynamics are defined by a large interconnected set of partial differential equations. Single Particle Model is an approximation of this set of partial differential equations. In this presentation we develop a constrained moving horizon algorithm to generate an optimal charging profile and illustrate it through a battery example.

After the huge earthquake occurred in East Japan, Mar. 11, 2011, circumstances around the Japanese power system have been drastically changed. Considerable amount of power supply capacity was lost in the East Japan including Tokyo metropolitan area at that time. Power demand had to be reduced to avoid large-scale blackout and all demand sectors had no choice to obey the official request issued from the government for power saving in peak seasons. Currently, for the coming summer peak season, the government has announced that the power saving request would not be issued but the situation of low reserve rate still continues and the amount of CO2 output is kept at high level since the power generation relies mostly on fossil fuel. Renewable energy seems to be one of the most promising options to overcome the above problems and Japanese Government is promoting mass introduction of photovoltaic and wind turbine generators in particular. Their outputs strongly depend on weather conditions, however, and it is pointed out that the mass introduction may induce serious frequency and voltage problems. In this presentation, the present situation of Japanese power system is outlined and the recent research activities related to these uncertain generators will be briefly summarized with some examples.