Driven by the needs of innovative process industries, the role of control engineering in process industries is being expanded. In this article, the gaps between emerging needs and the current process control technology are discussed, which are summarized in “protective control,” “process and product control” and “plant- and business-wide control.” The effort to reduce these gaps promises a bright future for control engineering.
This paper presents the experiences of the authors over the past three decades with the development of information and control systems based on the concept of autonomous decentralized systems. The autonomous decentralized system concept was born in the late 1970s stimulated by the emergence of microprocessors, which suggested a decentralized information and control system architecture with a publish/subscribe communication model. Successful applications to manufacturing systems as well as social infrastructure systems created the current dedicated architectures which are focused on achieving intelligent communication fields for meeting large-scale ever-changing plants with capabilities enabling collaboration between stakeholders as well as integration of ubiquitous devices.
Although the term “ubiquitous” may sound like jargon used in information appliances, ubiquitous computing is an emerging concept in industrial automation. This paper presents the author's visions of field ubiquitous computing, which is based on the novel Internet Protocol IPv6. IPv6-based instrumentation will realize the next generation manufacturing excellence. This paper focuses on the following five key issues: 1. IPv6 standardization; 2. IPv6 interfaces embedded in field devices; 3. Compatibility with FOUNDATION fieldbus; 4. Network securities for field applications; and 5. Wireless technologies to complement IP instrumentation. Furthermore, the principles of digital plant operations and ubiquitous production to support the above key technologies to achieve field ubiquitous systems are discussed.
In the pig-ironmaking process, factors that cause operation malfunctions have increased with both the enlargement of the blast furnace and the increasing use of low quality ore. Therefore, an operation support system that predicts blast furnace performance is demanded. This paper reports the development of a blast furnace operation support system with an integrated simulator and “Large-scale database-based Online Modeling (LOM).” To develop the integrated simulator, a sophisticated burden distribution model is integrated with a two-dimensional total internal phenomenon model for the stationary state by using Java technology. Moreover, an integrated simulator for the partial non-stationary state is developed by modifying the two-dimensional total internal phenomenon model for the stationary state. To incorporate the LOM system into the operation support system, a cross-platform LOM system with general versatility is rebuilt by an existing LOM system. The operation support system is realized by the simulator of the physical modeling method and the LOM of the local modeling method. As a result, the operation support system predicts a dynamic molten pig-iron temperature in the blast furnace. The operation support system is expected to provide staff with useful information.
A practical model predictive control method is proposed which was applied to a cement raw material mixing process. The method has a hierarchical structure of 3 layers consisted of set point calculation with an optimizer, multi-input multi-output material mixing ratio control system with the Model Predictive Control scheme, and local control system DCS (Distributed Control System) with PID controllers. It realized priority management of multi-objective control specifications and constraints, avoidance of infeasibility in optimization, handling of control degree of freedom, feed-forward control for transient manipulation, and adaptation to the time-varying components in each raw material with Kalman filtering estimator. A 72-hour test operation was executed for a real plant with regular raw materials and some additive industrial waste materials, which revealed good control performance and reached an economical optimal operation point automatically.
In petroleum refineries and petrochemical processes, the production cost reduction is a key matter in improving competitiveness. Previously, the authors proposed the cyclic one-spot tuning PID control scheme for single-input and single-output systems, and applied it to the atmospheric distillation tower. The effectiveness of the proposed control scheme has been verified in steady operation mode. However, satisfactory performance could not be obtained when the operation mode was switched to transition operation mode. In order to overcome this problem, it is necessary to consider the influence of the interactions upon each input and each output. This paper presents a new multiloop one-spot tuning PID control scheme with a static pre-compensator. According to the newly proposed control scheme, satisfactory control performance can be obtained in both the steady and the transition operation modes.
This paper considers an optimal path generation problem that generates a path of an automobile without any collision with obstacles. The problem is formulated as a mixed integer programming problem. In the problem the obstacles and environments around the automobile can be represent as inequality conditions. The dynamics of the obstacle is described as variation of a prohibited region. According to model predictive control we solve the optimal path generation problem at each time step then apply the first element of the optimal input. The method proposed in this paper can deal with an explicit representation of the dynamics of the obstacle and provides no collision between the automobile and the obstacle.
A lumped parameter plant modeling based on fully combined physical domains has been proposed as a key technology of MBD (Model-Based Development). The method derives a physical model strictly defined as the one to satisfy the relevant conservation laws. To execute the model, symbolical equation handling is applied because it derives the nonlinear differential algebraic equations. Projection method has been combined to make the mechanical system modeling flexible.
A Command Generation Method of Point-to-Point (PTP) control is presented for suppressing mechanical residual vibration and positioning machine load at a designated time. A time domain property of commands to suppress residual vibration is analyzed. This property shows that relation command shapes and vibration are important to suppress residual vibration, and selection of command shape depending on positioning time is necessary to suppress residual vibration. By using this property, concrete command generation methods are proposed. Proposed commands for suppressing residual vibration are formulated simply, and require few computational resources to be generated. Experimental results are presented to verify the effectiveness of the proposed commands.
This paper presents a design methodology for fast and precise positioning using a full closed loop sampled servo control system. A servo control of hard disk drive (HDD) achieves 3-4 ms fast access and nanoscale positioning accuracy. To achieve the nanoscale precise positioning, a full closed loop feedback control is a key structure. From control theory viewpoint, the full closed loop is an ideal method, but it is difficult to take this method in industries due to sensor allocation. In HDD, this full closed loop feedback control has been applied for last 20 years. The full closed loop sometimes brings drawbacks to the servo control design. In HDD case, that is a limited sampling rate selection. In this paper, based on these two features which are the full closed loop and a sampled servo, uniquely developed servo design methods for HDD are presented, which include two-degrees-of-freedom (TDOF) controller with multi-rate sampling, reference trajectory design not to excite higher order mechanical resonances, settling servo to compensate for tracking error near the target, phase stabilized design of feedback control to have better sensitivity, and multi-rate filter design to suppress disturbances above the Nyquist frequency.
A lot of applications of sensor networks require the positions of human and objects in indoor environments. There are some methods for this purpose. In this paper, we use received signal strength (RSS) to estimate the position for its simplicity. However, RSS varies substantially owing to fading, shadowing, multipath effects and so on. Attenuation coefficient varies according to indoor environment. For this reason, the attenuation coefficient is determined before estimating the position of a target node in the conventional method. We propose a position estimation method that estimates a target node position and an attenuation coefficient simultaneously. Thus, the proposed method has no need to estimate the attenuation coefficient in the target environment preliminarily. To evaluate the position estimation accuracy of the proposed method, we developed the prototype system and experimented in our office. Multiple fixed target nodes were set in the target environments. The experiments show that the proposed method has about the same accuracy as the conventional one without preliminary data collection for attenuation coefficient estimation.
Health maintenance and improvement of humans, artifacts, and nature are pressing requirements considering the problems human beings have faced. In this article, the health management technology is proposed by centering cause-effect structure. The important aspect of the technology is evolvement through human-machine collaboration in response to changes of target systems. One of the reasons why the cause-effect structure is centered in the technology is its feature of transparency to humans by instinct point of view. The notion has been spreaded over wide application areas such as quality control, energy management, and healthcare. Some experiments were conducted to prove effectiveness of the technology in the article.
A new compact automated DNA detection system Genelyzer™ has been developed. After injecting a sample solution into a cassette with a built-in electrochemical DNA chip, processes from hybridization reaction to detection and analysis are all operated fully automatically. In order to detect a sample DNA, electrical currents from electrodes due to an oxidization reaction of electrochemically active intercalator molecules bound to hybridized DNAs are detected. The intercalator is supplied as a reagent solution by a fluid supply unit of the system. The feasibility test proved that the simultaneous typing of six single nucleotide polymorphisms (SNPs) associated with a rheumatoid arthritis (RA) was carried out within two hours and that all the results were consistent with those by conventional typing methods. It is expected that this system opens a new way to a DNA testing such as a test for infectious diseases, a personalized medicine, a food inspection, a forensic application and any other applications.