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This research concerned about an online learning algorithm of the group method of data handling based proportional-integral-derivative (GMDH-PID) controller that is effective for nonlinear systems. Although a lot of PID controllers have been mainly used in industrial systems, it is difficult to maintain a desired control performance only by a PID controller with fixed control parameters due to system...
Industrial equipment, such as bulldozers, excavators, and cranes, requires human operation. Construction machines with better operability are necessary in order to improve productivity. The evaluation of such operational equipment is performed in order to obtain better operability, at the design stage, by sensory evaluation from a specific evaluator. Therefore, the design and evaluation of operational...
This study presents the practical results concerning model-based development educational practices implemented by Hiroshima University and Mazda Motor Corporation, an automobile manufacturer, and the consequent educational effects. In recent years, diversification and complexity of product structures have become prominent. Simultaneously, there is an increasing demand for short-period development...
In process industries, PID control has been applied to control objects such as chemical plants. A cascade control system is applied in order to improve control performance by using several feedback loops. However, it is complicated to design a cascade control system because this control system includes plural controllers. In this paper, a designed scheme of data-oriented cascade control system without...
The idea of controller performance assessment is becoming very important in the process control area. One of the main performance monitoring index is based on the minimum variance control benchmark proposed by Harris. However, the low value of this index means only low performance of the controller. So, it is difficult to tune the controlled parameters based on this index. This paper considers the...
PID controllers have been widely employed in real processes, and PID parameters strongly affect the control performance. Therefore, lots of schemes for tuning PID parameters have been proposed. Although fixed PID controllers are applied mainly, it is impossible to maintain good control performance for time-variant systems. In addition, most of the controlled objectives are multi-input multi-output...
A lot of Industrial equipments need operations. Equipments such as excavators and cranes are evaluated by sensory evaluations of the specific evaluator at the design stage. Designs and evaluations of operated equipments depend on subjective evaluations. However, subjective evaluations require the skill of evaluation or a lot of sample data. In this paper, a quantitative evaluation is considered about...
This paper presents a discrete-time adaptive output feedback control system design scheme based on the almost strictly positive real (ASPR) of controlled systems with a feedforward input. The reference signal is used to calculate the feedforward input. It is well-known that a stable adaptive output feedback control system can be designed based on ASPR conditions. However, most realistic systems do...
In industrial control processes, it requires fast response for transient state and for steady state it is necessary to maintain user-specified control performance to achieve desired productivity. Moreover, the Proportional-Integral-Derivative(PID) control algorithm is widely used in industrial control processes. Hence, in this paper an algorithm to tune PID control parameters that can improve control...
This study proposes a performance-driven control method that performs a “control performance assessment” and a “control system design” from a set of closed-loop data. The method evaluates control performance based on the minimum variance control index from closed-loop data. It also calculates control parameters that improve the control performance from the same closed-loop data by using the fictitious...
In order to design a controller for the nonlinear system, the model-based design method that makes a mathematical model for the system has been proposed. However, the requirement for the accuracy of the model to get a desired control performance is high. Therefore, a data-oriented control method was proposed to prevent making mathematic model for the system. Still, in some cases, a desired control...
In process industries, PID control has been applied to controlled objects such as chemical plants. A cascade control system is applied in order to improve control performance by using several feedback loops. However, it is complicated to design a cascade control system because this control system includes plural controllers. In this paper, a design scheme of data-oriented cascade control system without...
Proportional-integral-derivative (PID) control algorithm is playing an important role in industrial control process. However, for nonlinear control objects, it is difficult to obtain the desired control performance by using a typical PID controller. Therefore, some intelligent PID controllers are proposed and one of them is a PID controller with some cerebellar model articulation controllers (CMACs)...
Some design schemes of data-driven control methods which called model free methods have been proposed in nearly a decade. Fictitious Reference Iterative Tuning (FRIT) method which is one of the data-driven control has good advantages. This method can calculate the control parameters by the operation data which is under closed loop control. This paper provides the PID parameter calculation based on...
The construction field is increasingly adopting automation and manpower-saving technologies. However, automating all types of construction machinery is difficult because some operations require human skill and judgment-that is, professional skills-for realizing optimal work efficiency. However, the lack of competent professionals because of the decreasing and aging population in Japan is an emerging...
In this study, a learning algorithm for a data-driven proportional-integral-derivative (DD-PID) controller that uses a database for tuning control parameters is considered. PID controllers are still used in many process systems. However, if systems exhibit nonlinearity, PID controllers with fixed PID parameters cannot achieve a desired control performance when a system's equilibrium points are changed...
Most methods to compute PID parameters are based on system models. The model should describe the system properties accurately. In order to construct a highly accurate model, it is necessary to identify system parameters using input/output data so that it satisfies the richness condition of input/output data. However, it is not suitable to add such input signals to the real systems in industries. Therefore,...
This paper investigates finite-time horizon dynamic games for a class of nonlinear stochastic systems with multiple players. First, the necessary conditions for the existence of an open-loop Nash equilibrium are established using the stochastic maximum principle. Such conditions can be represented as the solvability conditions of cross-coupled forward-backward stochastic differential equations (CFBSDEs)...
Proportional-integral-derivative (PID) control schemes have been widely used in most industrial control systems. However, it is difficult to determine a suitable set of PID gains because most industrial systems have nonlinearity. On the other hands, the cerebellar model articulation controller (CMAC) classified as neural networks has been proposed, and design scheme of an intelligent PID controller...
PID control schemes have been widely used in most process industries. Since the control performance strongly depends on PID parameters, it is important to suitably choose a set of these parameters. Especially, it is difficult to determine these parameters in the case where the time-delay is unknown and/or large. On the other hand, it is well-known that the generalized predictive control(GPC) design...
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