• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.790-794
• /
• 1989

A novel control method involving an automatic tuning of digital PID controller parameters has been developed for better regulation of DO (dissolved oxygen) concentration in batch fermentation processes. Heuristic reasoning allows the PID controller to reach improved tuning decisions based upon the supervision of certain control performance indices in the same cognitive manner as in an expert control.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.27-34
• /
• 2017

Design of an intelligent controller for efficient control in smart building is one of the effective technologies to reduce energy consumption by reducing response time with keeping comfortable level for inhabitants. In this paper, we focus on how to find major parameters in order to enhance the ability of HVAC(heating, ventilation, air conditioning) PID controller. For the purpose of that, we use machine learning technologies for tuning HVAC devices. We show the simulation results to illustrate the behavioral relation of whole system and each control parameter while learning process.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1244-1254
• /
• 2015

This paper proposes a new method for tuning a linear quadratic - proportional integral derivative controller for second order systems to simultaneously meet the time and frequency domain design specifications. The suitable loop-shape of the controlled system and the desired step response are considered as specifications in the time and frequency domains, respectively. The weighting factors, Q and R of the LQ controller are determined by the algebraic Riccati equation with respect to the limiting behavior and target function matching. Numerical examples show the effectiveness of the proposed LQ-PID tuning method

• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.624-636
• /
• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2648-2650
• /
• 2000

The PID tuning algorithm which can be applied generally to processes with varies dynamic characteristics is proposed by Wang[7]. However, it can be applied well to process model without zeros and with $\angle$G(jw)=-${\pi}$/2 and -${\pi}$ point in Nyquist curve, but it gives unsatisfactory tuning performance for processes with zeros and without $\angle$G(jW)=-${\pi}$/2 and -${\pi}$ in Nyquist curve. In this paper, the method which improve it using Pade reduction method is proposed. Satisfactory responses can be expected for processes with various dynamics, including those with low or high order, small or large dead time, monotonic or oscillatory responses. Simulation examples are given to show the effectiveness and flexibility of the controller in handling processes of different characteristics.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.67.1-67
• /
• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• Journal of Advanced Marine Engineering and Technology
• /
• v.33 no.8
• /
• pp.1268-1274
• /
• 2009

Various evaluation systems using simulators have been adopted widely for the purpose of training and examination, including marine engineering education area. This paper suggests a PC based evaluation scoring system for simulators where the operation ability of machineries and background knowledges of trainees or examinees are able to be assessed relatively. The scores are based on the 100 point resulted from their responses for a given evaluation scenario under a PID tuning simulation. The mistakes they make during the operation time are integrated firstly to get error sum, and the error sum is transformed secondly to 100 point score according to a formula where the knowledge level of examinee's groups can be compensated and considered reasonably. The implementation result of evaluation system for the given control loop is described and analyzed to show the effectiveness of the suggested configuration as an evaluation tool.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.1
• /
• pp.78-86
• /
• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.05a
• /
• pp.348-354
• /
• 1999

In recent years, a PID controller has been used as a major control method in real control processes. This controller requires a determination of PID control gains. But it is difficult to select the best gains theoretically. Thus there have been many approaches to determine them empirically Most of them are based on experience and knowledge. In this paper, we proposed a tuning method of the PID Parameters by using neural network. To show effectiveness of the proposed method, the simulation of DC motor and one link manipulator position control is carried out.

• Journal of Industrial Technology
• /
• v.20 no.B
• /
• pp.155-162
• /
• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.