Robust Tuning of PID Controller With Disturbance Rejection Using Bacterial Foraging Based Optimization

نویسندگان

  • Dong Hwa Kim
  • Jae Hoon Cho
چکیده

In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on ∞ H are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection

The social foraging behavior of Escherichia coli (E. Coli) bacteria has been used to solve optimization problems. This chapter proposes a hybrid approach involving genetic algorithm (GA) and bacterial foraging (BF) algorithm for function optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mu...

متن کامل

A Fast, Easily Tuned, Siso, Model Predictive Controller

It is commonly believed that for SISO systems, well tuned PID controllers work as well as model-based controllers and that PID controllers are more robust to model errors. In this paper we present a novel offset-free constrained LQ controller for SISO systems, which is implemented in an efficient way so that the total controller execution time is similar to that of a PID. The proposed controlle...

متن کامل

Control of nonlinear systems using a hybrid APSO-BFO algorithm: An optimum design of PID controller

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

متن کامل

A Unified IMC based PI/PID Controller Tuning Approach for Time Delay Processes

This paper proposes a new PI/PID controller tuning method within filtered Smith predictor (FSP) configuration in order to deal with various types of time delay processes including stable, unstable and integrating delay dominant and slow dynamic processes. The proposed PI/PID controller is designed based on the IMC principle and is tuned using a new constraint and without requiring any approxima...

متن کامل

Control of nonlinear systems using a hybrid APSO-BFO algorithm: An optimum design of PID controller

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004