This study emphasizes the use of type-2 fuzzy (T2-Fuzzy) to improve the adaptive proportional-integrative-derivative (PID) control in the lower extremities. Several problems were identified from previous studies and those were the slow achievement of the target angle and the presence of oscillation in the achievement of the target blade. The oscillation occurred as the consequence of deploying ...

This paper presents genetic algorithms (GAs) to perform the optimal design of an auto-tuning fuzzy proportional-integral-derivative (PID) controller and to determine the minimal number of fuzzy rules simultaneously. Different from PID controllers with fixed gains, the fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivati...

Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired tempe...

Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired tempe...

Objective of this paper is to design various controllers for a temperature process control. PID controller is the well known and most widely used in the industries. Internal Model Control (IMC) has become the leading form of advanced control in the process industry. Modified form of IMC-PID and Fuzzy PID Controllers are designed for First Order Plus Dead Time (FOPTD) process model. The comparat...

In this paper we have designed a DC motor whose speed can be controlled using PID controller. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to FUZZY LOGIC. First, the fuzzy logic controller is designed according to fuzzy rules so that the systems are fundamentally robust. There are 25 fuzzy rules for self-tuning of each parameter of PID ...

In this paper, we formulate an optimization problem of establishing a fuzzy neural network model (FNNM) for efficiently tuning PID controllers of various test plants. An existing indirect, two-stage approach used a dominant pole assignment method with P=198 to find the corresponding PID controllers. Consequently, an adaptive neuro-fuzzy inference system (ANFIS) is used to independently train th...

Industry applications mainly use linear PID algorithms might deliver an insufficient performance dealing with nonlinear operating systems. A fuzzy PID controller results in a nonlinear control surface which can be adjusted to a controlled plant by rule based modification, nonlinear membership function application and inference rule selection. The tuning process is one of the most difficult step...

According to the nonlinear and time-varying uncertainty characteristics of direct drive electrohydraulic servo control system, a self-tuning fuzzy PID control method with speed change integral and differential ahead optimizing operator is put forward by combining fuzzy inference and traditional PID control in this paper. The rule of fuzzy logic is designed, the membership function of the fuzzy ...

Considering complex factors of affecting ambient temperature in Aircraft cabin, and some shortages of traditional PID control like the parameters difficult to be tuned and control ineffective, this paper puts forward the intelligent PID algorithm that makes fuzzy logic method and neural network together, scheming out the fuzzy neural net PID controller. After the correction of the fuzzy inferen...