Mukhtar Fatihu Hamza

Learn More
Finding the appropriate values of parameters and structure of type-2 fuzzy logic systems is a difficult and complex task. Many types of meta-heuristic algorithms have been used to find the complex structure and appropriate parameter values of the type-2 fuzzy systems and more recently hybrid meta-heuristic algorithms. In this paper, we review recent(More)
Temperature control is desirable in heat exchanger system due to fact that chemical processing plants requires certain level of temperature for a given for a particular processing. This research aims at the development of a PID controller for outlet temperature control of a heat exchanger system. The proposed controller was developed based on MIGO(More)
This paper presents the design of an optimized Interval Type 2 Fuzzy Proportional Derivative Controller (IT2F-PDC) in cascade form for Rotary<lb>Inverted Pendulum (RIP) system. The parameters of the IT2F-PDC are optimised by using Genetic Algorithm (GA) and Particle Swarm<lb>Optimization (PSO). The goal is to balance the pendulum in upright unstable(More)
This article presents an alternative approach useful for medical practitioners who wish to detect malaria and accurately identify the level of severity. Malaria classifiers are usually based on feed forward neural networks. In this study, the proposed classifier is developed based on the Jordan-Elman neural networks. Its performance is evaluated using a(More)
A fuzzy PD controller in cascade form is proposed in the present study to deal with stability issue of Furuta pendulum. The Furuta pendulum which is widely known as Rotary inverted pendulum (RIP) is under-actuated mechanical system. This paper, described a development of nonlinear dynamical equations of the RIP system using Kane's method. The Simulink model(More)
Numerous types of hybridizations between type 2 fuzzy logic system (T2FLS) and sliding mode control (SMC) have been proposed to construct an intelligent and robust controller that departs from the drawbacks of SMC and T2FLS. Recently, these hybridizations have been extended to the hybrid structures that are composed of type 2 fuzzy neural network (T2FNN)(More)
The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fuzzy Membership Function (MF). Numerous experimental investigations have shown the superiority of IT2FLC over T1FLC, particularly in high level(More)
  • 1