Hasan Alli

Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system

The modelling, numerical simulation and intelligent control of an expert HVAC (heating, ventilating and air-conditioning) system having two different zones with variable flow-rate were performed by considering the ambient temperature in this study. The sub-models of the system were obtained by deriving heat transfer equations of heat loss of two zones by conduction and convection, cooling unit and fan. All models of the variable flow-rate HVAC system were generated by using MATLAB/SIMULINK, and proportional-integral-derivative (PID) parameters were obtained by using Fuzzy sets. For comfortable of people the temperatures of the two different zones were decreased to 5^oC from the ambient temperature. The successful results were obtained by applying self-tuning proportional-integral-derivative (PID)-type fuzzy adaptive controller if comparing with the fuzzy PD-type and the classical PID controller. The obtained results were presented in a graphical form.

Predicting of fan speed for energy saving in HVAC system based on adaptive network based fuzzy inference system

In this paper, a HVAC (heating, ventilating and air-conditioning) system has two different zones was designed and fan motor speed to minimize energy consumption of the HVAC system was controlled by a conventional (proportional-integral-derivative) PID controller. The desired temperatures were realized by variable flow-rate by considering the ambient temperature for each zone. The control algorithm was transformed for a programmable logic controller (PLC). The realized system has been controlled by PLC used PID control algorithm. The input-output data set of the HVAC system were first stored and than these data sets were used to predict the fan motor speed based on adaptive network based fuzzy inference system (ANFIS). In simulations, root-mean-square (RMS) and the coefficient of multiple determinations (R2) as two performance measures were obtained to compare the predicted and actual values for model validation. All simulations have shown that the proposed method is more effective and controls the systems quite well.

Fuzzy adaptive control for the actuators position control and modeling of an expert system

In this paper, a heating, ventilating and air-conditioning (HVAC) system was designed and two different damper gap rates (actuators position) of the HVAC system were controlled by a conventional PID (proportional-integral-derivative) controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. The required air flow was supplied by controlled of the dampers placed on the entrance ducts of indoor. Programmable Logic Controller (PLC) used PID control algorithm was utilized to control the system. This system has been controlled by a PLC based closed-loop controller. In this work, the realized system has been controlled by PLC used PID control algorithm. The optimal values of PID parameters were obtained by using Fuzzy sets. Fuzzy adaptive control has been performed to maximize the performance of the system. Efficiency of fuzzy adaptive control (FAC) developed method was successfully obtained.

The solutions of vibration control problems using artificial neural networks

Abstract This paper introduces an alternative method artificial neural networks (ANN) used to obtain numerical solutions of mathematical models of dynamic systems, represented by ordinary differential equations (ODEs) and partial differential equations (PDEs). The proposed trial solution of differential equations (DEs) consists of two parts: The initial and boundary conditions (BCs) should be satisfied by the first part. However, the second part is not affected from initial and BCs, but it only tries to satisfy DE. This part involves a feedforward ANN containing adjustable parameters (weight and bias). The proposed solution satisfying boundary and initial condition uses a feedforward ANN with one hidden layer varying the neuron number in the hidden layer according to complexity of the considered problem. The ANN having appropriate architecture has been trained with backpropagation algorithm using an adaptive learning rate to satisfy DE. Moreover, we have, first, developed the general formula for the numerical solutions of n th-order initial-value problems by using ANN. For numerical applications, the ODEs that are the mathematical models of linear and non-linear mass-damper-spring systems and the second- and fourth-order PDEs that are the mathematical models of the control of longitudinal vibrations of rods and lateral vibrations of beams have been considered. Finally, the responses of the controlled and non-controlled systems have been obtained. The obtained results have been graphically presented and some conclusion remarks are given.

Design and prototype of a six‐legged walking insect robot

Purpose – This paper seeks to develop a novel legged robot.Design/methodology/approach – First, the paper models the legged robot using 3D computer model by intelligent inspiration of biological principles. Then, based on this model, it develops the prototype of the legged robot.Findings – A novel motion mechanism is used and only two actuators are used for driving the system.Originality/value – The modelled legged robot is original in terms of the developed motion mechanism.

Kinematic and dynamic analysis of a hexapod walking-running-bounding gaits robot and control actions

Kinematic and dynamic analysis, and control actions of a hexapod robot were realized for walking, running and bounding gaits in this study. If biological inspiration can be used to build robots that deal robustly with complex environments, it should be possible to demonstrate that legged biorobots can function in natural environments. Firstly, we tried to report on theoretic work with a six legged robot designed to emulate spider behavior like walking, running and bounding. We demonstrated theoretically that it can successfully walk, run and bound like a spider over natural terrain. Secondly, limitations in its capability were evaluated, and many biologically based important improvements were obtained for future experimental work. Thirdly, the hexapod robot with bounding gait was controlled by proportional-derivative control algorithm and was carried out by using spring loaded inverted pendulum model. Consequently, the developed kinematic and dynamic methods, and control action method makes both the system control easy and the system performance is improved by decreasing the run time for each loop.

Computer simulation and dynamic modeling of a quadrupedal pronking gait robot with SLIP model

In this study, a quadrupedal pronking gait robot modeling was carried out with Spring Loaded Inverted Pendulum model in stance phase. This is achieved by solving a natural problem in which the main goal is to enable the robot to walk and run in a stable condition regardless of the environmental conditions. In order to solve this problem, dynamic model and control of a quadrupedal robot were realized for a pronking gait. The stance and flight phase dynamic structures were solved in a sequential closed loop to obtain the equation of motion for pronking gait. Spring Loaded Inverted Pendulum model was used as a dynamic model to simplify the simulation, dynamic locomotion and experimental works of the system, and also to simplify the pronking gait concept. The quadrupedal robot with pronking gait was controlled by proportional-derivative control algorithm. As a result, all computer simulations have shown that the proposed control actions and methods are more effective and make the system control quite easy and successful.

Motion mechanism concept and morphology of a single actuator tetrapod walking spider robot: the ROBOTURK SA‐2 Robot

Purpose – This study seeks to develop a novel eight‐legged robot. Additionally, this study defines design and control of an eight‐legged single actuator walking ROBOTURK SA‐2 spider robot based on the features of a creatural spider.Design/methodology/approach – First, the single actuator eight‐legged tetrapod walking spider robot was modeled on solid works and then the animation of the model was realized to ensure the accurate walking patterns and more stable walking. Based on this model, the novel prototype of the single actuator eight‐legged walking spider robot was constructed.Findings – A novel motion mechanism uses only one actuator for driving the system.Originality/value – The modeled single actuator eight‐legged robot is original in terms of the developed motion mechanism.

Dynamic simulation model of a biomimetic robotic fish with multi-joint propulsion mechanism

In this paper, a biomimetic carangiform robotic fish is analysed based on dynamic and kinematic models. The carangiform fish can swim with features like high mobility, fast swimming and changing direction suddenly. Because it has these amazing features, a carangiform swimmer is modelled. Dynamic and kinematic models are analytically obtained to design a biomimetic carangiform robotic fish. The designed robotic fish consists of two parts: an anterior rigid body and a flexible tail, which is modelled as a four-joint propulsion mechanism, and each joint is driven by a servo motor. The dynamic model is developed in the MATLAB/Simulink environment using a Lagrange function and the state-space model is performed to linearize the obtained model. Each joint is controlled with conventional PID controller in the simulation. Furthermore, a solid model of the robotic fish prototype is drawn in SolidWorks and transferred to the MATLAB/Simmechanics environment, and the motion of the robotic fish is simulated using joint angles. Finally, experimental studies and simulation results show that a carangiform motion for autonomous swimming is developed and verified using controlled joint angles.

Application of neural based fuzzy logic sliding mode control with moving sliding surface for the seismic isolation of a building with active tendon

In this study, neural based fuzzy sliding mode control algorithm is designed by putting advantageous specifications of sliding mode control and artificial intelligence techniques and applied to 8 storey sample building with active tendon. Performance of the designed controller is examined by applying acceleration data belonging to 6 earthquakes, each having different characteristics, as the external driving force. MATLAB software is used for numerical solutions, and the obtained results are compared in graphical form and presented in tables. Genetic algorithm is used for optimization process. Parametric uncertainities and time delay effects are considered. It is observed that performance of the controller is quite high and control force can be used practically. The obtained results also show that the controller provides quite successful control under earthquake effects having different characteristics.