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A solar tracker is an electronic device consisting of several electrical and mechanical elements, which functions to control the solar panels so that they always follow the sun’s position at a perpendicular angle so that the energy produced by the solar panels can be maximized. One application is used as a source of energy for lamps in street lighting. However, in general, they still use conventional street lighting. Therefore, this research discusses the performance analysis of the dual-axis solar tracker based on a fuzzy PID controller on street lighting. In this dual-axis solar tracker system research, the fuzzy logic control uses 5 membership functions. The system response performance index with fuzzy and fuzzy PID control has different values. The PV tracker has a performance increase of 48.3% greater than the fixed panel.

The structure and principles of the development of fuzzy PID controllers are analyzed. A simple four-step method for tuning a fuzzy PID controller is proposed. A controller has been developed that provides typical transient requirements using a small number of control rules. Proposed methodology confirmed examples of digital modeling.

In this paper, we present and make comparison between the MFO and PSO methods to tuning fractional order fuzzy PID controller for a DC-DC Boost Converter where MFO and PSO algorithms used to find the optimal parameters of FOFPID controller for A DC-DC Boost Converter. The results showed that Moth-flame optimization algorithm with fractional order fuzzy PID controller give better performance compared with fractional order fuzzy PID controller with PSO and fuzzy PID controllers. Finally, The Moth-flame optimization (MFO) method is helpful to choose the best parameters of Fractional Order Fuzzy PID Controller for A DC-DC Boost Converter.

Minidrones are widely used as they are not only fast quadcopters with high manoeuvrability but also excellent research platforms for indoor usage. In this study, we provide the design and deployment of the PI-PD and Fuzzy PI-PD (FPI-PD) structures to solve position control problem of the Parrot Mambo Minidrone. In this context, we derive nonlinear mathematical model of Parrot Mambo Minidrone to obtain the control models of the minidrone. Then, via the control models, firstly PI-PD control systems are designed for the altitude and position control systems. Then, to handle the coupled nonlinearities, FPI-PD controllers are designed and employed in the position control loop of minidrone. The presented comparative real-world experiment results clearly show that the proposed control systems outperform the built-in ones. Moreover, the results show that the performance of FPI-PD is better than the built-in PD and designed PI-PD control systems.

In this paper, we analyze and present a general structure of fuzzy PID controller of Takagi-Sugeno (TS) type having two and three inputs. We show that while three-input fuzzy PID controller gains have an one-to-one relation with the conventional controller gains, this relationship is not directly evident in the case of two-input fuzzy PID controllers. The tuning of input/output scaling parameters of the presented fuzzy PID controllers is addressed based on the structure of conventional PID controllers.

In this paper, a design of fractional order fuzzy PID controller is presented for position-tracking control of an electro-hydraulic rotary actuator (EHRA) which uses a hydraulic rotary as the end-effector under different working conditions. The proposed controller combines between fractional order PID (FOPID) controller and an intelligent fuzzy rule. In detail, fractional order PID controller with two additional parameters changes the integer order of integral and derivative functions in conventional PID to non-integer order which help to improve tracking, robustness and stability of control performance. A fuzzy logic control system is designed to optimize the parameters of FOPID in term of variant requirements. To verify the proposed controller, simulations by using co-simulation between AMESim and Matlab are carried out. Furthermore, a comparative study with other controllers has been done to demonstrate the effectiveness of the proposed approach.

In this work, the parallel combination of PID and fuzzy PID controllers entitled as Intelligent fuzzy PID (IFPID) controller is validated as a superior controller over PID and fuzzy PID controllers for two area thermal power system as Automatic Generation Control (AGC). The parameters of controllers implemented in the power system are tuned by Ant Lion Optimizer (ALO). The validation of novelty of controller and algorithm are graded by concerning the response parameters such as undershoot, overshoot, and settling time of deviations (frequency and power). A load disturbance of 0.01 p.u. is implemented in area-1 to demonstrate the whole experiment. Finally, IFPID controller optimized by ALO algorithm contributes better performance over PID and fuzzy PID controllers as AGC.

One of a popular laboratory equipment used to study nonlinear dynamics and open-loop unstable system is ball and beam mechanism. The unstable behavior of ball and beam can be observed where the ball will keeps moving on a beam when the beam is tilted. Many controllers had been designed to achieve stability for this mechanism including a PID controller. Lately, the fuzzy incorporation in the system to facilitate PID tuning is basically simplifying the design problems especially in PID tuning. This research on the other hand, will propose a modified structure to a general fuzzy PID so that specific design requirements can be realized with ease. A reference model was introduced at the set point which will bring information about the desired output specifications. Hence, different specifications can be expected from a different reference model. This paper presents the results obtained from few first-order model references.

The paper presents a method to build an Adaptive Fuzzy PID Controller for a three-phase PMSM with a Field Oriented Control (FOC). However, there are many different approaches to design and code the program. This is dependent on the systems hardware. The Texas Instrument DSP is normally used in conjunction with the CCS environment which requires C languages skill. To simplify the process and reduce coding time, this paper recommends a new method to design the algorithm based on the Embedded Coder and the Fuzzy Logic Designer Toolbox in MATLAB. The results were verified on the platform with the F28069 Control Card and loaded conditions.

Aiming at the shortcomings of low stiffness of pneumatic system and low flexibility of hydraulic system, a new type of pneumatic-hydraulic upper limb rehabilitation training system is proposed in this paper. The system overcomes the shortcomings of pneumatic system and hydraulic system by adjusting the damping of the system, which is changed by the opening area of hydraulic valve. In order to verify the feasibility of the proposed method, simulation studies are carried out under different damping. And the simulation results show that the system achieves good posture control performance under higher damping and fuzzy PID controller.

Improved driver ride quality is the sole purpose of the designed active quarter car model. In this paper an active quarter car with driver model is simulated using MATLAB/Simulink and the performance of the controllers are studied. To reduce the Driver Body Acceleration (DBA) and thus increasing the ride quality a Fuzzy Tuned PID Controller (FPID) is designed. The performance of this Controller is analyzed against the performance of Fuzzy Logic Controller (FLC), PID and Passive System for the 3 Degree of Freedom (3DOF) active quarter car driver model. The system is subjected to road disturbance such as dual bump, sinusoidal bump and random road which is designed as per ISO 8606 standards. It is proved that the FPID increases the ride quality and reduces the vibration in comparison to the FLC, PID and Passive system from the performance analysis of these controllers.

This paper analyses the performance of Quadruple tank system with different controllers. The minimum and non-minimum phase behavior of the quadruple tank is controlled by the selection of flow ratio of the system. Change in phase from minimum to non-minimum affects the system performance and vice versa. This paper mainly focuses on the design of optimal controller to improve the system performance. An experimental study on different controllers has been implemented and the result is analyzed. The system performance with a PID controller, fuzzy PID controller and Model predictive controller are analyzed. The simulation result shows that the MPC controller provides the optimal solution for a quadruple tank system.

In this work a parallel fuzzy PID controller is proposed for enhancing small signal stability of variable solar integrated power system. The controller parameters are tuned by DE-GWO technique. With increase in solar penetration the system oscillations are found to be more aggravated subject to sudden variation in solar output. Time domain simulation has been performed with detail eigen value analysis to justify the effectiveness of controller. The system response predict that proposed controller can damp system oscillations much heavily in contrast to single fuzzy PID controller optimized by DE and GWO techniques.

Changes of the external environment and external loads can cause the change of the output power of photovoltaic(PV) cells. In order to improve the efficiency of photovoltaic cells, photovoltaic cells must be operated near the maximum power point. The fuzzy PID controller is designed to achieve maximum power tracking of the photovoltaic cells. The simulation models of output power of photovoltaic cells based on perturbation and observation and fuzzy PID control are built. The simulation results show that the fuzzy PID control has the faster response, better stability and smaller overshoot.

The hydrostatic driving tracked tractor was widely applied in the modern agriculture for its high adaptability to the working environment. By analyzing the motion of hydrostatic driving tracked tractor and combing the model of tracked tractor and the hydrostatic driving pump-motor with the rotational velocity adjustment control scheme, the paper design the control system of hydrostatic driving tracked tractor. In response to the motion of steering and straight-line driving, taking the mass-center velocity and rotational angular velocity of the tracked tractor as the expected inputs, meanwhile, using Matlab/Simulink toolbox to build and verify the hydrostatic driving tracked tractor system. The simulated result shows that, under the control of fuzzy PID controller, the hydrostatic driving tracked tractor was able to steer and drive along the straight line while reached the target of self-walking.

This paper presents a solution to the problem of stabilizing a given Takagi-Sugeno (TS) Fuzzy model by PID controllers using the particle swarm optimization (PSO). It is based on searching the best parameters kp, ki and kd existing in the stability region. So, a new algorithm is proposed. this algorithm relies on the use of a new objective function taking into account both the performance indices and the error signal. The advantages of this approach were discussed through simulations on a numerical example.

To ameliorate living conditions of people suffering from limb amputations, artificial prothesis are developed to follow Human body locomotion. This paper aims to depict and evaluate the dynamic modeling and control strategy for an Active Knee Prosthesis (APK). As a first step, the motion equations governing the APK are derived using Euler-Lagrange method. Then, human healthy leg data is used to build a knowledge based fuzzy inference system (FIS) to control the dynamic motions of the APK. An adaptive fuzzy-PID controller is designed to generate desired angles deduced from healthy leg. A conclusion finished the paper.

This article presents load frequency control of multi area interconnected microgrid power system. A Fuzzy proportional-integral-derivative (Fuzzy PID) controller is proposed as frequency controller for the system. The present work involves bio-inspired grasshopper optimization algorithm (GOA) for tuning of controller gains. The attainment of proposed Fuzzy PID controller is accounted with that of proportional- integral–derivative (PID) controller. The comparison of system performance is also carried out with and without energy storage system in microgrids. The system performance is also studied with system parameters change and random step load perturbations (SLPs).

This paper proposes an effective control solution to achieve stabilizing control and tracking control with robustness against high valued disturbances in the area of Electromagnetic Levitation System (EMLS). EMLS is an open-loop unstable and nonlinear test bench with input and state types of nonlinearities presents in the current control mode. Fuzzy-PID controller is designed and implement based on ITAE performance criterion to achieve satisfactory transient as well as steady state performance from EMLS. Pre-filter structure is added to smooth the system performance as well as to reduce the transient overshoot problem. The simulation results and different integral errors like ISE, ITAE and ISTE are presented to validate the effectiveness of the proposed research work under different initial conditions, various trajectories and different disturbances.

The Indoor flights of UAV (Unmanned Aerial Vehicle) are susceptible to impacts of multiples obstacles and walls. The most basic controller that a drone requires in order to achieve indoor flight, is a controller that can maintain the drone flying in the same site, this is called hovering control. This paper presents a fuzzy PID controller for hovering. The control system to modify the gains of the parameters of the PID controllers in the x and y axes as a function of position and error in each axis, of a known environment. Flight tests were performed over an AR.Drone 2.0, comparing RMSE errors of hovering with classical PID and fuzzy PID under disturbances. The fuzzy PID controller reduced the average error from 11 cm to 8 cm in a 3 minutes test. This result is an improvement over previously published works.

Because the subway station has the characteristics of large area, wide space, complicated regional function and large passenger mobility between regions, the controlled objects in the subway station environment are characterized by time-varying, randomness, non-linearity and large lag. As the PID control parameters are fixed throughout the control, for the highly complex subway station environment, the PID control becomes helpless, it is difficult to achieve the best. There fore, a fuzzy PID control method is proposed. This method combines the fuzzy control and the PID control technology to establish the fuzzy PID controller, which can effectively realize the reasonable control of the ambient temperature of the subway station.

In this paper we propose an optimal slip ratio control using a current sensing method. The optimal slip ratio control consists of a Fuzzy PID controller using a current sensor and IMU sensor. The slip of mobile robot is caused by the external environment factors and dynamic characteristics of the mobile robot. The slip caused by several factors have a significant impact on the efficiency of the mobile robot. The proposed Fuzzy Slip control focuses on the reduction of this slip problems. FSC (Fuzzy Slip Control) is designed using a current sensor which is included in the ASS (Anti Slip System) by combining PI. To verify the control performance, a field experiment is performed using the mobile robot in outdoors.

This paper focuses on design a adaptive fuzzy PID controller which applied in the VAV air-conditioning system. The task is to control the temperature of supply air and the return air close to their respective targets. This paper adopt parameter auto-tuning technique that could adjust the PID parameters on real time to ensure good quality of control system. The control system has two respective close loops. In the first circuit, the valve of the cooling coil was adjusted to control the temperature of supply air. In the second one, the frequency is modulated to control the rotate speed of the electromotor, up to the temperature of return air. The supply air temperature and the return air temperature (indoor temperature) are controlled online by fuzzy PID controller. The test result shows that the design of fuzzy adaptive PID controller is reasonable and the effect of fuzzy PID control is well.

During the Vision-based Unmanned Aerial Vehicle (UAV) tracking mobile vehicle, the speed of vehicle is different and variation with the time, so the conventional PID controller with single fixed parameters is difficult to track the mobile vehicle precisely. For the question, designing the Fuzzy PID controller, which can adjust the parameters of the PID controller according to different conditions, is necessary. In this paper, describing its characteristics and the rules of adjusting the parameters, it can meet the requirement of tracking the mobile vehicle precisely. The simulation results demonstrate that, under different vehicle speed and variation with time, the Fuzzy PID controller response is fast, small overshoot, high robustness and high tracking accuracy.

An air resistance test system is established for the plate fm heat exchanger. A fuzzy PID controller is proposed to realize the quick, accurate, and efficient control of air volume for the plate fin heat exchanger. The simulation results show that the proposed fuzzy PID controller not only can improve the control quality of system, but also the system has better dynamic tracking characteristics of the load change.

Fuzzy control has lots of advantages compared with traditional PID control. Good performance can be obtained by fuzzy control without mathematic model of control object. Meanwhile, fuzzy controller is equipped with high stability and robustness. The characteristics of traditional PID control and fuzzy controls were integrated as fuzzy PID control, greatly enhancing performance of the controller. The work discussed the design of fuzzy parameter self-tuning PID controller. The performance of the controller was compared with traditional PID controller mainly from the robustness. Results indicated robustness of fuzzy PID controller is better after comparison.

Different control methods are preowned in dc-dc converters to control the dynamic and output characteristics of the response. In this paper some of the soft computing techniques are used to analyze the performance of buck converter using Mathematical laboratory.

A self-tuning fuzzy PID controller (STFPID) is developed to enhance the performance of an inverted pendulum in crane mode operation. Efficacy of STFPID is justified against the performance of a conventional PID and fuzzy PID controller (FPID). Inverted pendulum is a typical example of a nonlinear system and its free hanging mode is a well accepted form to realize a usual crane operation. Here, STFPID is designed with a continuous variation of its output scaling factor depending on the latest process status. Simulation study along with real time experimentation justifies the superiority of STFPID in comparison with conventional PID and FPID. Moreover, performance of STFPID is found to be more robust in comparison with conventional and fuzzy PID controllers.

This paper presents the performance evaluation of an active vibration technique in suppressing human hand tremor. A PID integrated with fuzzy logic controller is proposed to control a linear electromagnet actuator and then applied onto a four Degree-of-Freedoms (DOFs) biodynamic model which emulate a Parkinson Disease (PD) hand. Heuristic method is employed in searching for appropriate parameters values for the proposed controller. Then, a comparative study between the performances of Fuzzy-PID controller and conventional PID controller tuned using Ziegler-Nichols method is done. The simulation study results demonstrates a comparable performance between Fuzzy-PID controller and conventional PID controller. Fuzzy-PID controller was effectively attenuated about 96.77% of initial tremor magnitude while for the PID controller is about 89.37%.

The development status of the temperature control system of sealing machine is analyzed, the working principle of the seal and experiment are introduced. Currently, the heat output of sealing machine used by enterprise is consistent every move. Residual heat was repeated superimposed lead to the wreck of the package material. A new type of temperature control system based on fuzzy PID is designed which can output stable heat. Control system which is built in microcontroller was based on PROTEUS. The model of fuzzy PID controller which is established by using MATLAB to simulate the heat output. The results indicated that the system has better performance with ideal rapid responsible heat output and load disturbances.

During cardiovascular and cerebrovascular interventional surgical procedure, the accuracy of guide wire advance is particularly important for the success rate and safety of surgery, a single PID controller can't adapt to the complex surgical situations, the performance of the system has much room for improvement. In this paper, a fuzzy PID control algorithm with guide wire feedback force was proposed. According to the various situations in surgical procedures, multiple PID controller were designed correspondingly. In the actual surgical procedure, according to the different feedback-force of guide wire, the controller switches between different sets of PID controllers in real time to achieve more excellent performance respectively under different circumstances. Experimental results show that the fuzzy PID controller with guide wire feedback force achieves more excellent performance than the classical PID controller. And the dynamic performance of master-slave control system is better, the following error is reduced, overshoot decreases, and surgical safety greatly increased.

Because of the strong couple of temperature and humidity in air handing unit (AHU), the control of AHU is more difficult. In this paper, the coupling effect of temperature and humidity in the AHU is analyzed. Fuzzy PID controller is used to control the temperature and humidity of the mixed air in the process of cooling and dehumidifying, heating, and possible humidifying, and also to compensate temperature drop caused by isenthalpic cooling humidification process. Simulation results show that the effect of the controller is remarkable.

Suitable controller is a significant part in speed governing system of gasoline engine. In this paper, an integral-separation fuzzy PID algorithm used in controller is proposed to enhance the static and dynamic characteristics of speed governing system. The designed controller in this paper, based on the mathematical model of speed governing system, was established by using MATLAB/Simulink as the platform to simulate the process of gasoline engine starting and load mutating. The simulation results indicate that integral-separation fuzzy PID controller is better than traditional PID controller because it can obviously improve the speed adjusting characteristic of the gasoline engine in full operating conditions.

BLSRM (Bearingless Switched Reluctance Motor) is a nonlinear, strong coupling and multi-variable system. The convertional control method is vulnerable to uncertain factors such as the load disturbance and satellite parameters' change. It is difficult to obtain a satisfactory control effect. Basing on a novel 8/10 BLSRM, whose suspending force control is separated with the torque control, this paper presents a novel suspending force control scheme. Conventional PID controllers in BLSRM radial force control must set initial parameters in advance according to engineers' knowledge, which will be unchanged during regulation. In order to solve this problem, adaptive fuzzy logic is applied to convertional PID controller for parameters self-tuning in this paper. Both fuzzy and parameters of PID controller are self-tuning on-line, which improve the performance of controller. Finally, simulation and experimental results show the performance of the proposed method.

This paper presents investigations into the development of an assistive device for elderly mobility. An exoskeleton is designed as an assistive device, to enhance the lower extremity and provide supporting torque to augment the torque of hip and knee during the walking cycle. A humanoid and actuated exoskeleton frame are designed in solid works and then imported to Visual Nastran 4D virtual environment. Fuzzy PID Control algorithm uses to control the actuated exoskeleton. Simulated walking tasks are performed with a humanoid wearing the exoskeleton. It is assumed that the humanoid representing an elderly person, is able to provide 60% of the whole torque required to complete the gait cycle, and the assistive device providing 40% of the overall torque.

In this paper, the real time tracking performance of the fuzzy PID controller has been evaluated on nonlinear 3-DOF helicopter system. Quanser 3-DOF helicopter system has been utilized as experimental setup. Three separate fuzzy PID controller have been employed so as to control three state of the system. The dynamics of the system has been altered via counterweight in order to examine the performances of the both controller for parametric uncertainty in system parameter. The results reveal that the fuzzy PID controller leads to a good tracking performance and has better parametric uncertainty rejection capability than LQR.

A fuzzy controller is established for the wire feeder of the invasive vascular interventional surgery robot in this paper. First of all, the mechanism of the wire feeder is introduced, and the axial motion is analyzed. Second, the dynamic model of the wire feeder is established. Next, the fuzzy PID controller is established to improve the positional accuracy and dynamic performance. At last, the controller is simulated by MATLAB. Comparing with normal PID controller, the fuzzy PID controller has better dynamic properties and anti-jamming ability.