Buck Converter Output Voltage Control System Using Proportional Integral Differential Method on Solar Cell Battery Charging

This paper investigates the fuzzy control method for the linear switched reluctance motor (LSRM) drive system. Modeling of the LSRM is constructed based on the finite element method (FEM) environment Maxwell and the control system is analyzed by the co-simulation environment with Simplorer. Both the performance of the fuzzy proportional integral differential (PID) controller and the traditional PID controller are compared. The simulation results prove that the fuzzy PID controller yields faster rising time and smaller overshoot, compared with the traditional PID controller.

In the paper, the PV power supply control system is proposed to realize the uninterrupted power supply, including DC and AC supply. By the method of combining software with hardware, through the solar panel to the configured two pieces of battery could realize the function of fast and slow charging, and the supply battery is changed by testing the battery power to the load uninterrupted power supply. Moreover, when the output voltage of the solar panel is lower than the battery, the output voltage of solar panel is boosted by DC/DC circuit to make the solar panel at low pressures also to charge the battery, effectively solving the difficult solar energy in the weak power supply problem.

This paper proposes a microcontroller based single axis automatic solar panel tracking control method for keeping the solar panel approximately at right angle with the incident photon for the better performance and maximize the output power of the solar panel. The charge controller with the DC-DC boost converter is used along the automatic tracking system for further enhancing output power under variable insolation conditions and protecting the battery from being overcharged and over discharged condition. The Boost converter is used to overcome the lower output voltage of solar panel for not fulfilling the minimum charging voltage requirement of the battery thus more power extraction is possible from the solar panel to battery. The system includes a photovoltaic array, three LDRs sensor, a PWM controlled Boost converter, charge controller and sensor circuits. This paper discusses the low cost implementation of the whole system in the 8-bit microcontroller using the tools and techniques to generate optimized real time code in C for ATMega8 microcontroller which will demonstrate how maximization of power output is visible and efficient solution for increasing the efficiency of a solar system based on experimental results rather than on mathematical models.

This paper presents an optimal tuning of a proportional integral differential (PID) controller used to maintain glucose concentration at a desired set point. The PID controller synthesizes an appropriate feed rate profile for an E. coli fed-batch cultivation process. Mathematical models are developed based on dynamic mass balance equations for biomass, substrate, and product concentration of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation for bacterial phytase extracellular production. For model parameter identification and PID tuning, a hybrid metaheuristic technique—chaotic electromagnetic field optimization (CEFO)—is proposed. In the hybridization, a chaotic map is used for the generation of a new electromagnetic particle instead of the electromagnetic field optimization (EFO) search strategy. The CEFO combines the exploitation capability of the EFO algorithm and the exploration power of ten different chaotic maps. The comparison of the results with classical EFO shows the superior behaviour of the designed CEFO. An improvement of 30% of the objective function is achieved by applying CEFO. Based on the obtained mathematical models, 10 PID controllers are tuned. The simulation experiments show that the designed controllers are robust, resulting in a good control system performance. The closed-loop transient responses for the corresponding controllers are similar to the estimated models. The settling time of the control system based on the third PID controller for all estimated models is approximately 9 min and the overshoot is approximately 15%. The proposed CEFO algorithm can be considered an effective methodology for mathematical modelling and achievement of high quality and better performance of the designed closed-loop system for cultivation processes.

This article deals with the sensor-less control of a DC Motor via a SEPIC Converter-Full Bridge combination powered through solar panels. We simultaneously regulate, both, the output voltage of the SEPIC-converter to a value larger than the solar panel output voltage, and the shaft angular velocity, in any of the turning senses, so that it tracks a pre-specified constant reference. The main result of our proposed control scheme is an efficient linear controller obtained via Lyapunov. This controller is based on measurements of the converter currents and voltages, and the DC motor armature current. The control law is derived using an exact stabilization error dynamics model, from which a static linear passive feedback control law is derived. All values of the constant references are parameterized in terms of the equilibrium point of the multivariable system: the SEPIC converter desired output voltage, the solar panel output voltage at its Maximun Power Point (MPP), and the DC motor desired constant angular velocity. The switched control realization of the designed average continuous feedback control law is accomplished by means of a, discrete-valued, Pulse Width Modulation (PWM). Experimental results are presented demonstrating the viability of our proposal.

Objective To design the control system of a magnetic resonance image (MRI) navigated pneumatic surgical robot. Method The driven system of the robot was constructed by combining with pneumatically driven and ultrasonic motor. The cylinder position control loop was established based on proportion integration differentiation (PID) control. The mathematical model of the pneumatic servo system was established by system identification. The PID parameter tuning and the simulation of the system characteristics were conducted. The stability analysis was conducted using the Nyquist criterion, and the acupuncture accuracy and the magnetic compatibility of the robot were verified. Results The simulation results showed that the maximum steady-state error was about 0.4 mm and the maximum tracking error was less than 2 mm, indicating that the PID control system had high control precision and trajectory tracking ability. The error of the acupuncture accuracy test was 0.72 mm. The results of water-modeling experiments showed that the magnetic resonance images were clear indicating that the influence of the robot on the MRI images was small. Conclusions The results of imulation, acupuncture and water-modeling tests showed that the pneumatic robot system can meet the requirements of brachytherapy surgery. Key words: Magnetic resonance imaging; Surgical robot; Pneumatic control system; PID control

This paper investigates the fuzzy Proportion Integration Differentiation (PID) controller for uncertain networked control systems (UNCSs). By combining T-S fuzzy model with the fuzzy PID controller, the uncertain networked control systems under transmission delays and external disturbances are proposed in this letter. Moreover, the asymptotically stability condition about the uncertain networked control systems is presented in the form of Lyapunov function and linear matrix inequality. The applicability of the proposed PID controller gain for uncertain networked control system is numerically tasted for various system parameters.

The recent development of drones has aroused great concern at home and abroad. For civil industry and agricultural plant protection industry, it can provide safer and more stable flight and improve production efficiency. For the exploration industry, the application of UAV (Unmanned Aerial Vehicle) will reduce unnecessary casualties. In places where damage is serious, UAV will bring accurate on-site information and data more quickly. It can make drones to replace people in high-risk operations, scientific and technological agricultural development and survey more stable and safe; For the military industry, it can be applied to different combat environments to increase its stability. In recent years, although UAV combat and reconnaissance are not the mainstream combat methods, UAV has become or an indispensable part. Improving the stability of UAV will also increase the military combat capability, so UAV has good development prospects and economic benefits. Nowadays, PID (Proportion Integration Differentiation) control plays an indispensable role in quad-rotor UAV. How to use different types of PID control combined with existing intelligent technology to improve the stability of quad-rotor UAV is a hot issue in recent years. This paper summarizes the previous research results in this field, briefly describes the motion mechanism of four-rotor UAV, wind disturbance resistance mechanism, the action principle and contract between traditional PID control and fuzzy PID control, as well as the effect of intelligent algorithm on PID control addition, and puts forward suggestions for PID control algorithm of the future UAV.

This research paper is about implementing energy harvesting solutions to maximize the output voltage of solar panel and to harvest the waste energy from solar panel for low voltage application. As the range of applications for solar energy increases, the improved materials and methods used to harness this power source needs to be developed. Major influences on overall efficiency include solar cell efficiency, intensity of source radiation and storage technique. To circumvent this problem this technique is implemented by solar energy system independent on irradiance and temperature developed by using buck-boost converter. Fuzzy logic controller generate variable duty cycle depends on variable solar panel voltage. Generated duty cycle is applied to buck-boost converter on which output is depends which is used for low voltage application such as battery charging. The charge battery will be used for lightening the parking, staircase and quoridor etc.

This study seeks to determine the effects of partial shading on the power output of solar panels and to test the effectiveness of bypass diodes in minimizing these effects. The first part of the study focuses on determining the effect of partial shade on the energy output of a solar panel. The second part of this study is aimed at establishing the effect that partial shade has on solar panel power output. In this study, partial shade was found to reduce the amount of energy generated by solar panels when compared to the solar panel in fully exposed conditions. After conducting experiments and reviewing scholarly works, this study concludes that partial shading does decrease the power produced by the solar panels, thus reducing the amounts of energy produced. Moreover, this research establishes that bypass devices are effective in mitigating these effects, which can improve the performance of the solar panel arrays, increasing the overall efficiency of solar panel systems. This research may offer support for the creation of new solar panel technologies that are more effective and efficient and can better endure the effects of partial shading, ultimately resulting in a global adoption of solar energy as a workable and sustainable energy source.

Active queue management (AQM) can keep smaller queuing delay and higher throughput by purposefully dropping the packets at the intermediate routers. Comparing with RED algorithm, although the PID (proportional-integral-differential) controller for AQM improves the stability. It is no systematic method in selecting a group of parameters for these controllers to guarantee the transient performance, and the case is much worse especially when the network parameters are time-varying. We use generalized predictive control to propose a predictive PID (PPID) controller for AQM router supporting TCP with slightly modified ECN to improve the robustness and transient performance of the PID controller. The simulation results show that the integrated performance of the controller is obviously superior to those of PID controller.

Solar panels often suffer from dust accumulation, significantly reducing their output, especially in desert regions where many of the world's largest solar plants are located. Here, an autonomous dust removal system for solar panels, powered by a wind-driven rotary electret generator is proposed. The generator applies a high voltage between one solar panel's output electrode and an upper mesh electrode to generate a strong electrostatic field. It is discovered that dust particles on the insulative glass cover of the panel can be charged under the high electrical field, assisted by adsorbed water, even in low-humidity environments. The charged particles are subsequently repelled from the solar panel with the significant Coulomb force. Two panels covered with sand dust are cleaned in only 6.6min by a 15cm diameter rotary electret generator at 1.6ms-1 wind speed. Experimental results manifest that the system can work effectively in a wide range of environmental conditions, and doesn't impact the panel performance for long-term operation. This autonomous system, with its high dust removal efficiency, simplicity, and low cost, holds great potential in practical applications.

Fuzzy controller design of micro-unmanned helicopter relying on improved genetic optimization algorithm

The turret system is a precision mechanical system capable of carrying mission equipment to move in both azimuth and elevation degrees of freedom. The servo control of the turret usually adopts proportion-integration-differentiation (PID) control, However, when the turret perform target tracking or shooting tasks, it faces various impact responses such as vibration impact, center of mass change, elastic deformation, etc. The PID control method with fixed parameters cannot handle these unknown or unpredictable effects well. So, the combination of PID control and fuzzy reasoning decision is proposed to establish the dynamic fuzzy adaptive adjustment rules of PID parameters and build an adaptive fuzzy PID (FPID) controller to suppress external interference. The turret servo control models are given out first, then the fuzzy adjustment rules for PID parameters based on tracking error and error change rate are provided. Finally, to verify the superiority of the FPID algorithm over the PID algorithm, a comparative analysis was conducted on the target single maneuver with and without considering external influences. The simulation results show that the FPID can suppress external interference and FPID has higher accuracy than PID, especially in the case of target maneuvering and external response, its tracking error can be reduced by about 80%. This method can be used for the servo control of the turret system to improve the servo accuracy of the turret during the target tracking process.

PurposeThis study aims to realize the constant force grinding of automobile wheel hub.Design/methodology/approachA force control strategy of backstepping + proportion integration differentiation (PID) is proposed. The grinding end effector is installed on the flange of the robot. The robot controls the position and posture of the grinding end actuator and the grinding end actuator controls the grinding force output. First, the modeling and analysis of the grinding end effector are carried out, and then the backstepping + PID method is adopted to control the grinding end effector to track the expected grinding force. Finally, the feasibility of the proposed method is verified by simulation and experiment.FindingsThe simulation and experimental results show that the backstepping + PID strategy can track the expected force quickly, and improve the dynamic response performance of the system and the quality of grinding and polishing of automobile wheel hub.Research limitations/implicationsThe mathematical model is based on the pneumatic system and ideal gas, and ignores the influence of friction in the working process of the cylinder, so the mathematical model proposed in this study has certain limitations. A new control strategy is proposed, which is not only used to control the grinding force of automobile wheels, but also promotes the development of industrial control.Social implicationsThe automatic constant force grinding of automobile wheel hub is realized, and the manpower is liberated.Originality/valueFirst, the modeling and analysis of the grinding end effector are carried out, and then the backstepping + PID method is adopted to control the grinding end effector to track the expected grinding force. The nonlinear model of the system is controlled by backstepping method, and in the process, the linear system composed of errors is obtained, and then the linear system is controlled by PID to realize the combination of backstepping and PID control.