A Classic and Fuzzy Parallel Hybrid Controller of PD-PI Type for a Two-Wheeled Self-Balancing Robot

Modern spacecraft are often equipped with large-scale, complex, and lightweight solar arrays whose deployment involves a highly dynamic movement. This paper proposed a novel adaptive proportional-derivative typed fuzzy logic control scheme for the attitude stabilization of a flexible spacecraft during the deployment of a composite laminated solar array. First, a constrained rigid-flexible coupling spacecraft model consisting of a rigid main body and a flexible solar array was proposed. The solar array, which is composed of composite laminated shells, was described by the absolute nodal coordinate formulation. Then, the detailed derivation of the adaptive fuzzy PD controller for attitude stabilization of the spacecraft was discussed. In addition, the spacecraft dynamic model which integrated the adaptive fuzzy PD controller was derived as a set of differential-algebraic equations. Several simulations were developed to investigate the solar array deployment dynamics and to verify the effectiveness of the proposed adaptive fuzzy PD controller. The results suggested that the proposed dynamic model is able to exactly describe the deployment dynamics of the composite laminated solar array. The solar array deployment causes obvious translational and rotational motions of the spacecraft. The proposed adaptive fuzzy PD control scheme has better performance in terms of the control precision and time response in stabilizing spacecraft during the deployment of the composite laminated solar array, comparing with that of the conventional PD controller.

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.

This paper presents an Artificial Intelligence (AI) based approach uniquely applied to Permanent Magnet DC motor actuator for position control. The AI method employed in this work is Fuzzy logic. A first order lag Sliding mode controller is tuned and combined with an Adaptive Fuzzy- PI controller architecture which operates in parallel. The controller architecture proposed in this study is aimed at improving the disturbance rejection capability, steady state as well as transient performance of the conventional Adaptive Fuzzy-PI controller and sliding mode controller. Hence, the robust control law of the proposed controller (SM+FZ-PI) consists of a discontinuous Sliding mode output added to a continuous Adaptive Fuzzy-PI controller output. The sliding mode controller switches on only when disturbance in the system is detected. The performance of the proposed controller architecture has been compared with a conventional PID and Adaptive Fuzzy-PI controllers for performance evaluation with respect to several operating conditions such as load torque disturbance injection, noise injection in feedback loop, motor non-linearity exhibited by parameters variation, and a step change in reference input demand. The proposed controller (SM+FZ-PI), had the best disturbance rejection and steady state error elimination.

As the near space atmospheric environment is complicated and variational, aircraft electric propulsion system parameters and load characteristics of the propeller will be changed, if the control method of electric propulsion system shall not be treated, the system stability and reliability will be affected. A novel double close loops control method with current and speed was presented in this paper, PI control combined with fuzzy adaptive scheme was developed for high-performance robust speed controller, which has the advantages of fuzzy adaptive control and PI control, PI control was developed for the current controller. And the system simulation experiments were accomplished in Matlab/Simulink. The simulation results are illustrated to show that the system works well, has very good static and dynamic performance, strong robustness and self-adaptive ability than PI control.

Artificial intelligence methods such as fuzzy logic and particle swarm optimization (PSO) have been applied to maximum power point tracking (MPPT) for solar panels. The P-V curve of a solar panel exhibits multiple peaks under partial shading condition (PSC) when all modules of a solar panel do not receive the same solar irradiation. Although conventional PSO has been shown to perform well under uniform insolation, it is often unable to find the global maximum power point under PSC. Fuzzy adaptive PSO controllers have been proposed for MPPT. However, the controller became computation-intensive in order to adjust the PSO parameters for each particle. In this paper, fuzzy adaptive PSO-based and conventional PSO-based MPPT are compared and evaluated in the aspect of design and performance. A simple fuzzy adaptive PSO controller for MPPT was designed to reach the global optimal point under PSC and uniform irradiation. The controller combines the advantages of both PSO and fuzzy control. The fuzzy controller dynamically adjusts the PSO parameter to improve the convergence speed and global search capability. Since tuning of the PSO parameter is designed to be common for all particles, it reduced the computation complexity. The fuzzy controller’s rule base is designed to obtain a fast transient response and stable steady state response. Design of the fuzzy adaptive PSO-based MPPT is verified with simulation results using a boost converter. The results are evaluated in comparison to the results using a conventional PSO controller under PSC. Simulation shows the fuzzy adaptive PSO-based MPPT is able to improve the global search process and increase the convergency speed. The comparison indicates the settling time using the fuzzy adaptive PSO-based MPPT is 14% faster under PSC on average and 30% faster under uniform irradiation than the settling time using the conventional PSO. Both the fuzzy adaptive and conventional PSO controllers have similar output power tracking accuracy.

In this paper, an adaptive fuzzy output feedback control approach is investigated for a class of stochastic nonlinear strict-feedback systems without the requirement of states measurement. The stochastic nonlinear system addressed in this paper is assumed to possess unstructured uncertainties (unknown nonlinear functions) and, in the presence of unmodeled dynamics, dynamics disturbances. Fuzzy logic systems are used to approximate the unstructured uncertainties, and a fuzzy state observer is designed to estimate the unmeasured states. By combining the backstepping design technique with the stochastic small-gain approach, a new adaptive fuzzy output feedback control approach is developed. It is proved that the proposed control approach can guarantee that the closed-loop system is input-state-practically stability (ISpS) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation results are included to indicate that the proposed adaptive fuzzy control approach has a satisfactory control performance. In addition, the simulation comparisons with the previous methods show that the proposed adaptive fuzzy control approach has robustness to the dynamical uncertainties.

Abstract- This paper introduces a linear structure of wind turbine, operator and the pitch angle controller. Then, a new method of adaptive fuzzy on the variable speed wind turbines was provided and it was compared with PID and Fuzzy Logic Control ler and the simulation results were analyzed. So when the results of each simulation using PID and Fuzzy controllers and adaptive fuzzy PID controllers provided, the observed advantages and disadvantages of the rotor speed and wind turbine power can be introduced. It can be seen that in PID method the high overshoot is discussed as a disadvantage while it is overcome by using fuzzy controller and overshoot will decrease. The time of reaching to a sustained speed increases slightly and in adaptive fuzzy PID controller, the less overshoot has provided a good and effective performance for system response. The use of adaptive fuzzy PID controller causes the system does not have any steady-state error and at all moments of time, the response rate is better than PID and fuzzy controller. The importance of the amount of overshoot and rate fluctuations is that by reducing these parameters in addition to reducing the cost of preventive care, maintenance and depreciation, the fluctuations in electricity generated by induction generator also greatly reduced.

This paper presents a new dual-loop control structure, with a fixed switching frequency current decoupling as the inner-loop and a fuzzy adaptive PI voltage as the outer-loop. The input currents are decoupling controlled in the stationary reference frame. A fuzzy adaptive PI voltage controller with the direct voltage error and the slope of the error based on the theory of fuzzy adaptive PI control is designed. A simulation model is created in Matlab. The overshoot of the system response, time of system dynamic response and input current waveform are compared with the experiments of traditional PI controller versus fuzzy adaptive PI controller during the operation including starting and a sudden change from rectifying to regenerating. The simulation results show that this control strategy can improve the dynamic and static performance. Finally , the feasibility of this method is verified by the results of Experimentation.

This paper introduces a high quality home PV power supply system. A step-up power converter is applied to take the place of the step up transformer. A fuzzy adaptive PI control scheme is applied to control the output of the inverter. The performances of the prototype shows that the new developed one could be an effective alternative for smaller home PV power supply systems in the future.

This paper presents a fuzzy PI controller as a power system stabilizer. The fuzzy PI controller has been designed in order to prepare an auxiliary signal for the excitation system of the synchronous generator. The proposed controller utilizes a combination of a fuzzy logic controller (FLC) and a PI controller, which are the most recent researches in the problem at hand. In comparison with the conventional fuzzy controllers, the proposed fuzzy PI controller takes advantage of both FLC and conventional PI controller to overcome all kind of disturbances. The damping of oscillations local modes in a power system will substantially be controlled by employing this controller as a replacement for conventional PSS. Furthermore, the presented paper considers the conventional PSS and compares its performance with respect to three proposed types of fuzzy PI controller. Correspondingly, the effects of the supplementary signals in damping oscillation have been shown. Finally, to scrutinize the effectiveness of the proposed controller in damping oscillations, a three-phase short circuit condition is studied in order to clarify the application of the developed methodology. The achieved outcomes show that the proposed controller for stabilizing power system can provide very good damping characteristic.

Aircraft are non-minimum phase, MIMO and highly nonlinear systems which undergo significant disturbances and variation in system parameters during operation. In spite of the prosperous literature in adaptive control, application of the promising control strategy on aircraft control has been restricted by the lack of assurance in closed-loop stability. This paper proposes a robust adaptive control scheme for aircraft. The scheme is composed of an inner-level adaptive fuzzy PD control law and an outer-level supervisory control law. Importantly, the outer-level controller of the two-level scheme is designed based on a fuzzy model which takes non-minimum phase phenomena and modeling error explicitly into account. Numerical studies of the tracking control of a five degree of freedom aircraft system demonstrate the effectiveness of the proposed control strategy in the face of bursting disturbances.

Motion control is an essential part of industrial machinery and manufacturing systems. In this article, the adaptive fuzzy controller is proposed for precision trajectory tracking control in biaxial X-Y motion stage system. The theoretical analyses of direct fuzzy control which is insensitive to parameter uncertainties and external load disturbances are derived to demonstrate the feasibility to track the reference trajectories. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system, and all the signals are bounded in the closed-loop system. The intelligent position controller combines the merits of the adaptive fuzzy control with robust characteristics and learning ability for periodic command tracking of a servo drive mechanism. The simulation and experimental results on square, triangle, star, and circle reference contours are presented to show that the proposed controller indeed accomplishes the better tracking performances with regard to model uncertainties. It is observed that the convergence of parameters and tracking errors can be faster and smaller compared with the conventional adaptive fuzzy control in terms of average tracking error and tracking error standard deviation.

Adaptive fuzzy fault-tolerant control problem for a class of uncertain switched stochastic nonlinear systems with time-varying asymmetric output constraints is addressed in this study. Under the action of well-designed asymmetric nonlinear mapping, fuzzy control technology, and backstepping recursive design scheme; the actuator faults of both loss of effectiveness and lock-in-place are considered to develop the adaptive fuzzy controller. The boundedness of all signals as well as the convergence of the output tracking error of the closed-loop plant to an arbitrary small neighborhood about zero are guaranteed by the developed fuzzy adaptive control strategy, and the time-varying output constraints are not violated. A simulation example is worked out to demonstrate the validity of the proposed control scheme.

For two-wheeled self-balancing robot nonlinear model uncertainties and other characteristics, the design of fuzzy immune PD controller and a simulation study. The simulation results show that the control system than the conventional fuzzy PD controller with a small overshoot, adjust the time is short, anti-interference ability, etc., applicable to the mathematical model and the parameter change is difficult to determine two-wheeled self-balancing robot control system.

The combination of matrix converter with direct torque control is a way towards green energy-saving of the world. It has great sense for theory research and good developing future. First, it is analyzed about working principle of matrix converter, the control principle and its realization process of direct torque control for induction machine inverter-based. Then the comprehensive switching control table is deduced according to the special properties of matrix converter together with direct torque control for induction machine. And the comprehensive modulation strategy can be concluded by looking up the table. Third, the simulation model is set up. The simulation results have verified the feasibilities and advantages of this novel alternative current adjustable speed system. Finally, an adaptive fuzzy PI controller was designed to improve the electric magnetic torque of induction machine.