Fuzzy PD Controller Research Articles

Robust speed control of hybrid electric vehicle using fractional order fuzzy PD and PI controllers in cascade control loop

In this paper, a novel scheme is proposed for speed control of highly nonlinear hybrid electric vehicle (HEV) having an electronic throttle control system (ETCS) in the cascade control loop. Fractional order fuzzy PD (FOFPD) and fractional order fuzzy PI (FOFPI) nonlinear controllers are developed and used as primary and secondary controllers, respectively in the cascade control loop. These controllers are variable gain fuzzy controllers having an adaptive nature. Their corresponding integral counterpart, fuzzy PD and fuzzy PI controllers are realized by keeping integer order differentiator and integrator in FOFPD and FOFPI controllers. Further, fractional order PD (FOPD) and fractional order PI (FOPI) controllers are implemented by using non-integer order operators in conventional PD and PI controllers. Extensive simulations have been carried out using National Instruments software LabVIEW™ and its add-on tools such as control design and simulation toolkit to perform a comparative study for FOFPD, FPD, FOPD and PD as primary controller and FOFPI, FPI, FOPI and PI as secondary controller for setpoint tracking of speed of HEV. Multi objective genetic algorithm is used to optimize the gains of primary and secondary controllers for minimization of integral of absolute error (IAE), maximum overshoot and settling time. Performances of tuned controllers are further evaluated for tracking of speed profile, disturbance rejection and model uncertainty. It has been observed that combination of FOFPD and FOFPI controllers outperformed rest of the controllers in servo, regulatory and uncertain environment and demonstrate very robust behavior for speed control of HEV.

Sit-to-Stand and Stand-to-Sit Control Mechanisms of Two-Wheeled Wheelchair.

This paper presents a mechanism for standing and sitting transformation of a wheelchair using a two-wheeled inverted pendulum concept with reduced torque requirement, in simulation studies. The motivation of this work is to design a compact standing mechanism to help an elderly/disabled person with functional limitation in lower extremities to maneuver in small and confined spaces and enable them to perform standard daily life routines independently. The wheelchair system at the upright standing position is tested with different travel distances, and the challenge is to control both sit-to-stand and stand-to-sit operations in a stable manner using flexible-joint humanoid. An additional spring/damping element is incorporated at each wheel to provide a comfortable ride for the user especially during stand-to-sit transformation task. A PD-fuzzy control with modular structure is implemented, and the performance of the system is observed through visual nastran 4d (vn4d) visualization software and simulation in matlab. The stand-to-sit performance tests have shown more than 38% reduction in tilt and back seat angles fluctuation in linear travel motion using a suspension system, while the initial tilt torque needed is 50% less than the amount required in previous designs.

Adaptive proportional derivative controller using fuzzy logic

Design of an improved fuzzy rule-based auto-tuning PD controller has been done with conventional Ziegler-Nichols PID controller. It has been observed that for the very common system in industry, the integrating system, the classical Ziegler-Nichols tuned PID controller (ZNPID) gives excessively large value of overshoot and settling time. Here, the proposed controller is a fuzzy auto-tuning PD (FAPD) controller. The value of the derivative gain of the conventional PD controller is continuously updated by a factor α. The value of α is determined depending on the process trend, i.e., normalised value of error (e) and change of error (Δe) and 49 or nine fuzzy if then rules. In FAPD, the updating factor 'α' continuously updates the value of derivative gain to provide an overall good performance during set point change and load disturbance. To study the effectiveness of the proposed controller FAPD has been tested and compared with other PID controllers for different integrating systems with varying dead time.

Fuzzy Controllers for a Gantry Crane System with Experimental Verifications

The control problem of gantry cranes has attracted the attention of many researchers because of the various applications of these cranes in the industry. In this paper we propose two fuzzy controllers to control the position of the cart of a gantry crane while suppressing the swing angle of the payload. Firstly, we propose a dual PD fuzzy controller where the parameters of each PD controller change as the cart moves toward its desired position, while maintaining a small swing angle of the payload. This controller uses two fuzzy subsystems. Then, we propose a fuzzy controller which is based on heuristics. The rules of this controller are obtained taking into account the knowledge of an experienced crane operator. This controller is unique in that it uses only one fuzzy system to achieve the control objective. The validity of the designed controllers is tested through extensive MATLAB simulations as well as experimental results on a laboratory gantry crane apparatus. The simulation results as well as the experimental results indicate that the proposed fuzzy controllers work well. Moreover, the simulation and the experimental results demonstrate the robustness of the proposed control schemes against output disturbances as well as against uncertainty in some of the parameters of the crane.

Modelling and Experimental Study on Active Energy-Regenerative Suspension Structure with Variable Universe Fuzzy PD Control

A novel electromagnetic active suspension with an energy-regenerative structure is proposed to solve the suspension’s control consumption problem. For this new system, a 2-DOF quarter-car model is built, and dynamics performances are studied using the variable universe fuzzy theory and the PD control approach. A self-powered efficiency concept is defined to describe the regenerative structure’s contribution to the whole control consumption, and its influent factors are also discussed. Simulations are carried out using software Matlab/Simulink, and experiments are conducted on the B-class road. The results demonstrate that the variable universe fuzzy control can recycle more than 18 percent vibration energy and provide over 11 percent power for the control demand. Furthermore, the new suspension system offers a smaller body acceleration and decreases dynamic tire deflection compared to the passive ones, so as to improve both the ride comfort and the safety.

A Study on Influence of System Parameters on Servo Pneumatic System and Multi-Response Optimization Using Taguchi – Grey Methodology

Servo pneumatics is a mechatronic approach that enables accurate position control of pneumatic drives with high speed. Simulation model of the servo pneumatic system with fuzzy PD controller has been created in Matlab-Simulink software using nonlinear mathematical model of the system. The influence of supply pressure and size of the cylinder on the positioning accuracy and speed has been studied. It is observed that the supply pressure is the most influencing factor in positioning accuracy and speed compared to the size parameters of the cylinders. Further a multi-response optimization of the system parameters minimize settling time, overshoot and ITAE (Integral of time-weighed absolute error) values has been carried out using Taguchi based Grey relational analysis methodology. The optimal system characteristics have been observed when supply pressure is 0.2 MPa, diameter of the cylinder is 0.05 m and length of the cylinder is 0.15 m.

Active Vibration Control for a Large Annular Flexible Structure via a Macro-Fiber Composite Strain Sensor and Voice Coil Actuator

Large annular flexible structures (LAFS) are typical antenna structures for satellites. This structure can significantly increase antenna aperture and effectively improve communication accuracy with minimum addition of mass. LAFS have become mainstream for large aperture antenna structures. However, they have disadvantages, such as low natural frequencies, low damping ratio, and low stiffness. They easily suffer from low frequency, longtime and modal responses. Therefore, the vibration control of LAFS is very important. This study proposes a novel active vibration control method using macro-fiber composite (MFC) as a sensing unit, a voice coil actuator and a PD-fuzzy control algorithm. The MFC sensor can measure a minimum strain of 10-8 m/m. The voice coil actuator generates a displacement and driving force. Based on the feedback signal from the MFC sensor, the PD-fuzzy control algorithm controls the voice coil actuator. A dynamic model of LAFS was established, and its characteristics analyzed. A theoretical model for the voice coil actuator and MFC sensor were established, and the corresponding governing equations derived. An experimental system was set up. The results demonstrated that the novel active vibration control method has good performance. This active vibration control method can control vibration at ultralow frequencies and requires no additional stiffness.

Fuzzy PD plus I Controller of a CSTR for Temperature Control

A chemical reaction occurring in CSTR (Continuous Stirred Tank Reactor) is significantly affected by the concentration, temperature, pressure, and reacting time of materials, and thus it has strong nonlinear and time-varying characteristics. Also, when an existing linear PID controller with fixed gain is used, the performance could deteriorate or could be unstable if the system parameters change due to the change in the operating point of CSTR. In this study, a technique for the design of a fuzzy PD plus I controller was proposed for the temperature control of a CSTR process. In the fuzzy PD plus I controller, a linear integral controller was added to a fuzzy PD controller in parallel, and the steady-state performance could be improved based on this. For the fuzzy membership function, a Gaussian type was used; for the fuzzy inference, the Max-Min method of Mamdani was used; and for the defuzzification, the center of gravity method was used. In addition, the saturation state of the actuator was also considered during controller design. The validity of the proposed method was examined by comparing the set-point tracking performance and the robustness to the parameter change with those of an adaptive controller and a nonlinear proportional-integral-differential controller.

Dual-layer fuzzy control architecture for the CAS rover arm

Since the conventional impedance control method for a rover arm is not suitable for unconstructed environment with uncertainties, a fuzzy inference method which improves the impedance model dynamically is introduced to realize high-precision control. The fuzzy PD control algorithm which applies to the joint control of a rover arm is analyzed in this paper. With the two level control algorithms, a novel dual-layer fuzzy control framework is proposed, which can enhance the control performance significantly. In order to verify the validity and reliability of the designed algorithms, the robotic arm of the CAS rover is considered as an experimental platform. Kinematics and dynamics models of robotic arm are derived at first. Moreover, the fuzzy inference mechanism and implementation process of impedance model parameters are illustrated. Extensive simulations and experimental results show that the control accuracy and the force control of the system have been significantly improved with the proposed dual-layer fuzzy control architecture.

Deployment and control of spacecraft solar array considering joint stick-slip friction

For solar array system, traditional modeling theories usually adopt the Cartesian coordinates to establish the dynamic equation of the system. The order of this equation is often too high and inconvenient to design control laws and the Cartesian coordinates are difficult to be measured in practice. This paper presents a modeling method for solar array system. In this method, joint coordinates of the solar panels, yoke and the spacecraft main-body are defined as the generalized variables. In this way, the dynamic equation derived here possesses lower order than those derived by other methods used before, which facilitates further control design. Moreover, the joint coordinates can be easily measured in practice. On the other hand, joint friction is an important issue to be considered. Joint friction could affect the stability and control precision of the system. Most existing studies on joint friction of solar array system are over-simplified into plane problems, and as a result, inaccuracy of friction force calculation output was incurred. In this paper, a three-dimensional revolute joint model is introduced, the calculation of joint friction is discussed in detail, and the relationship between ideal constraint force and Lagrange multipliers is derived. In addition, the control design of the solar array system is discussed and the fuzzy adaptive PD control method is used for controller design. At the end of this paper, the validity of the above studies is verified by the comparisons of numerical simulations with the ADAMS software.

Research on Fuzzy PD Current Controller for FDWRD

A fuzzy control scheme is proposed for the system of filling and draining off water of the rubber dam（FDWRD） which is a typical nonlinear, multi- variables, time- varying and strong coupling control system base on traditional PID control or model-based control methods can not meet its constant flow sufficient drainage control requirements, during to it couldn‘t be established accurate mathematical model. In a practical project, a fuzzy PD controller is designed for the constant current control of filling and draining off water of the rubber dam, combining with the traditional PID algorithm which is widely used in industrial process control, and achieved good control effect. This paper elaborates the control system of filling and draining off water of the rubber dam and the implementation process of the fuzzy PD controller, and then giving the actual control curve of constant current. Practice proves that the proposed control scheme is efficient and the system possesses good static, dynamic performance and certain robustness.

Development of intelligent controllers for pyrolysis reactors control systems based on their mathematical models

This paper presents the development and research of intelligent controllers for pyrolysis reactors control systems on the basis of its mathematical models. The functional structure and mathematical model of the pyrolysis reactor control system are presented. The reactor heating temperature control system is developed with the fuzzy PD-controllers of Mamdani and Sugeno types. The adjustment procedures of the fuzzy controllers, simulation and quality indicators comparative analysis of the control systems with fuzzy and traditional PD-controllers are carried out. Simulation results confirm the efficiency of the developed control systems, based on intelligent controllers. The PLC based realization of most efficient fuzzy controller is then considered.

PD Controller Structures: Comparison and Selection for an Electromechanical System

Many different PD controller modeling, configurations and control algorithms have been developed. These methods differ in their theoretical basis and performance under the changes of system conditions. In the present paper we review the methods used in the design of PD control systems. We highlight the main difficulties and summarize the more recent developments in their control techniques. Intelligent control systems like PD fuzzy control can be used to emulate the qualitative aspects of human knowledge with several advantages such as universal approximation theorem and rule- based algorithms.

Genetic Algorithm and Particle Swarm Optimization Based Cascade Interval Type 2 Fuzzy PD Controller for Rotary Inverted Pendulum System

This paper presents the design of an optimized Interval Type 2 Fuzzy Proportional Derivative Controller (IT2F-PDC) in cascade form for Rotary Inverted Pendulum (RIP) system. The parameters of the IT2F-PDC are optimised by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The goal is to balance the pendulum in upright unstable equilibrium position. The IT2F-PDC which is the extended version of conventional type 1 fuzzy logic controller, improves the control strategy by using the advantage of its footprint of uncertainty for the fuzzy membership function. The performance characteristics considered for the controller are steady state error, settling time, rise time, maximum overshoot, and control energy. Experimental and simulation results indicated that the effectiveness and robustness of the proposed GA- and PSO-based controllers on the RIP with respect to load disturbances, parameter variation, and noise effects have been improved over state-of-the-art method. However, the comparative results for simulation and experiment based on cascade IT2F-PDC indicate that GA-based IT2F-PDC has lower steady state error while PSO-based IT2F-PDC has lower overshoot, settling time, and control energy, but both have almost the same rise time. The proposed control strategy can be regarded as a promising strategy for controlling different unstable and nonlinear systems.

Adaptive MIMO Supervisory Control Design Using Modeling Error

This paper proposes an adaptive control scheme for nonlinear systems with significant nonminimum phase dynamics. The scheme is composed of an inner-level adaptive fuzzy PD control law and an outer-level supervisory control law. Importantly, the inner-level controller of the two-level scheme is designed based on a fuzzy model, which takes nonminimum phase phenomenon and modeling error explicitly into account. The scheme is both much simpler in design and more applicable to general nonlinear systems when compared with most existing nonlinear controllers. Effectiveness of the proposed control strategy is demonstrated by numerical simulation of the control of a five-degree-of-freedom aircraft system in the face of bursting disturbances.

The Speed Control Design Based on Fuzzy Logic

The cruise control system has the highly nonlinear and time-varying uncertainty, and it will also influenced by the outside disturbance and complex operating conditions, and it is difficult to obtain a satisfied effect by using traditional PID control. In this paper, the auto cruise control system is designed based on fuzzy PI and fuzzy PD control algorithm, and the simulated effect is also provided.

The research on the Application of Fuzzy Immune PD Algorithm in the Two-Wheeled and Self-Balancing Robot System

The fuzzy immune PD controller is designed in view of the nonlinear and model uncertainty characteristics of the two-wheeled and self-balancing robot, and the simulation study is carried out. The simulation results show that the designed control system has the advantages of small overshoot amount, short adjustment time and strong anti-jamming capability compared with the conventional fuzzy PD controller. It is suitable for the balance of the robot control system whose mathematical model is difficult to determine and when the parameter changes.

Study on Two-Wheeled Self-Balancing Electric Vehicle Based on Fuzzy PD Control Algorithm

A Two-Wheeled Self-Balancing Electric vehicle control system was developed base on the system design, hardware development and software strategies.The paper designed the posture acquisition module by gyroscopes and accelerometer sensors, and improved the control ccuracy using Calman filtering algorithm. Based on the system structure model, construction of Two-Wheeled Self-Balancing Electric vehicle dynamic equations by using the analysis method of Newtonian echanics was developed.A fuzzy PD controller was designed,the displacement and velocity as the input variable is controlled by fuzzy controller, and the tilt angle and angular velocity is controlled by PD controller. Finally, the platform of real-time control system was established for parameters adjustment and real-time control.Experiments show that the system has good robustness,high real-time response and has a higher market value.

Comparison of Performance Measures of Speed Control for a DC Motor Using Hybrid Intelligent Controller and Optimal LQR

-In this paper , performance of fuzzy PD , fuzzy PI , fuzzy PD+I , fuzzy PID controllers are evaluated and compared. This paper also describes the speed control based on Linear Quadratic Regulator (LQR) technique. The comparison is based on their ability of controlling the speed of DC motor, which merely focuses on performance index of the controllers, and also time domain specifications such as rise time, settling time and peak overshoot. The controller is modelled using MATLAB software, the simulation results shows that the fuzzy PID controllers are the best performing candidates in all aspects but it as higher overshoot and IAE in comparison with optimal LQR. The Fuzzy PI controller exhibited null offset but suffers from poor stability and peak overshoot, whereas the fuzzy PD controller has fast rise time, with no overshoots but the IAE is much greater. Thus, the comparative analysis recommends fuzzy PID controller but it is usually associated with complicated rule base and tedious tuning. To circumvent these problems, the proposed LQR controller gives better performance than the other controllers.

Analysis and Design on Course Control for Sail-Assisted Ship

Aiming at the problem that sail-assisted ship is easy to yaw because of sail’s lateral force and adjusts its course slowly due to wind, wave and other interferences on the sea, this paper put forward a feedforward feedback control method based on fuzzy system. According to the relationship between lateral force and yaw angle, a feedforward controller was designed to offset the yaw of ship. In order to correct the drift angle of ship automatically, the feedback controller was fulfilled to track the given course. Feedback control loop adopted fuzzy self-adjusting PD controller to make the drift angle be adjusted in time. The simulations indicate that the feedforward feedback control can suppress the disturbance produced by lateral force effectively, enhance the stability of the system and accelerate the response speed.