Nonlinear Fuzzy Logic Controller Research Articles

Fuzzy Coordinated Control of TCSCs to Improve Power System Stability

This paper presents the application of a coordinated fuzzy logic controller for the Thyristor Controlled Series Capacitors (TCSC) to improve the stability of the power system. The nonlinear fuzzy logic controller is used to overcome the problems generated by modeling and different uncertainties existing in power systems during design stage of controllers to damp electromechanical oscillations. To facilitate the design process, neural network is used to model the system input-output behavior. Proposed method is implemented on the 9 Bus IEEE power system and simulation results are presented to confirm the performance of the proposed controller. It is shown that this controller can increase the damping of the system

A new fragled series resonance-bridge fault current limiter with fuzzy logic controller to enhance fault ride through capabilities in DFIG-wind farms

In the wind energy market, the doubly-fed induction generator (DFIG) is the most popular generator over the other generators. However, the noteworthy concern for DFIG-based wind farms (WFs) is to retain transient stability at fault condition and according to grid code requirements, generators should connect to the grid. Therefore, the need of some solution against the severity is essential. In this paper, a series resonance-bridge type fault current limiter (SR-BFCL) with accurate nonlinear fuzzy logic control is proposed to achieve the fault ride through (FRT) capabilities. The proposed FCL provides low-voltage ride through (LVRT) and reactive power compensation. A comparative analysis has been performed with inductive-type bridge fault current limiter (I-BFCL). Simulation results are performed in MATLAB/Simulink environment under both symmetrical and unsymmetrical faults. A quantitative analysis is reported in terms of the performance indexes that indicate the proposed FCL gives a better performance in comparison to the I-BFCL.

Control of Photovoltaic Water Pumping System Employing Non-Linear Predictive Control and Fuzzy Logic Control

This contribution proposes a robust control scheme for a two-stage water pumping system based on an induction motor. In the first stage of the system, a boost converter is used for maximum power point tracking, while the second stage consists of a three-phase inverter that regulates the DC-bus voltage and the rotor speed of an induction motor. In order to achieve a fast-tracking of the maximum power, an improved maximum power point tracking algorithm based on a fuzzy logic controller is designed in this paper. On the other hand, a non-linear predictive controller is employed to drive the induction motor, due to its capability to eliminate the drawbacks of the conventional field-oriented control. The performances of the proposed control scheme are evaluated in the MATLAB/Simulink environment. The developed control scheme was compared with the conventional one (Perturb and Observe algorithm for maximum power point tracking and field-oriented control to control the induction motor). It is concluded that the developed control techniques offer excellent performances such as rapid maximum power point tracking, stable output power, and high-quality of power conversion.

Active gyroscopic stabilizer to mitigate vibration in a multimegawatt wind turbine

AbstractOne of the main concerns in developing large wind turbines, especially offshore, is their cost‐effectiveness versus traditional power sources. Significant dynamic loads are applied to the tower and the foundation of a multimegawatt wind turbine. Any reduction in the loads can reduce the size of the structure and, consequently, the turbine's cost. In this paper, a novel structural control application is proposed to mitigate the transmitted vibrations to a multimegawatt turbine tower to decrease the tower base shear forces and overturning moments. For this purpose, a hybrid passive/active gyro stabilizer is designed and incorporated into the NREL baseline 5‐MW wind turbine. Furthermore, two controllers, including a proportional integral differential (PID), as the baseline controller, and a nonlinear fuzzy logic controller (FLC) as the main and nonlinear controllers, have been designed and implemented to the turbine model. The structural control systems are implemented into the turbine model by cosimulating ADAMS and Simulink. The results reveal that the application of the proposed stabilizer can significantly reduce the overturning moment at the base of the tower compared to the reference NREL 5‐MW model.

Underactuated Coupled Nonlinear Adaptive Control Synthesis Using U-Model for Multivariable Unmanned Marine Robotics

This paper presents the control modelling and synthesis using a coupled multivariable under-actuated nonlinear adaptive U-model approach for an unmanned marine robotic platform. A nonlinear marine robotics model based on the dynamic equation using the Newtonian method and derivation with respect to the kinematics equations and rigid-body mass matrixes are explained. This nonlinear marine robotics model represents the underwater thruster dynamics, marine robotics dynamics and kinematics related to the earth-fixed frame. Coupled multivariable nonlinear adaptive control synthesis using a U-model approach for the Remotely Operated Vehicle (ROV) and Unmanned Surface Vessel (USV) represent an unmanned marine robotics application. A comparison is presented for the proposed nonlinear control approach between the U-model control approach with nonlinear Fuzzy Logic Control and Sliding Mode Control for the ROV and USV platforms. The results show minimum mean square error values and tracking performance between the plant or system model with the proposed method. Lastly, robustness and stability analysis for the proposed U-Model nonlinear control approach are presented by implementing an adaptive learning rate value.

Performance Improvement of Multi-DER Microgrid for Small- and Large-Signal Disturbances and Nonlinear Loads: Novel Complementary Control Loop and Fuzzy Controller in a Hierarchical Droop-Based Control Scheme

This paper presents new control scheme for a microgrid including several distributed energy resources that is completely analyzed so that the three hierarchical control levels are modeled for islanded and grid-connected modes. However, decentralized control methods of voltage-source converter (VSC)-based microgrids and microgrids’ hierarchical control scheme in the earlier research works have been limited to primary and secondary control levels. The presented hierarchical control scheme exploits new control loop to control the reactive power reference by a nonlinear fuzzy logic controller to improve performance of microgrid, not only for small signal events, but also respect to large signal disturbances such as short circuits, line outage, heavy motor starting, etc. and moreover, nonlinear loads and consequently, have the benefit of increasing the system stability margins and fault ride through capability. Besides, this control scheme can sufficiently provide power sharing to loads and network. Simulation studies are performed on a microgrid consisting of four distributed energy resources with local loads in MATLAB/Simulink environment to show the effectiveness of the proposed hierarchical control strategy.

Adaptive multipopulation genetic algorithm based self designed fuzzy logic controller for active magnetic bearing application

Active magnetic bearings (AMBs) are contact less bearings where the stable suspension of the rotor depends on attractive forces produced by electromagnets. Further, these systems are subjected to system uncertainties, nonlinearities and speed dependent rotor dynamic conditions. Therefore, designing a controller to provide a desired dynamics for these systems is a challenging task. Various linear and nonlinear control techniques have been used to control AMBs. These techniques require detailed mathematical model of the system and are sensitive to modelling errors. Therefore, in the present work, human heuristic knowledge based nonlinear fuzzy logic controller (FLC) is designed for AMB. Zero-order Takagi–Sugeno controller (ZTSC) model of FLC is proposed over Mamdani model to reduce the computational time required to calculate the fuzzy output. However, deciding the fuzzy parameters such as rule base and range of operation of the membership functions to achieve desired performance is an iterative process. In order to automate this process and to improve the performance of controller, a self-designed zero-order Takagi–Sugeno controller (SZTSC) based on evolutionary genetic algorithm is proposed. Further, multipopulation genetic algorithm with adaptive tuning of its parameters (adaptive multipopulation genetic algorithm) is proposed over simple genetic algorithm, due to its ability to search better optimal solution at a higher convergence speed. Membership functions range of operation for the input variables and control rules of the SZTSC are generated automatically without any expert’s knowledge by adaptive multipopulation genetic algorithm based optimization method. Simulations are carried out to check the performance of SZTSC compared to the expert’s knowledge based ZTSC. SZTSC has shown better performance compared to ZTSC under different dynamic conditions of AMB.

Self-tuned robust fractional order fuzzy PD controller for uncertain and nonlinear active suspension system

In this paper, a self-tuned robust fractional order fuzzy proportional derivative (FO-FPD) controller is proposed for nonlinear active suspension system of a quarter car. Quarter car is a highly uncertain system as the number of riders or payload may vary. The control objective is to improve the level of ride comfort by minimizing the root mean square of vertical vibration acceleration (RMSVVA) of car body and maintaining hard constraints such as tracking force, ratio of tyre dynamic and static loads and suspension travel. The used FO-FPD controller is a nonlinear fuzzy logic controller having self-tuning capability, i.e. it changes its gains at runtime. The FO-FPD controller is realized using non-integer differentiator operator in FPD controller. The gains of FO-FPD and FPD controllers are tuned using Genetic Algorithm optimization method for a sinusoidal road surface. To evaluate the performances, extensive simulation studies were carried out and FO-FPD and FPD controllers were compared for different roads profiles such as sinusoidal, random and bump. It has been observed that FO-FPD and FPD controllers outperform passive suspension system in terms of RMSVVA and offer much better comfort ride while keeping all the hard constraint in the specified limits. Furthermore, FO-FPD controller demonstrated an excellent comfort ride, especially in uncertain environment, wherein it offered very robust behaviour as compared to FPD controller. Also, bonded-input and bounded-output stability conditions are established for overall closed loop control system by using small gain theorem.

Smart damping of functionally graded nanotube reinforced composite rectangular plates

In this study, the dynamic response and the active vibration control behavior of various functionally graded carbon nanotube reinforced composite (FGCNTRC) rectangular plates is investigated numerically instrumented with piezoelectric sensor and actuator layers. The functionally graded plate is modeled using finite element method incorporating first order shear deformation theory is implemented in order to predict static and dynamic responses of vibrating structure. The linear piezoelectric theory is implemented to model the piezoelectric effect across the thickness. The equations of motion of the smart plate are formulated using Hamilton’s principle. The nonlinear fuzzy logic controller is designed as multi input-single output (MISO) system using 49 If-Then rules and implemented numerically to perform active vibration control. The results are presented both in the time domain and frequency domain. The numerical simulations conclude that the FG-O plate panel demonstrates the fastest vibration attenuation subjected to impact load using a fuzzy logic controller followed by FG-V, FG-UD and FG-X plate panels irrespective of volume fraction of the CNTs as well as boundary conditions. The effect of temperature rise and volume fraction of CNT on natural frequency of CNT reinforced composite plate with different boundary conditions is also investigated.

Experimental and numerical investigation of active vibration control over wide range of operating temperature

In this study, the dynamic response and the active vibration control behavior of cantilever-type structure over wide temperature range (−70°C to 70°C) are investigated experimentally and numerically. A cantilever structure of titanium alloy integrated with the collocated piezoelectric ceramic (PZT-5H) was studied for effective vibration amplitude reduction. The experimental results are verified with the numerical results which show good agreement among them. For the numerical simulations, finite element formulation using first-order shear deformation theory is implemented. The nonlinear fuzzy logic controller is designed as multi-input single-output system using 49 rules and implemented both experimentally and numerically to perform active vibration control. The results show that even moderate fluctuations in the temperature under study can considerably influence the performance of the piezoelectric ceramics used as sensors and actuators resulting in degraded performance for active vibration control.

Development and precision position/force control of a new flexure-based microgripper

This paper presents the design, modeling and position/force control of a new piezo-driven microgripper with integrated position and force sensors. The structural design of the microgripper is based on double amplification mechanisms employing the bridge-type mechanism and the parallelogram mechanism. The microgripper can generate a large gripping range and pure translation of the gripping arm. Through the pseudorigid-body-model method, theoretical models are derived. By means of several finite-element analysis simulations, the optimal structural parameters for the microgripper are acquired and the theoretical models are analyzed and validated. Furthermore, to improve the performance of the microgripper, a new hybrid position/force control scheme employing a nonlinear fuzzy logic controller combined with an incremental proportional-integral controller is presented. The control scheme is capable of regulating the position and the gripping force of the microgripper simultaneously. Experimental investigation and validation were performed and the experimental results verify the effectiveness of the developed structural design and the proposed hybrid control scheme.

Active vibration control of space antenna reflector over wide temperature range

In this study, the dynamic response and the active vibration control behavior of large space antenna reflector is investigated numerically over wide temperature range (−70°C to 120°C). A space antenna reflector of composite material integrated with collocated piezoelectric ceramic PZT-5H was studied for effective vibration amplitude reduction. For the numerical simulations, finite element formulation is employed. The nonlinear fuzzy logic controller is designed as single input–single output (SISO) system using 49 If-Then rules and implemented numerically to perform active vibration control. The results are presented in time domain and frequency domain. The numerical results show that even moderate fluctuations in temperature under study can considerably influence the performance of piezoelectric ceramics used as sensors and actuators resulting in degraded performance for active vibration control. The fuzzy logic controller can effectively attenuate the structural vibrations at both high and low temperature.

Genetic Optimization based Adaptive Fuzzy Logic Control of a pH Neutralization Process

Presence of severe nonlinearity in pH neutralization process makes the problem of pH control a difficult and challenging one. Further, optimized control of such highly nonlinear system requires tuning of various parameters with a suitable evolutionary algorithm (EA). This paper presents genetic algorithm (GA) based unconstrained, continuous and single-objective optimization of conventional and adaptive nonlinear fuzzy logic control (FLC) of pH neutralization process for servo and regulatory operations. The GA optimized adaptive FLC scheme changes the universe of discourse of input-output membership functions based on the region of operation and amount of step change in set-point and load. The performance of controllers are evaluated using integral of squared errors (ISE) and tested for random step changes in set-point and load.

Fault-tolerant control of three-pole active magnetic bearing

Active magnetic bearings have many advantages over conventional bearings due to contactless operation and adjustable force dynamics. However, one of the obstacles associated with these bearings is failure modes, which may result in destructive rotor dynamic behaviour. One of the important failure modes is electric power outage which may be due to failure of power amplifier, coil or electric wiring. In the present work, a fault tolerant controller has been designed for three-pole magnetic bearings to provide unaltered performance in the event of fault occurrence. The controller has been designed by incorporating the nonlinear fuzzy logic control. The present design of fuzzy logic controller is done by reducing the number of rules of its rule base. Simulations have been carried out to test the performance of the controller for different failure conditions. The designed controller is able to stabilize the rotor for large deviations from the origin even in the presence of failure. The controller is found to be robust as it provides satisfactory operation in the presence of uncertainties.

Single-chip fuzzy logic controller design and an application on a permanent magnet dc motor

This paper describes a low-cost single-chip PI-type fuzzy logic controller design and an application on a permanent magnet dc motor drive. The presented controller application calculates the duty cycle of the PWM chopper drive and can be used to dc–dc converters as well. The self-tuning capability makes the controller robust and all the tasks are carried out by a single chip reducing the cost of the system and so program code optimization is achieved. A simple, but effective algorithm is developed to calculate numerical values instead of linguistic rules. In this way, external memory usage is eliminated. The contribution of this paper is to present the feasibility of a high-performance non-linear fuzzy logic controller which can be implemented by using a general purpose microcontroller without modified fuzzy methods. The developed fuzzy logic controller was simulated in MATLAB/SIMULINK. The theoretical and experimental results indicate that the implemented fuzzy logic controller has a high performance for real-time control over a wide range of operating conditions.

Varying the Stiffness of a Beam-Like Neutralizer Under Fuzzy Logic Control

Vibration neutralizers are effective vibration control devices at a single frequency. If they can compensate for drift in the excitation frequency by adjusting their stiffness the performance can be improved, and the range of problems to which they can be applied is broadened. This paper considers a beam-like adaptive vibration neutralizer, and it is shown that the stiffness of the device and hence its natural frequency can be significantly altered by varying the beam cross-section. Several different beam configurations are investigated and the rate of change of stiffness as a function of beam separation is calculated for each configuration. The results are validated by some simple experiments. Real-time stiffness control of a beam-like tuneable neutralizer is also demonstrated both by computer simulation and experiment. The neutralizer is subjected to swept sine excitation over a six-second period and the tuned condition is maintained throughout the excitation period. The efficacy of using a nonlinear fuzzy logic controller is compared with the use of a simple proportional controller.

Fuzzy logic based attitude control of the spacecraft X-38 along a nominal re-entry trajectory

Fuzzy logic control techniques are investigated for applications in the intelligent re-entry flight control of the ESA–NASA crew return vehicle. Three PD-Mamdani fuzzy controllers are constructed to control the inner-loop attitude dynamics, simulated by a fully nonlinear 3 degree-of-freedom simulator of the CRV. Each controller uses an angle tracking error and its derivative to calculate a commanded control surface deflection of the simulator. The input-domains are partitioned with 5 membership functions, resulting in 25 fuzzy rules for each rule-base. The output-domains are partitioned with 9 membership functions. The Mamdani controllers use a standard max–min inference process and a fast center of area method to calculate the crisp control signals. Simulation results show the ability to track a reference trajectory with acceptable performance, though the real strength of a nonlinear fuzzy logic controller is yet to be proven with more demanding benchmark trajectories.

Robust fuzzy control of a magnetic bearing system subject to harmonic disturbances

Proposes a robust fuzzy logic-based control scheme for a rotating active magnetic bearing (AMB) system. We represent the nonlinear magnetic bearing by means of a Takagi-Sugeno-Kang fuzzy model. Subsequently a systematic synthesis procedure is used to derive a nonlinear fuzzy logic control strategy that overcomes the inherent characteristics of displacement sensitivity and position-dependent nonlinearity of the AMB. Experimentation and simulation results demonstrate that the proposed fuzzy controller yields robustness against harmonic disturbances and parameter uncertainties.

Global stability analysis of fuzzy controllers using cell mapping methods

Linear and nonlinear stability analysis of a nonlinear fuzzy logic controller is considered. The linear analysis is carried out by Lyapunov's first method (i.e. by determination of the eigenvalues of the linearized system). The nonlinear global stability analysis is executed by a combination of two methods: simple and interpolated cell mapping. Examples of controllers with a complex dynamic behavior are presented. These include controllers with multiple solutions such as (i) stable equilibrium point and stable limit circle, (ii) five unstable equilibrium points and three stable limit circles, and (iii) examples where the linear analysis is completely insufficient and only nonlinear investigation provides desirable results. The structure of domains of attraction of stable solutions is determined. Comparison of the results obtained by the cell mapping method with those provided by direct numerical integration, are presented.