Fuzzy Cascade Control Research Articles

Research on up and down line control method of 500kV live working robot

It is a developing trend for transmission line operation robots to replace manual operations in line operation and maintenance. However, the existing on-line methods of robots are complex and inefficient, which seriously affects the progress of the entire operation and maintenance. In order to solve this problem, this paper studies the automatic on-line and off-line control method of live working robot for 500kV transmission lines. Firstly, the on-line and off-line structure of the robot and its operating mechanism are analyzed, and on this basis, the relevant mathematical model is established. Through the analysis of the model, cascade fuzzy PID is used to control the robot’s attitude leveling. Finally, through MATLAB software simulation, the cascade fuzzy PID control effect is the best.

A cascade fuzzy adaptive based interaction torque control of a pneumatically actuated forearm rehabilitation robot under disturbance effects

In this study, an intelligent adaptive interaction torque control for a pneumatically actuated forearm rehabilitation robot has been proposed. The main objective is to provide a haptic environment that ensures stable interaction torque fields at changing levels. To achieve this goal, a cascade fuzzy adaptive controller, that is specifically tailored to handle varying levels of interaction torque and ensure stability throughout the rehabilitation process, has been designed. To improve the efficiency of the controller, non-linear friction torque identification of the pneumatic actuator based on changing operating conditions has been conducted. Parallel to this, a user motion intention detection algorithm has been designed to provide compliant, safe and suitable human-robot interactions. The disturbance cases have been considered to make the system robust to unknown conditions. Stability analysis has been performed, specifically focusing on the boundary-input boundary-output (BIBO) stability conditions. In order to demonstrate the superior performance of the proposed cascade fuzzy adaptive algorithm, a cascade PID algorithm has also been meticulously designed for comparison. Numerous experimental validation tests involving a healthy user were conducted in a Hardware-in-the-Loop environment, focusing on torque trajectory tracking performance. The proposed control technique exhibited improved convergence dynamics compared to the cascade PID algorithm, yielding mean absolute error levels of 0.0218 Nm and 0.099 Nm for target interaction torque under disturbance-free and disturbed conditions, respectively.

Frequency control of fully-renewable interconnected microgrid using fuzzy cascade controller with demand response program considering

The main purpose of this paper is to design a good fuzzy cascade controller for interconnected microgrids (μGs) with supporting a frequency perturbation-based demand response program. A fuzzy PD-(1+I) controller is optimally designed to perform the load frequency task in a fully-renewable interconnected μGs. In the proposed control strategy, exact adjusting of controller parameters and membership functions has a key role to achieve the robust performance. Thus, the fuzzy PD-(1+I) controller is automatically designed and updated using a nature-inspired mayfly optimization algorithm for finding a better controller and reducing system control cost. It combines the fuzzy theory and cascade control advantages to enhance load disturbance rejection effort in each μG and dump frequency fluctuations considering system parametric uncertainties and renewable energy sources (RESs) generation changes. The studied two-area islanded μG system by applying a fuzzy PD-(1+I) controller has been investigated in six different situations in comparison with the fuzzy PID and PD-(1+I) cascade controllers to demonstrate capability of load disturbance rejection, RESs generation changes and system parameters variation. The results in all cases show the decisive superiority of the fuzzy PD-(1+I) controller and its high adaptability than the other controllers.

Design and Experimental Validation of a Fuzzy Cascade Controller for a Zero-Power Permanent Magnetic Suspension System with Variable Flux Path Control

Magnetic suspension technology has been a promising method to achieve contactless movement, and its advantages are smooth motion, no wear, no noise and low maintenance. In previous studies, the suspension force was mainly controlled by the current in the coils, which can lead to energy loss. To solve the problem of energy loss, we have proposed a novel zero-power permanent magnetic suspension system with variable flux path control (ZPPMSS-VFPC); moreover, the interference suppression and response of the ZPPMSS-VFPC need to be further investigated. This paper aims to improve the robustness and decrease the response time for the ZPPMSS-VFPC; as a result, a fuzzy cascade controller composed of a fuzzy controller and a cascade controller is designed and applied, in which the investigated fuzzy cascade control methods include the position loop fuzzy cascade control (PLFCC) and angle loop fuzzy cascade control (ALFCC). The structure and the working principle of the proposed ZPPMSS-VFPC are introduced, and the theoretical modeling and the fuzzy cascade controller design of the system are exhibited. An experimental setup is established to validate the simulation results and to investigate the control effect of the designed controller. The experimental results demonstrate that the response times of the fuzzy cascade controller at the displacement disturbance and the force disturbance are 0.5 s and 0.6 s faster than those of the cascade control, respectively. Furthermore, the control effect of the PLFCC is better than that of the ALFCC. Overall, the fuzzy cascade controller not only has the characteristics of strong adaptability but also has the characteristics of easy adjustment parameters, which can be applied to the complex magnetic suspension system.

Novel DQN optimised tilt fuzzy cascade controller for frequency stability of a tidal energy-based AC microgrid

The research paper addresses a robust tilt fuzzy cascade (TDF(1+TI)) controller for frequency regulation of an islanded AC microgrid under different uncertainties. The proposed microgrid is modelled with penetrating various renewable energy-based micro-generating units. The renewable energy-based power-generating sources are associated with low inertia and large uncertainties which degrade the frequency stability of the system. In order to obtain nominal frequency, the work employs a tilt-based fuzzy cascade controller to make control over the frequency of the system. The parameters of the proposed controller are optimally designed with suggesting a novel deep Q-network (DQN) algorithm under various operating regions. An assessment over comparative study has been carried out to validate the significance of the proposed tilt fuzzy cascade controller in response to frequency regulation of microgrid system. Finally, DQN optimised tilt fuzzy cascade controller is found to be more effective in regard to frequency regulation of microgrid system.

Frequency regulation of an electric vehicle-operated micro-grid under WOA-tuned fuzzy cascade controller

ABSTRACT The present manuscript highlights on the frequency regulation of an islanded AC micro-grid under different uncertainties. The advancement in battery-operated vehicles (electric vehicles) keeps environment clean and healthy due to carbonless gas emissions. However, charging of electric vehicles creates frequency instability issues in the micro-grid system. Additionally, the incorporation of low inertia and large uncertainties of the micro-grid system puts adverse effect over frequency stabilisation. To obtain multi-beneficial (green environment and nominal frequency) scenario in micro-grid systems, the manuscript proposes a robust fuzzy cascade PD-PI controller for this study. A nature-inspired whale optimisation algorithm (WOA) algorithm is suggested to optimally design the proposed fuzzy cascade PD-PI controller. In order to defend the viability of the proposed approaches few comparative analyses have been synthesised in this study. Finally, it is revealed the proposed WOA-optimised fuzzy cascade PD-PI controller gracefully improves micro-grid dynamic performance under various operational conditions.

Event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks

This paper investigates the event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks. In order to solve the problem of limited communication resources, an event-triggered scheme and a quantization mechanism are adopted, which can effectively reduce the burden of communication and save the network resources of the system. By considering the influence of cyber attacks, a newly quantized T-S fuzzy model for networked cascade control systems (NCCSs) under the event-triggered scheme is established. By using the Lyapunov stability theory, sufficient conditions guaranteeing the asymptotical stability of networked T-S fuzzy cascade control systems are obtained. In addition, the controller gains are derived by solving a set of linear matrix inequalities. Finally, a numerical example is presented to verify the validity of the proposed method.

Design and Simulation of Cascade Fuzzy Control System for Boilers

The control of boiler drum water level plays an important role in the automation control of boilers, the control effect directly affects the safety production of the boiler. In order to solve problems of non-linearity, instability and time-delay of boiler drum water level control system and difficulty in establishing accurate mathematical model, a feedforward-cascade three-flush boiler water level control system is designed, the Simulink control simulation system is established, and the control system is simulationed in the MATLAB environment, parameters of PID is determined according to engineering setting method, considering the PID controller exists some shortage,the adaptive fuzzy PID controller is designed and simulationed. The results of the system simulation analysis indicate, the three-pulse cascade and feedforward water level control system can effectively eliminate the load (steam amount) change and the disturbance of the feed water flow fluctuation, fuzzy adaptive PID has shorter response time and smaller overshoot than PID controller, to make the control water level meet the stable-operational requirement with high qualituy and accuracy, and can more satisfy the boiler drum water level control requirements.

Tracking Error Compensation of XY Table Ball Screw Driven System Using Cascade Fuzzy P+PI

This paper describes the potential of the fuzzy logic technique and cascade controller in improving the tracking performance of the XY Table Ball Screw Driven System. The proposed controller used in this research is Cascade Fuzzy P+PI. This proposed technique is compared to other techniques, namely PI and Fuzzy-PI controllers, for the purpose of proving the ability of both techniques in producing good results. The performances of the systems are analyzed to two cases, with and without disturbance. The disturbance case involves the form of cutting force with different spindle speeds which are 1000 rpm, 2000 rpm, and 3000 rpm. Besides, in order to examine robustness, the system is operated under different frequencies of 0.3 Hz, 0.5 Hz, and 0.7 Hz. The results show that the combination of Fuzzy Logic technique with Cascade Controller, which is known as Cascade Fuzzy P+PI, successfully, provide a good performance with an increase of 55% to 71% compared to other methods tested in this research.

Implementation of an Active Wire Tensioner Using a Cascade Fuzzy Logical Controller for a Brush-Less Direct Current Coil Winding Machine

This paper is to implement an active wire tensioner which uses a cascade fuzzy logical controller to handle wire tension on a brush-less direct current (BLDC) coil winding machine during the winding process. A manifold winding process of the BLDC machine found by an analysis among various winding processes shows that the wire tension in winding process of the BLDC winding machine is more fluctuated than that in other winding processes. Based on the result of the analysis, a mechanism called as a wire accumulator using a pneumatic servo system is designed to decay the vibration of wire tension encountered with the harsh condition of winding process. In order to ensure the wire accumulator working properly, a magnetic powder clutch is adopted to prevent the wire passing through the wire accumulator freely. The active wire tensioner is defined as a multi-input single-output system with two control inputs for driving the magnetic powder clutch/the pneumatic cylinder and single output as the wire tension force. For such sophisticated behavior of the system’s response, a novel cascade fuzzy logical controller (CC-FLC) with the fuzzy rule constructed based on a split-range method is appropriate for controlling the active wire tensioner. Additionally, the CC-FLC is convenient to be built into DSP alone-chip since its processing calculation consumes a low time. The effectiveness of the proposed active wire tensioner using CC-FLC is compared to that of a passive wire tensioner existing on the BLDC winding machine when both wire tensioners are used for coil producing process of the BLDC winding machine. Experimental results show that the BLDC winding machine equipped with the proposed active wire tensioner can operate at high winding speed without breaking the wire and reducing the coil size in the view of dimension.

Design and Implementation of Cascade Fuzzy Controller For Secondary Pipe Network Of Heat Exchange Station

Design and Implementation of Cascade Fuzzy Controller For Secondary Pipe Network Of Heat Exchange Station

Phase plane tuning of fuzzy controller for 1 DoF helicopter model

The paper suggests a design procedure for fuzzy cascade control. The expert knowledge based tuning procedure is supported by investigation the phase plane of the reference tracking. The plant is a one degree of freedom helicopter model with highly non-linear dynamics in a hardware-in-the-loop arrangement. Starting from a common fuzzy-PI controller in the outer loop and classic PI-controller in the inner loop, the presented tuning procedure enables to obtain fuzzy-adaptive parameter settings of the inner-loop and a heuristic modified rule base in the outer loop. The developed control strategy proves to be very successful: both the settling times and overshoots have become well regulated.

Model reference fuzzy cascade controller: a novel method for attaining desired mass flow in a wind tunnel

Hypersonic wind tunnels can hit hypersonic speeds and is used to test newly designed space crafts, airplanes, etc. The prototype of the vehicle is made and it is tested in the wind tunnel. While performing the experiment the pressure in the settling chamber has to be maintained constant, to get the desired Mach number speed and mass flow rate. Here, a novel non-linear control method called model reference fuzzy cascade MRFC controller is proposed and simulated for hypersonic wind tunnels. It consists of a cascade controller along with model reference and fuzzy controllers. Fuzzy controller is used instead of other neural controllers, since it is easy to implement and train them. The performance of MRAC controller is analysed with that of model reference fuzzy adaptive PI MRFA-PI controller. The simulation results shows that the MRFC controller is performing well compared to MRFA-PI for this process in terms of settling time and IAE.

Simulation Research on Fuzzy Control of Main Steam Temperature in Power Series

due to the characteristics of large delay, nonlinear super-heater, time-varying, multivariate and self-balance ability .It is difficult to establish accurate mathematical model, this paper uses the cascade fuzzy control, realize the effective control of the main steam temperature. Simulation results show that, the temperature cascade fuzzy control has fast dynamic response, good steady-state performance and robustness.

Simulation of Main Steam Temperature Control System Based on Fuzzy PID and Improved Smith Predictor

The main steam temperature process has the characteristics of large inertia, large time delay and time-variation , to solve this problem, the fuzzy PID cascade control system with Smith predictor is presented .The improved Smith predictor with the effect of filtering was used in the main loop of the cascade control system, and fuzzy PID compound controller was used as the main controller based on the advantage of fuzzy control and PID. Through establishing the mathematical model and simulating the main steam temperature control system, either the parameter changed or invariable, the results show that the method can improve the control qualities and enhance the robustness and stability of the control system.

Design of optimized cascade fuzzy controller based on differential evolution: Simulation studies and practical insights

In this study, we discuss a design of an optimized cascade fuzzy controller for the rotary inverted pendulum system and ball & beam system by using an optimization vehicle of differential evolution (DE). The structure of the differential evolution optimization environment is simple and a convergence to optimal values realized here is very good in comparison to the convergence reported for other optimization algorithms. DE is easy to use given its mathematical operators. It also requires a limited computing overhead. The rotary inverted pendulum system and ball & beam system are nonlinear systems, which exhibit unstable motion. The performance of the proposed fuzzy controller is evaluated from the viewpoint of several performance criteria such as overshoot, steady-state error, and settling time. Their values are obtained through simulation studies and practical, real-world experiments. We evaluate and analyze the performance of the proposed optimal fuzzy controller optimized by Genetic Algorithm (GA), and DE. In this setting, we show the superiority of DE versus other methods being used here as well as highlight the characteristics of this optimization tool.

Cascade fuzzy logic control of a single-link flexible-joint manipulator

This paper presents the design and control of a single-link flexible-joint robot manipulator. A cascade fuzzy logic controller (FLC) was used to remove link vibrations and to obtain fast trajectory tracking performance. The cascade FLC structure includes 3 different FLCs. The input variables of the first and the second FLCs are the motor rotation angle error, its derivative, and the end-point deflection error its derivative, respectively. The outputs of these controllers are the inputs of the third FLC, which yields the control signal to the flexible robot arm. All of the FLCs were embedded in a DS1103 real-time control board. Several experiments were conducted to verify the controller performance. In the step-response experiments, the error of motor rotation angle was obtained as less than 0.12° and there was no steady-state error in the end-point deflection. In trajectory tracking experiments with the same FLC structure, small errors and phase shifts in the system variables occurred. Model parameters of the flexible arm such as link length and spring stiffness were changed to test the robustness of the FLC. It was seen that the FLCs were very robust to internal and external disturbances. Considering the results of the experiments, the proposed FLC structure shows efficient control performance in flexible robot arms.

The Study on the Fuzzy Control Algorithm for Main Steam Pressure Control of Circulated Fluidized Bed Boiler

The main steam Pressure is one of the most important guidelines on Circulating Fluidized Bed Boiler (CFBB) operation quality and an important part in control system of CFBB. However, It is very difficult to establish the exact mathematical models of controlled objects because the combustion system of circulating fluidized bed boiler is an object that has many features: distributed parameters, nonlinear, time-varying and long time-delaying. it is unfavorable to control it with traditional controller. Therefore , In this paper fuzzy controller is used in controlling main vapor pressure systems of CFBB, and the fuzzy cascade control system is designed. In computer simulation, the fuzzy cascade control system exert stably, and has perfect control effect to main vapor pressure systems of CFBB.

A comparative experimental study of type-1/type-2 fuzzy cascade controller based on genetic algorithms and particle swarm optimization

In this study, we introduce the design methodology of an optimized fuzzy controller with the aid of particle swarm optimization (PSO) for ball and beam system. The ball and beam system is a well-known control engineering experimental setup which consists of servo motor, beam and ball. This system exhibits a number of interesting and challenging properties when being considered from the control perspective. The ball and beam system determines the position of ball through the control of a servo motor. The displacement change of the position of ball leads to the change of the angle of the beam which determines the position angle of a servo motor. The fixed membership function design of type-1 based fuzzy logic controller (FLC) leads to the difficulty of rule-based control design when representing linguistic nature of knowledge. In type-2 FLC as the expanded type of type-1 FL, we can effectively improve the control characteristic by using the footprint of uncertainty (FOU) of the membership functions. Type-2 FLC exhibits some robustness when compared with type-1 FLC. Through computer simulation as well as real-world experiment, we apply optimized type-2 fuzzy cascade controllers based on PSO to ball and beam system. To evaluate performance of each controller, we consider controller characteristic parameters such as maximum overshoot, delay time, rise time, settling time, and a steady-state error. In the sequel, the optimized fuzzy cascade controller is realized and also experimented with through running two detailed comparative studies including type-1/type-2 fuzzy controller and genetic algorithms/particle swarm optimization.

병렬유전자 알고리즘 기반 최적 Fuzzy PD Cascade 제어기의 설계

In this paper, we propose the design of an optimized fuzzy cascade controller for rotary inverted pendulum system by means of Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) which is a kind of parallel genetic algorithms. The rotary inverted pendulum system is the system for controlling the inclination of pendulum axis through the adjustment of rotating arm. The control objective of the system is to control the position of rotating arm and to make the pendulum maintain the unstable equilibrium point of vertical position. To control rotary inverted pendulum system, we designs the fuzzy cascade controller scheme consisted of two fuzzy controllers and optimizes the parameters of the designed controller by means of HFCGA. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy cascade controller leads to superb performance in comparison with the conventional LQR controller as well as HFCGA based PD cascade controller.