Self-organizing Fuzzy Sliding Mode Control Research Articles

A novel approach to wastewater treatment control: A self-organizing fuzzy sliding mode controller

<p>The treatment of wastewater plays a crucial role in protecting the environment and ensuring the sustainable use of resources. This research paper presents a new methodology for managing wastewater treatment operations, utilising Self-Organizing Fuzzy Sliding Mode Controller (SOFSMC) to enhance the efficiency of treatment procedures. MATLAB Simulink functions as a simulation tool that facilitates meticulous analysis. SOFSMC presents a control strategy that is both adaptive and robust. This strategy effectively regulates crucial parameters, including dissolved oxygen levels, pH levels, and flow rates. It achieves this within the challenging and complex framework of wastewater treatment, which is characterised by dynamic and nonlinear dynamics. Using a SOFSMC for wastewater treatment control is novel approach. This novel technique creates a self-learning, dynamic system using fuzzy logic (FL) and sliding mode control (SMC). This unique approach can autonomously adapt to wastewater treatment processes' complex and nonlinear dynamics, improving efficiency, resource optimisation, and system dependability. The results emphasise the potential of SOFSMC as a revolutionary approach for wastewater treatment. This approach can improve treatment effectiveness, conserve resources, and protect the environment. The proposed method SOFSMC, exhibits commendable outcomes, with an integrated absolute error of 0.082 mg/L, an integrated square differential error of 0.091 mg/L, and a response time of 1.85 seconds This study offers a substantial advancement in the field of wastewater treatment regulation, highlighting its significance in the context of sustainable water management and environmental conservation.</p>

Adaptive self-organizing fuzzy sliding mode controller for a nonlocal strain gradient nanobeam

In this investigation, an adaptive self-organizing fuzzy sliding mode controller (ASFSC) has been developed for vibration control of an Euler-Bernoulli nanobeam with immoveable ends, imposed by a centralized external force. Considering the mid-plane stretching effect, the governing ordinary differential equation (ODE) of the considered nanobeam is derived based on nonlocal strain gradient theory and using Galerkin projection. In order to overcome the problem of choosing inappropriate parameters in the self-organizing part, a self-organizing fuzzy sliding mode controller is constructed to modify the parameters. Another fuzzy controller is designed and has the role of imposing controller output to regulate the system response. The sliding surface and its changes are determined as the controller signal inputs for obtaining a better performance. An adaptive law is used to validate the stability and improve the system's performance by modifying the fuzzy controller coefficients and reducing the chattering phenomena and overcoming the issue of dead-zone. Furthermore, Lyapunov stability proof is presented, and the numerical simulations are the showcase of the superior performance of the proposed controller.

A Lower Limb Rehabilitation Assistance Training Robot System Driven by an Innovative Pneumatic Artificial Muscle System.

This study aims to develop the application of pneumatic artificial muscle (PAM) for a 2-degrees of freedom (2-DOF) lower limb rehabilitation assistance training robot system. The proposed lower limb robot system can be divided into two axes, such as hip joint and knee joint. Each joint contains a pneumatic proportional valve to control a single-PAM with a torsion spring to simulate joint extension and flexion bionics characteristics and achieve a human-like 2-DOF lower limb robot system design and experimental prototype system. By analyzing the kinematics, the derived kinematics conforms to the lower limb motion pattern of the moving human body. Single PAM is difficult to achieve high accuracy control due to the different characteristics between extension and contraction. In our previous research, dual PAMs have been developed to drive a rotational joint which can achieve better control accuracy, however, cannot be suitable for multiaxial robotic design. The mechanism will become very complex and result in lower response and control accuracy. Thus, in this article the novel concept using single PAM with torsion spring was proposed to drive a joint to achieve two-axial robotic design. It has the advantage of multiaxial mechanism design, but the difficulty in joint control due to motion nonlinearity between contraction and extension. The torsion spring can improve motion nonlinearity between contraction and extension partly. Thus, the joint controller using adaptive self-organizing fuzzy sliding mode controller (ASOFSMC) was developed to solve this problem and achieve the required control performance for the joint angle positioning and gait planning control. Through the novel combination of single PAM, torsion spring, and the ASOFSMC joint controller with novel mechanism design and controller design, the two-axial robot mechanism designs and achieves the required control accuracy. The experimental results show that ASOFSMC can effectively control a 2-DOF lower limb robot system, and can modify fuzzy rules online, and adapt to rapid changes in the external environment and load to improve system control performance. The results prove that the proposed innovative single-PAM with a torsion spring and the control strategy can achieve the performance of 2-DOF lower limb rehabilitation assistance training robot system.

Multimodal Vibration Control of Photo-Electric Laminated Thin Cylindrical Shells Via Self-Organizing Fuzzy Sliding Mode Control

In this paper, a novel multipiece actuator configuration is first proposed. This configuration exhibits several advantages over the existing ones, such as: (1) the ability to overcome the deficiency of one-way actuation of PbLaZrTi (PLZT) actuators and (2) all of the actuators in this configuration being placed on the inner surfaces of a thin cylindrical shell and the removal of extra electrical wires between the end surfaces of the actuators. A new index of modal control factors is defined, and an optimization method for allocating actuator is proposed. By using the proposed method, the PLZT actuators can be located in an optimum position. Moreover, in view of the nonlinear and time-variant characteristics of photostrictive actuators, a self-organizing fuzzy sliding mode control (SOFSMC) method is established to attenuate multimodal vibration of photo-electric laminated thin cylindrical shells. A multilevel sliding mode surface is defined as fuzzy input and the SOFSMC method is used to infer the applied light intensity. Its control rule bank can be developed and adjusted continuously via online learning. In addition, using fuzzy sliding mode, the chatter inherent in conventional sliding mode control is therefore managed effectively while ensuring sliding mode behavior. Case studies demonstrate that the proposed approach can efficiently suppress multimodal vibration of photo-electric laminated thin cylindrical shells. It is also founded that SOFSMC can achieve better control effect than fuzzy neural network control (FNNC).

Enhanced Adaptive Self-Organizing Fuzzy Sliding-Mode Controller for Active Suspension Systems

A self-organizing fuzzy controller (SOFC) is proposed to control engineering applications. However, its stability is difficult to demonstrate. Therefore, the parameters of the SOFC must be carefully chosen to ensure that the system controlled by the SOFC can operate stably. To overcome the problem, this study developed an enhanced adaptive self-organizing fuzzy sliding-mode controller (EASFSC) for active suspension systems. Rather than using the output error and the error change of the system, the EASFSC uses a sliding surface and its differential as the input variables of a fuzzy logic controller (FLC) in the SOFC to generate a control input through fuzzy operation. It also applies an adaptive law to modify the fuzzy consequent parameter of the FLC in the SOFC to improve the stability of the system. The stability of the EASFSC was proven using the Lyapunov stability theorem. The EASFSC eliminates the problem of an SOFC implementation in determining the stability of the system and overcomes the difficulty of finding appropriate membership functions and fuzzy rules for designing an FLC. To confirm the applicability of the EASFSC, this study used the EASFSC to manipulate an active suspension system to improve its control performance. Experimental results showed that the EASFSC achieved better control performance than the SOFC for active suspension control.

Enhanced adaptive grey-prediction self-organizing fuzzy sliding-mode controller for robotic systems

A grey-prediction self-organizing fuzzy controller (GPSOFC) has been proposed to control robotic systems. It solves the problems caused by the inappropriate selection of parameters in a self-organizing fuzzy controller (SOFC) and eliminates the dynamic coupling effects between degrees of freedom (DOFs) in robotic systems. However, its stability is difficult to demonstrate. To overcome the stability issue, this study developed an enhanced adaptive grey-prediction self-organizing fuzzy sliding-mode controller (EAGSFSC) for robotic systems. The EAGSFSC not only solves the problem of a GPSOFC implementation by determining the stability of the system but also applies an adaptive law to modify the fuzzy consequent parameter of a fuzzy logic controller for manipulating a robotic system to improve its control performance. The stability of the EAGSFSC was proven using the Lyapunov stability theorem. To confirm the suitability of the proposed method, this study applied the EAGSFSC to manipulate a 6-DOF robot to determine its control performance. Experimental results showed that the EAGSFSC achieved better control performance than the GPSOFC as well as the SOFC for robotic motion control.

Intelligent Pitch Control for a 2MW Wind Turbine

The objective of the paper is to develop a novel intelligent pitch control system of a 2MW wind turbine driven by variable-speed hydraulic pump-controlled system. For realizing the intelligent pitch controller, self-organizing fuzzy sliding mode control, which combines fuzzy sliding mode control and self-organizing modifier, is proposed. In order to verify the proposed concept experimentally, a full-scale test rig of the hydraulic pitch control system of a 2MW wind turbine blades, including a novel mechanism of pitch control, a variable-speed hydraulic pump-controlled system, a disturbance system and a PC-Based control system, are designed and set up. The variable-speed pump-controlled hydraulic servo system contains an AC servo motor and a constant displacement hydraulic piston pump. In order to compare the control performance, the pitch control experiments by fuzzy sliding mode control and by self-organizing fuzzy sliding mode control are implemented respectively for different path profiles and different disturbance torque. Finally, the experimental results clarify that the pitch control controlled by self-organizing fuzzy sliding mode control can perform better than that controlled by fuzzy sliding mode control.

Design of an enhanced adaptive self-organizing fuzzy sliding-mode controller for robotic systems

It is difficult to determine the stability of a self-organizing fuzzy controller (SOFC). Therefore, a system controlled using the SOFC cannot guarantee the stability of the system during the control process. To eliminate the problem caused by the SOFC, this study developed an enhanced self-organizing fuzzy sliding-mode controller (EASFSC) for robotic systems. Instead of using the system’s output error and its error change, the EASFSC uses a sliding surface and its differentiation as the input variables of a fuzzy logic controller (FLC) in the SOFC. Using the fuzzy operation, these variables generate a control input that ensures the stability of the system. The proposed method also employs an adaptive law to modify the fuzzy consequent parameter of the FLC in the SOFC to improve the control performance of the system. The stability of the EASFSC has been proven using the Lyapunov stability theorem. Simulation results of a two-link robotic manipulator application verified that the EASFSC provides superior control performance as compared with the SOFC.

Self organizing fuzzy sliding mode controller for the position control of a permanent magnet synchronous motor drive

In this paper, a self organizing fuzzy sliding mode controller (SOFSMC) which emulates the fuzzy controller with gain auto-tuning is proposed for a permanent magnet synchronous motor (PMSM) drive. The proposed controller is used for the position control of the PMSM drive. The performance and robustness of the control system is tested for nonlinear motor load torque disturbance and parameter variations. It has a novel gain self organizing strategy in response to the transient or tracking responses requirement. To illustrate the performance of the proposed controller, the simulation studies are presented separately for the SOFSMC and the fuzzy controller with gain auto-tuning. The results are compared with each other and discussed in detail. Simulation results showing the effectiveness of the proposed control system are confirmed under the different position changes.

Development of X-Y Servo Pneumatic-Piezoelectric Hybrid Actuators for Position Control with High Response, Large Stroke and Nanometer Accuracy

This study aims to develop a X-Y dual-axial intelligent servo pneumatic-piezoelectric hybrid actuator for position control with high response, large stroke (250 mm, 200 mm) and nanometer accuracy (20 nm). In each axis, the rodless pneumatic actuator serves to position in coarse stroke and the piezoelectric actuator compensates in fine stroke. Thus, the overall control systems of the single axis become a dual-input single-output (DISO) system. Although the rodless pneumatic actuator has relatively larger friction force, it has the advantage of mechanism for multi-axial development. Thus, the X-Y dual-axial positioning system is developed based on the servo pneumatic-piezoelectric hybrid actuator. In addition, the decoupling self-organizing fuzzy sliding mode control is developed as the intelligent control strategies. Finally, the proposed novel intelligent X-Y dual-axial servo pneumatic-piezoelectric hybrid actuators are implemented and verified experimentally.

An adaptive control system with self-organizing fuzzy sliding mode control strategy for micro wire-EDM machines

This paper aims to develop an adaptive control system for process monitoring, identification, and control in micro wire electrical discharge machining (wire-EDM). The proportion of short circuits in the total sparks defined as short circuit ratio is chosen as a control parameter for the adaptive control system. Pulse interval of each spark is adjusted in real-time according to the discrimination of gap status to improve the stability of machining operation. A self-organizing fuzzy sliding mode controller is then proposed for servo feed control. This intelligent control strategy has on-line learning capability and disturbance rejection robustness for responding to the nonlinear, stochastic, and time-varying characteristics of the micro wire-EDM process. Another fuzzy logic controller is designed to control the short circuit ratio at a pre-determined level through an on-line regulation of servo voltage for adaptive process control. Experimental results show that the developed adaptive control system results in faster machining and better machining stability than does a conventional control scheme.

An adaptive self-organizing fuzzy sliding mode controller for a 2-DOF rehabilitation robot actuated by pneumatic muscle actuators

Pneumatic muscle actuators have the highest power/weight ratio and power/volume ratio among actuators of all types. Therefore, they can be used not only in rehabilitation engineering, but also as actuators in robots, including industrial robots and therapy robots. It is difficult to achieve excellent control performance using classical control methods because the compressibility of gas and the nonlinear elasticity of bladder containers cause parameter variations. An adaptive self-organizing fuzzy sliding mode control (ASOFSMC) is developed in this study. Its fuzzy sliding surface can help reduce the number of fuzzy rule. The self-organizing learning mechanism is employed to modify fuzzy rules on-line. The model-matching technique is then adopted to adjust the scaling factors. Finally, the Lyapunov theory is employed to prove the stability of the ASOFSMC. Experimental results show that this control strategy can attain excellent control performance.

DEVELOPMENT OF AN INTELLIEGNT PNEUMATIC-PIEZOELECTRTC HYBRID SERVO POSITIONING SYSTEM WITH HIGH RESPONSE, LARGE STROKE AND NANOMETER ACCURACY

This investigation aims to develop an intelligent hybrid pneumatic-piezoelectric servo positioning system with high response, large stroke and nanometer precision. The rodless pneumatic cylinder serves to position in coarse stroke and the piezoelectric (PZT) actuator compensates fine stroke. Thus, the overall control systems become a dual-input single-output (DISO). Although the rodless pneumatic cylinder has relative higher friction force, it has the advantage of mechanism for multi-axes development. In order to develop an intelligent controller, self-organizing fuzzy sliding mode control theory (SOFSMC) is proposed here for the DISO system. SOFSMC is based on fuzzy sliding mode control (FSMC) combining with self-organizing strategy. Thus, SOFSMC has simple fuzzy rule base and on-line selforganizing ability. Besides, in order to reduce the coupling effects of the DISO system, a decoupling controller is developed. The experimental results clarify that the servo pneumatic-piezoelectric control system can achieve excellent positioning response and accuracy of 20 nm with high response for maximum stroke of 250 mm and multi-step positioning.

Parallel Control of Velocity Control and Energy-Saving Control for a Hydraulic Valve-Controlled Cylinder System Using Self-Organizing Fuzzy Sliding Mode Control.

Conventional hydraulic valve-controlled systems that incorporate positive displacement pumps and relief valves have a problem of low energy efficiency. The objective of the research is to implement parallel control of energy-saving control in an electro-hydraulic load-sensing system and velocity control in a hydraulic valve-controlled cylinder system to achieve both high velocity control accuracy and low input power simultaneously. The overall control system is a two-input two-output system. For that, the control strategy of self-organizing fuzzy sliding mode control (SOFSMC) is developed in this study to reduce the fuzzy rule number and to self-organize on-line the fuzzy rules. To compare the energy-saving performance, the velocity control is implemented under three different energy-saving control systems, such as load-sensing control system, constant supply pressure control system and conventional hydraulic system. The parallel control of the velocity control and energy-saving control by the SOFSMC is implemented experimentally.

Self-organizing fuzzy control for motor-toggle servomechanism via sliding-mode technique

The dynamic response of a self-organizing fuzzy sliding-mode-controlled toggle mechanism, which is driven by a permanent magnet synchronous servo motor, is studied in this paper. First, based on the principle of fuzzy control, a self-organizing fuzzy control (SOFC) system is developed to control the position of a slider of the motor-toggle servomechanism. Moreover, to reduce the control rules in the design of the SOFC system and to strengthen the robust characteristics, a self-organizing fuzzy sliding-mode control (SOFSMC) is proposed to control the motor-toggle servomechanism. The proposed SOFC and SOFSMC systems contain two sets of fuzzy inference logic: one is the fuzzy controller and the other is the rule modifier. A new fuzzy learning method of the rule modifier is developed, where the modification value of each rule is based on the fuzzy firing weight. The proposed SOFC and SOFSMC systems can automatically tune the rules bases to achieve satisfactory performance, so that they can be applied for on-line learning, real-time control. In addition, simulated and experimental results due to periodic step and sinusoidal commands show the dynamic behaviors of the proposed SOFC and SOFSMC systems are robust with regard to parameter variations and external disturbances. Comparison between SOFC and SOFSMC also shows that the SOFSMC can reduce implementation complex while defining the sliding surface.

A self-organizing fuzzy sliding-mode controller design for a class of nonlinear servo systems

A self-organizing fuzzy controller to augment a sliding-mode control (SOFSMC) scheme for a class of nonlinear systems is proposed. The motivation behind this scheme is to combine the best features of self-organizing fuzzy control and sliding-mode control to achieve rapid and accurate tracking control of a class of nonlinear systems. The chatter encountered by most sliding-mode control schemes is greatly alleviated without sacrificing invariant properties. A stability analysis is presented; the design guidelines and the class of applicable systems are clearly identified. To verify the scheme, the authors performed experiments on its implementation in a magnetic levitation system. The results show that both alleviation of chatter and robust performance are achieved; the advantages of the scheme are indicated in comparison with the conventional sliding-mode design. >