Improvement of machining characteristics of micro-EDM using transistor type isopulse generator and servo feed control

This paper describes the improvement of machining characteristics of micro electrical discharge machining (micro-EDM) using a newly developed transistor type isopulse generator and servo feed control. The RC generator is mainly applied in conventional micro-EDM even though the transistor type isopulse generator is generally more effective for obtaining higher removal rate, because the transistor type generator is unable to generate iso-duration discharge current pulses with small pulse duration (several dozen nano-seconds), which is the normal level for micro-EDM. A new transistor type isopulse generator was therefore developed using a current sensor with high frequency response. With the new transistor type isopulse generator developed, the pulse duration can be reduced to about 30 ns, which is equivalent to the pulse duration used in finishing by the conventional RC pulse generator for micro-EDM. In order to achieve stable machining and improve machining characteristics, a new servo feed control system for micro-EDM using average ignition delay time to monitor the gap distance was also developed. By integrating the transistor type isopulse generator with this new servo feed control system, we were able to obtain a removal rate of about 24 times higher than that of the conventional RC pulse generator with a constant feed rate in both semifinishing and finishing. The effectiveness of the servo feed control proved higher in finishing than in semifinishing, whereas the transistor type isopulse generator was more effective in semifinishing than in finishing.     

Interval type-2 fuzzy PID controller for uncertain nonlinear inverted pendulum system

In this paper, the interval type-2 fuzzy proportional–integral–derivative controller (IT2F-PID) is proposed for controlling an inverted pendulum on a cart system with an uncertain model. The proposed controller is designed using a new method of type-reduction that we have proposed, which is called the simplified type-reduction method. The proposed IT2F-PID controller is able to handle the effect of structure uncertainties due to the structure of the interval type-2 fuzzy logic system (IT2-FLS). The results of the proposed IT2F-PID controller using a new method of type-reduction are compared with the other proposed IT2F-PID controller using the uncertainty bound method and the type-1 fuzzy PID controller (T1F-PID). The simulation and practical results show that the performance of the proposed controller is significantly improved compared with the T1F-PID controller.     

Trajectory and vibration control of a flexible joint manipulator using interval type-2 fuzzy logic

This study presents the development of a novel interval type-2 fuzzy logic controller for real time trajectory and vibration control of a flexible joint manipulator. The controller is designed on the Mamdani based interval type-2 fuzzy logic toolbox, which is developed by the authors, using interval triangular membership functions and Karnik–Mendel type reduction algorithm. The closed-loop stability of the system is proved based on Lyapunov stability theorem. In order to observe the effectiveness and robustness of the proposed controller to variations of system parameters (change in link length and payload), the experimental results of interval type-2 and conventional type-1 fuzzy logic controllers are compared. The results show that proposed controller clearly improves the link vibration and trajectory tracking behavior of the system.     

A novel interval type-2 fractional order fuzzy PID controller: Design,performance evaluation,and its optimal time domain tuning

In this paper, a novel concept of an interval type-2 fractional order fuzzy PID (IT2FO-FPID) controller, which requires fractional order integrator and fractional order differentiator, is proposed. The incorporation of Takagi-Sugeno-Kang (TSK) type interval type-2 fuzzy logic controller (IT2FLC) with fractional controller of PID-type is investigated for time response measure due to both unit step response and unit load disturbance. The resulting IT2FO-FPID controller is examined on different delayed linear and nonlinear benchmark plants followed by robustness analysis. In order to design this controller, fractional order integrator-differentiator operators are considered as design variables including input-output scaling factors. A new hybridized algorithm named as artificial bee colony-genetic algorithm (ABC-GA) is used to optimize the parameters of the controller while minimizing weighted sum of integral of time absolute error (ITAE) and integral of square of control output (ISCO). To assess the comparative performance of the IT2FO-FPID, authors compared it against existing controllers, i.e., interval type-2 fuzzy PID (IT2-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), type-1 fuzzy PID (T1-FPID), and conventional PID controllers. Furthermore, to show the effectiveness of the proposed controller, the perturbed processes along with the larger dead time are tested. Moreover, the proposed controllers are also implemented on multi input multi output (MIMO), coupled, and highly complex nonlinear two-link robot manipulator system in presence of un-modeled dynamics. Finally, the simulation results explicitly indicate that the performance of the proposed IT2FO-FPID controller is superior to its conventional counterparts in most of the cases.     

CNC机床伺服系统中模糊自整定PID控制研究

在CNC机床伺服进给系统中,控制对象的位置、速度具有不确定性和非线性,很难去建立精确的数学模型,而常规PID控制器的参数无法随着被控对象参数的变化而及时调整。模糊控制降低了对被控对象数学模型的要求,只需把经验知识转化为控制策略,进而使模型难以确定的复杂系统得以有效的控制,模糊PID控制器结合了常规PID控制和模糊控制的优点,将其应用于CNC机床伺服进给系统中,在MATLAB环境下进行仿真分析,结果表明,模糊自整定PID控制器具有更好鲁棒性,改善了伺服进给系统的动态性能。     

Nonlinear dynamic systems identification using recurrent interval type-2 TSK fuzzy neural network – A novel structure

In this study, a novel structure of a recurrent interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural network (FNN) is introduced for nonlinear dynamic and time-varying systems identification. It combines the type-2 fuzzy sets (T2FSs) and a recurrent FNN to avoid the data uncertainties. The fuzzy firing strengths in the proposed structure are returned to the network input as internal variables. The interval type-2 fuzzy sets (IT2FSs) is used to describe the antecedent part for each rule while the consequent part is a TSK-type, which is a linear function of the internal variables and the external inputs with interval weights. All the type-2 fuzzy rules for the proposed RIT2TSKFNN are learned on-line based on structure and parameter learning, which are performed using the type-2 fuzzy clustering. The antecedent and consequent parameters of the proposed RIT2TSKFNN are updated based on the Lyapunov function to achieve network stability. The obtained results indicate that our proposed network has a small root mean square error (RMSE) and a small integral of square error (ISE) with a small number of rules and a small computation time compared with other type-2 FNNs.     

Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload

The interval type-2 fuzzy logic controller (IT2-FLC), with footprint of uncertainty (FOU) in membership functions (MF), has increasingly recognized for controlling uncertainties and nonlinearities. Within the ambit of this, the efficient interval type-2 fuzzy precompensated PID (IT2FP-PID) controller is designed for trajectory tracking of 2-DOF robotic manipulator with variable payload. A systematic strategy for optimizing the controller parameters along with scaling factors and the antecedent MF parameters for minimization of performance metric integral time absolute error (ITAE) is presented. Prominently, recently proposed optimization technique hybridizing grey wolf optimizer and artificial bee colony algorithm (GWO–ABC) is utilized for solving this high-dimensional constrained optimization problem. In order to witness effectiveness, the performance is compared with type-1 fuzzy precompensated PID (T1FP-PID), fuzzy PID (FPID), and conventional PID controllers. More significantly, the robustness of IT2FP-PID is examined for payload variation, model uncertainties, external disturbance, and noise cancellation. After experimental outcome, it is inferred that IT2FP-PID controller outperforms others and can be referred as a viable alternative for controlling nonlinear complex systems with higher uncertainties.     

Laminated fabrication of 3D queue micro-electrode and its application in micro-EDM

3D micro-electrode used in micro electrical discharge machining (micro-EDM) is difficult to be fabricated. Based on laminated object manufacturing (LOM) process, this paper superimposed multilayer 2D micro-structures together to fit out 3D micro-electrode and applied it in micro-EDM to process 3D micro-cavity mold. Firstly, 100-μm-thick Cu foils were cut by wire-electrical discharge machining (WEDM) to obtain multilayer 2D micro-structures, and then these 2D micro-structures were connected together to fit out 3D micro-electrode through vacuum pressure thermal diffusion welding. Secondly, under the effect of 80-V voltage, 0.2-MHz pulse frequency, 800-ns pulse width, and 4200-ns pulse interval, the 3D micro-electrode was applied in micro-EDM and 3D micro-cavity mold with high surface quality was obtained. Thirdly, in order to reduce the adverse impact of electrode wear on machining precision of 3D micro-cavity mold, 3D queue micro-electrode was used to process the same 3D micro-cavity mold, in which the first electrode is for rough machining and the others for fine machining. Finally, based on the above studies, two kinds of 3D queue micro-electrodes were fabricated, and the 3D micro-cavity molds with surface roughness Ra?=?0.48 μm were obtained through micro-EDM. Compared with the scanning 3D micro-EDM process, the 3D micro-cavity mold can be obtained through up and down reciprocating method of the 3D queue micro-electrode, featuring simple machining process and high efficiency.     

Development of a linear electrostrictive servo motor

This paper presents a linear electrostrictive servo motor with high resolution and large stroke for ultra-precision motion control. High thrust force is obtained by making use of an electromagnetic clamping mechanism with force magnifying structure in the motor design. An operator alterable iterative learning control algorithm is proposed for the motion control of the motor. A prototype is designed, fabricated and tested. Experimental results show that the prototype has a mechanical resolution of 0.02 μm, yaw error less than 2 μm and maximum thrust force of 30N. Applications of the motor include producing the servo feed motions required in micro electrical discharge machining (micro-EDM) system or as a motion control device for other precision machining systems.     

数控机床进给伺服系统模糊自适应PID仿真

针对传统的PID控制策略不能满足数控进给伺服系统的对控制性能要求。结合模糊控制理论,在传统PID控制基础上设计出一种基于模糊决策的模糊自适应PID控制器。运用模糊控制理论,对PID参数进行实时修改,使系统具有较好的自适应能力和较强的鲁棒性。在MATLAB环境下对进给伺服系统进行了动态仿真;仿真结果表明,模糊自适应PID控制器的控制性能远优于常规PID控制器,即使在外界干扰和系统工况发生变化时,此控制器也具有很好的快速响应特性和较强的鲁棒性。     

Fault tolerant control based on interval type-2 fuzzy sliding mode controller for coaxial trirotor aircraft

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopter control is proposed in presence of defects in the system. A control strategy based on the coupling of the interval type-2 fuzzy logic control and sliding mode control technique are used to design a controller. The main purpose of this work is to eliminate the chattering phenomenon and guaranteeing the stability and the robustness of the system. In order to achieve this goal, interval type-2 fuzzy logic control has been used to generate the discontinuous control signal. The simulation results have shown that the proposed control strategy can greatly alleviate the chattering effect, and perform good reference tracking in presence of defects in the system.     

基于模糊PID控制的数控进给伺服系统仿真研究

针对数控机床进给伺服系统数学模型难以建立的问题,提出了一种模糊PID控制器,将其引入到数控进给伺服闭环控制中。并在Simulink环境下进行了仿真实验,结果表明,与传统PID控制相比,模糊PID控制改善了伺服系统动态性能,超调量小、鲁棒性强和稳态精度高。     

A hybrid model using supporting vector machine and multi-objective genetic algorithm for processing parameters optimization in micro-EDM

In micro-electrical discharge machining (EDM), processing parameters greatly affect processing efficiency and stability. However, the complexity of micro-EDM makes it difficult to determine optimal parameters for good processing performance. The important output objectives are processing time (PT) and electrode wear (EW). Since these parameters influence the output objectives in quite an opposite way, it is not easy to find an optimized combination of these processing parameters which make both PT and EW minimum. To solve this problem, supporting vector machine is adopted to establish a micro-EDM process model based on the orthogonal test. A new multi-objective optimization genetic algorithm (GA) based on the idea of non-dominated sorting is proposed to optimize the processing parameters. Experimental results demonstrate that the proposed multi-objective GA method is precise and effective in obtaining Pareto-optimal solutions of parameter settings. The optimized parameter combinations can greatly reduce PT while making EW relatively small. Therefore, the proposed method is suitable for parameter optimization of micro-EDM and can also enhance the efficiency and stability of the process.     

High-efficiency approach for fabricating MTE rotor by micro-EDM and micro-extrusion

Micro-gas turbine engine（MTE） rotor is an important indicator of its property, therefore, the manufacturing technology of the microminiature rotor has become a hot area of research at home and abroad. At present, the main manufacturing technologies of the MTE rotor are directed forming fabrication technologies. However, these technologies have a series of problems, such as complex processing technology high manufacturing cost, and low processing efficiency, and so on. This paper takes advantage of micro electric discharge machining（micro-EDM） in the field of microminiature molds manufacturing, organizes many processing technologies of micro-EDM reasonably to improve processing accuracy, presents an integrated micro-EDM technology and its process flow to fabricate MTE rotor die, and conducts a series of experiments to verify efficiency of this integrated micro-EDM. The experiments results show that the MTE rotor die has sharp outline and ensure the good consistency of MTE rotor blades. Meanwhile, the MTE rotor die is applied to micro extrusion equipment, and technologies of micro-EDM and micro forming machining are combined based on the idea of the molds manufacturing, so the MTE rotor with higher aspect ratio and better consistency of blades can be manufactured efficiently. This research presents an integrated micro-EDM technology and its process flow, which promotes the practical process of MTE effectively.     

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter.The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller.Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults.     

Type-2 fuzzy model based controller design for neutralization processes

In this study, an inverse controller based on a type-2 fuzzy model control design strategy is introduced and this main controller is embedded within an internal model control structure. Then, the overall proposed control structure is implemented in a pH neutralization experimental setup. The inverse fuzzy control signal generation is handled as an optimization problem and solved at each sampling time in an online manner. Although, inverse fuzzy model controllers may produce perfect control in perfect model match case and/or non-existence of disturbances, this open loop control would not be sufficient in the case of modeling mismatches or disturbances. Therefore, an internal model control structure is proposed to compensate these errors in order to overcome this deficiency where the basic controller is an inverse type-2 fuzzy model. This feature improves the closed-loop performance to disturbance rejection as shown through the real-time control of the pH neutralization process. Experimental results demonstrate the superiority of the inverse type-2 fuzzy model controller structure compared to the inverse type-1 fuzzy model controller and conventional control structures.     

Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input - delay systems

In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller. By introducing a new adaptive compensator for the predictor and controller, the effects of the external disturbance, estimation errors of the unknown nonlinear functions, and future sate estimation errors have been eliminated. In the proposed method, using an appropriate Lyapunov function, the stability analysis as well as the adaptation laws is carried out for the T2FNN parameters in a way that all the signals in the closed-loop system remain bounded and the tracking error converges to zero asymptotically. Moreover, compared to the related existence predictive controllers, as the number of T2FNN estimators are reduced, the computation time in the online applications decreases. In the proposed method, T2FNN is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. The proposed T2FNNP controller is applied to a nonlinear inverted pendulum and single link robot manipulator systems with input time-varying delay and compared with a type-1 fuzzy sliding predictive (T1FSP) controller. Simulation results indicate the efficiency of the proposed T2FNNP controller.     

A type-2 fuzzy expert system based on a hybrid inference method for steel industry

In this paper, a novel type-2 fuzzy expert system for prediction the amount of reagents in desulfurization process of a steel industry in Canada is developed. In this model, the new interval type-2 fuzzy c-regression clustering algorithm for structure identification phase of Takagi–Sugeno (T–S) systems is presented. Gaussian Mixture Model is used to generate partition matrix in clustering algorithm. Then, an interval type-2 hybrid fuzzy system, which is the combination of Mamdani and Sugeno method, is proposed. The new hybrid inference system uses fuzzy disjunctive normal forms and fuzzy conjunctive normal forms for aggregation of antecedents. A statistical test, which uses least square method, is implemented in order to select variables. In order to validate our method, we develop three system modeling techniques and compare the results with our proposed interval type-2 fuzzy hybrid expert system. These techniques are multiple regression, type-1 fuzzy expert system, and interval type-2 fuzzy TSK expert system. For tuning parameters of the system, adaptive-network-based fuzzy inference system is used. Finally, neural network is utilized in order to reduce error of the system. The results show that our proposed method has less error and high accuracy.     

Fabrication of micro rods by twin-mirroring-wire tangential feed micro electrical discharge grinding

In micro electrical discharge machining (micro-EDM), the precision fabrication of cylindrical micro rods is difficult to achieve with a high processing efficiency. In order to overcome this challenge, this paper proposes a new processing method, which is denoted as twin-mirroring-wire tangential feed micro electrical discharge grinding (TMTF-WEDG). The machining principle, characteristics, and realization of the new method are firstly introduced. Then, the advantages of TMTF-WEDG in terms of machining efficiency and accuracy are demonstrated. The experimental results have shown that the machining efficiency can be increased to more than 70% in comparison with conventional tangential-feed wire electrical discharge grinding. It has also been proved that a minimum removal of material corresponding to a reduction of less than 1 μm in the diameter of a micro rod can be obtained by TMTF-WEDG. This considerably helps in improving the accuracy and repeatability of the machining process. A deviation of less than 1 μm on the diameter of a micro rod has been obtained in a length range of 800 μm. The process repeatability in machining five micro rods has been established to be below 2 μm. The proposed method is therefore of great significance for improving the machining efficiency and ensuring a high precision in the shaping process of cylindrical micro rods.     

基于Matlab/Simulink的电液位置伺服系统可视化仿真

建立了液压位置伺服系统的动力学模型。针对液压伺服系统难以精确控制的特点,把模糊控制理论引入了伺服系统,构造了模糊推理系统,设计了二维模糊控制器。基于Matlab/Simulink软件平台对电液位置伺服系统进行了可视化仿真,仿真结果显示所设计的二维模糊控制器在电液位置伺服系统中取得了良好的控制精度和稳定性。为研究设计多维模糊控制器以及多输入多输出模糊控制系统（MIMO）提供了思路和方法。