A hybrid fuzzy logic and neural network algorithm for robot motioncontrol

Robotic manipulators are multivariable nonlinear coupling dynamic systems. Industrial robots were controlled by using a traditional controller, the control performance of which may change with respect to operating conditions. Since the robotic manipulators have complicated nonlinear mathematical models, control systems based on the system model are difficult to design. In this paper, a model-free hybrid fuzzy logic and neural network algorithm was proposed to control this multi-input/multi-output (MIMO) robotic system. First, a fuzzy logic controller was designed to control individual joints of this 4-degree-of-freedom (DOF) robot. Secondly, a coupling neural network controller was introduced to take care of the coupling effect among joints and refine the control performance of this robotic system. The experimental results showed that the application of this control strategy effectively improved the trajectory tracking precision     

Design of a mixed fuzzy controller for multiple-input multiple-output systems

Multiple-input multiple-output (MIMO) systems usually have characteristics of nonlinear dynamics coupling. Therefore, the difficulty in controlling MIMO systems is how to overcome the coupling effects between the degrees of freedom. The computational burden and dynamic uncertainty associated with MIMO systems make model-based decoupling impractical for real-time control. This work develops a mixed fuzzy controller (MFC) to solve this problem and improve control performance. This study first designs a traditional fuzzy controller (TFC) from the viewpoint of a single-input single-output (SISO) system for controlling each degree of freedom of a MIMO system. Then, an appropriate coupling fuzzy controller is also designed according to the characteristics of the system’s dynamics coupling and incorporated into a TFC to compensate for coupling effects between the degrees of freedom. This control strategy can not only simplify the implementation problem of fuzzy control, but also improve control performance. The state-space approach for analyzing the stability of fuzzy control systems is applied to evaluate the stability and robustness of this intelligent mixed fuzzy controller. To verify the applicability of the proposed mixed fuzzy controller, this work presents a two-link robotic manipulator with a complex dynamic model for a MIMO system to evaluate the stability and robustness of the MFC by numerical simulation, and to examine the control performance by comparing the simulation results of the MFC with those of a TFC for this MIMO system.     

New hybrid fuzzy controller for direct torque control induction motor drives

A new hybrid fuzzy controller for direct torque control (DTC) induction motor drives is presented in this paper. The newly developed hybrid fuzzy control law consists of proportional-integral (PI) control at steady state, PI-type fuzzy logic control at transient state, and a simple switching mechanism between steady and transient states, to achieve satisfied performance under steady and transient conditions. The features of the presented new hybrid fuzzy controller are highlighted by comparing the performance of various control approaches, including PI control, PI-type fuzzy logic control (FLC), proportional-derivative (PD) type FLC, and combination of PD-type FLC and I control, for DTC-based induction motor drives. The pros and cons of these controllers are demonstrated by intensive experimental results. It is shown that the presented induction motor drive is with fast tracking capability, less steady state error, and robust to load disturbance while not resorting to complicated control method or adaptive tuning mechanism. Experimental results derived from a test system are presented confirming the above-mentioned claims.     

Dual Servo Control of a High-Tilt 3-DOF Microparallel Positioning Platform

This paper presents a precise positioning control of a microparallel positioning platform using a dual-stage servo system. The result of the research can be applied to dual-stage-type parallel machines for improving the positioning accuracy. The proposed platform adopts a dual-stage system that consists of three coarse actuators and three fine actuators to realize 3 degrees of freedom (DOF) motion. The 3-DOF motion of the end-effector is measured by a set of three linear sensors. Dynamic models for the coarse and fine actuators are derived by the system identification approach. The gain-scheduled multi-input multi-output (MIMO) controllers are synthesized based on the modeling. The MIMO controller is designed with a mixed-sensitivity criterion on tracking performance and positioning capability, and the design of the gain scheduler is based on the kinematics change. By integrating the controllers for two kinds of actuators, a dual servo controller can be developed based on the master-slave with decoupling structure. An antiwindup controller and a feedforward compensator are adopted to improve the performance. The successful performance of the synthesized dual servo controller is validated through experiments on tracking to guarantee submicrometer accuracy.     

光电跟踪系统的模糊Ⅱ型控制技术研究

为了解决高型控制方法在光电伺服跟踪系统应用中存在的稳态精度与超调量之间的矛盾,设计了一种由多种群遗传算法(MPGA)优化的模糊Ⅱ型控制方法.该方法在经典Ⅰ型双闭环反馈控制器的速度环之前并联一个积分环节,将系统型别增加到Ⅱ型,以此加快反应速度、减小稳态误差;并引入模糊控制器(FLC),根据系统状态动态调节积分环节的增益,...     

Hybrid fuzzy proportional-integral plus conventional derivativecontrol of linear and nonlinear systems

This paper presents a new approach toward the optimal design of a hybrid proportional-integral-derivative (PID) controller applicable for controlling linear as well as nonlinear systems using genetic algorithms (GAs). The proposed hybrid PID controller is derived by replacing the conventional PI controller by a two-input normalized linear fuzzy logic controller (FLC) and executing the conventional D controller in an incremental form. The salient features of the proposed controller are as follows: (1) the linearly defined FLC can generate nonlinear output so that high nonlinearities of complex systems can be handled; (2) only one well-defined linear fuzzy control space is required for both linear and nonlinear systems; (3) optimal tuning of the controller gains is carried out by using a GA; and (4) it is simple and easy to implement. Simulation results on a temperature control system (linear system) and a missile model (nonlinear system) demonstrate the effectiveness and robustness of the proposed controller     

Motion synchronization for dual-cylinder electrohydraulic liftsystems

This paper presents a nonlinear control algorithm to address the motion synchronization problem for a dual-cylinder electrohydraulic (EH) lift system. A two-step design approach is applied that utilized linear multiple input-multiple output (MIMO) robust control technique to design an outer-loop motion synchronization controller. A nonlinear single input-single output (SISO) perturbation observer-based pressure-force controller is designed for each of the lift cylinders as the inner-loop controller to handle the nonlinearities associated with the EH actuators. Experimental results on a 2-cylinder lift system verified the effectiveness of the proposed approach     

Fuzzy motion control of an auto-warehousing crane system

Fuzzy motion control of an auto-warehousing crane system is presented in this paper. Using the concept of linguistic variable, a fuzzy logic controller (FLC) can convert the knowledge and experience of an expert into an automatic control strategy. The designed FLC with a rule base and three sets of parameters is used to control the crane system in x, y, and z directions. The unloaded weight and the fully loaded weight of the crane system in discussion are 1.35×10⁴ kg and 1.5×10⁴ kg, respectively. For various loading conditions and varying distances, the FLC still controls the crane system very well with positioning accuracy less than 2×10 ^-3 m for all directions. The distance-speed reference curve for control of the crane system is designed to meet the engineering specifications of motion such as acceleration, deceleration, maximum speed, and creep speed in each direction, and is generated automatically according to varying distance. The method for designing the distance-speed reference curve can make the crane move at relatively high speed to approach the target position. Simulations of the motion control in the three directions are demonstrated     

Lyapunov-function-based design of fuzzy logic controllers and itsapplication on combining controllers

This paper presents the design of fuzzy logic controllers (FLCs) for nonlinear systems with guaranteed closed-loop stability and its application on combining controllers. The design is based on heuristic fuzzy rules. Although each rule in the FLC refers to a stable closed-loop subsystem, the overall system stability cannot be guaranteed when all these rules are applied together. In this paper, it is proved that if each subsystem is stable in the sense of Lyapunov (ISL) under a common Lyapunov function, the overall system is also stable ISL. Since no fuzzy plant model is involved, the number of subsystems generated is relatively small, and the common Lyapunov function can be found more easily. To probe further, an application of this design approach to an inverted pendulum system that combines a sliding-mode controller (SMC) and a state feedback controller (SFC) is reported. Each rule in this FLC has an SMC or an SFC in the consequent part. The role of the FLC is to schedule the final control under different antecedents. The stability of the whole system is guaranteed by the proposed design approach. More importantly, the controller thus designed can keep the advantages and remove the disadvantages of the two conventional controllers     

基于dSPACE的三相PWM整流器最优控制

PWM整流器系统通常采用双闭环控制。其电流环为一多输入多输出强耦合的系统,普遍应用PI调节器结合前馈解耦的方法。本文针对电流环的特点,设计了LQR调节器,进一步提高了控制系统的性能。本文选取id,iq作为系统状态变量,建立PWM整流器电流环的系统状态方程,通过求解Riccati方程得到所求控制器。搭建了基于dSPACE...     

High-Speed Control of IPMSM Drives Using Improved Fuzzy Logic Algorithms

This paper presents an improved fuzzy logic controller (FLC) for an interior permanent magnet synchronous motor (IPMSM) for high-performance industrial drive applications. In the proposed control scheme for high-speed operations above the rated speed, the operating limits of IPMSM are expanded by incorporating the maximum torque per ampere operation in constant torque region and the flux-weakening operation in constant power region. The power ratings of the motor and the inverter are considered in developing the control algorithm. A new and simple FLC is utilized as a speed controller. The FLC is developed to have less computational burden, which makes it suitable for real-time implementation, particularly at high-speed operating conditions. The complete drive is implemented in real-time using digital signal processor (DSP) controller board DS 1102 on a laboratory 1-hp IPM motor. The efficiency of the proposed control scheme is evaluated through both experimental and computer simulation results. The proposed controller is found to be robust for high-speed applications     

Fuzzy Feedback Linearization Control for MIMO Nonlinear System and Its Application to Full-Vehicle Suspension System

The paper presents a novel fuzzy feedback linearization control of nonlinear multi-input multi-output (MIMO) systems for the tracking and almost disturbance decoupling (ADD) performances based on the fuzzy logic control (FLC). The main contribution of this study is to construct a controller, under appropriate conditions, such that the resulting closed-loop system is valid for any initial condition and bounded tracking signal with the following characteristics: input-to-state stability with respect to disturbance inputs and almost disturbance decoupling. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. As soon as the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control immediately is applied via a human expert’s knowledge to improve the convergence rate. One example, which cannot be solved by the previous paper on the almost disturbance decoupling problem, is proposed in this paper to exploit the fact that the tracking and the almost disturbance decoupling performances are easily achieved by the proposed approach. In order to demonstrate the applicability, this paper has investigated a full-vehicle suspension system.     

A Control System for Rotary Blood Pumps Based on Suction Detection

A control system for rotary ventricular assist devices was developed to automatically regulate the pumping speed of the device to avoid ventricular suction. The control system comprises a suction detector and a fuzzy logic controller (FLC). The suction detector can correctly classify pump flow patterns, using a discriminant analysis (DA) model that combines several indices derived from the pump flow signal, to classify the pump status as one of the following: no suction (NS), moderate suction (MS), and severe suction (SS). The discriminant scores, which are the output of the suction detector, were used as inputs to the FLC. Based on this information, the controller updates pump speed, providing adequate flow and pressure perfusion to the patient. The performance of the control system was tested in simulations over a wide range of physiological conditions, including hypertension, exercise, and strenuous exercising for healthy, sick, and very sick hearts, using a lumped parameter model of the circulatory system coupled with a left ventricular assist device. The controller was able to maintain cardiac output and mean arterial pressure within acceptable physiologic ranges, while avoiding suction, demonstrating the feasibility of the proposed control system.     

Fuzzy-PI-based centralised control of semi-isolated FP-SEPIC/ZETA BDC in a PV/battery hybrid system

Multiport converters with centralised controller have been most commonly used in stand-alone photovoltaic (PV)/battery hybrid system to supply the load smoothly without any disturbances. This study presents the performance analysis of four-port SEPIC/ZETA bidirectional converter (FP-SEPIC/ZETA BDC) using various types of centralised control schemes like Fuzzy tuned proportional integral controller (Fuzzy-PI), fuzzy logic controller (FLC) and conventional proportional integral (PI) controller. The proposed FP-SEPIC/ZETA BDC with various control strategy is derived for simultaneous power management of a PV source using distributed maximum power point tracking (DMPPT) algorithm, a rechargeable battery, and a load by means of centralised controller. The steady state and the dynamic response of the FP-SEPIC/ZETA BDC are analysed using three different types of controllers under line and load regulation. The Fuzzy-PI-based control scheme improves the dynamic response of the system when compared with the FLC and the conventional PI controller. The power balance between the ports is achieved by pseudorandom carrier modulation scheme. The response of the FP-SEPIC/ZETA BDC is also validated experimentally using hardware prototype model of 500 W system. The effectiveness of the control strategy is validated using simulation and experimental results.     

MIMO阵列波束形成方法研究

相控阵雷达无法分辨一个波束宽度内的2个目标,多输入多输出(Multi-Input Multi-Output,MIMO)雷达阵列各阵元发射正交信号,提高了阵列系统的自由度,改善了雷达阵列系统分辨性能。文中给出了MIMO阵列相关滤波器组分离目标回波信号的原理框图,并进行了MIMO阵列常规波束形成器和最小方差无失真响应(MVDR)波束形成器理论分析和仿真实验。仿真结果表明,MIMO阵列比常规相控阵列具有更高的角度分辨率。     

Fuzzy logic control-a taxonomy of demonstrated benefits

The motivations for fuzzy logic control (FLC) are illuminated by exploring the benefits obtained by application designers through its use. A context for this exploration is set with a discussion of the characteristics of control policies and of the general attributes of FLC. Each benefit is described by reference to reported FLC implementations in which the benefit is demonstrated. Based on common features of the example applications, application preconditions for obtaining each benefit are stated     

A fuzzy-logic-controlled single-stage converter for PV-poweredlighting system applications

This paper presents a fuzzy-logic-controlled single-stage power converter (SSC) for photovoltaic (PV)-powered lighting system applications. The SSC is the integration of a bidirectional buck-boost charger/discharger and a class-D series resonant parallel loaded inverter. The designed fuzzy logic controller (FLC) can control both the charging and discharging current, and can improve its dynamic and steady-state performance. Furthermore, a maximum power point tracker (MPPT) based on a perturb-and-observe method is also realized to effectively draw power from PV arrays. Both the FLC and the MPPT are implemented on a single-chip microprocessor. Simulated and experimental results obtained from the proposed circuit with an FLC have verified the adaptivity, robustness and feasibility     

Decentralized nonlinear adaptive control of an HVAC system

This paper presents a new decentralized nonlinear adaptive controller (DNAC) for a heating, ventilating, and air conditioning (HVAC) system capable of maintaining comfortable conditions under varying thermal loads. In this scheme, an HVAC system is considered to be two subsystems and controlled independently. The interactions between the two subsystems are treated as deterministic types of uncertain disturbances and their magnitudes are supposed to be bounded by absolute value. The decentralized nonlinear adaptive controller (DNAC) consists of an inner loop and an outer loop. The inner loop is a single-input fuzzy logic controller (FLC), which is used as the feedback controller to overcome random instant disturbances. The outer loop is a Fourier integral-based control, which is used as the frequency-domain adaptive compensator to overcome steady, lasting uncertain disturbances. The global DNAC controller ensures that the system output vector tracks a desired trajectory vector within the system bandwidth and that the tracking error vector converges uniformly to a zero vector. The simulated experimental results on the HVAC system show that the performance is dramatically improved.     

Two-degree-of-freedom control with robust feedback control for harddisk servo systems

A two-degree-of freedom (2 DOF) control structure is proposed for read/write head servo systems of hard disk drives (HDDs). This structure is applied to both track seeking and track following, and makes mode switches found in conventional HDD servo systems unnecessary. Two innovative features introduced in the paper are: 1) a new method for generating the reference signal for track seeking and 2) two robust feedback control schemes for rejection of disturbances; one scheme uses a disturbance observer (DOB), and the other uses adaptive robust control (ARC). Simulation results show that the 2 DOF structure with ARC provides better performance than either the conventional servo system with mode switches or the 2 DOF structure with DOB. Experimental results show the advantage of the new reference generation method and the use of the DOB-based robust controller