Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Proportional integral plus multi-frequency resonant current controller for grid-connected voltage source converter under imbalanced and distorted supply voltage conditions

This paper proposes a current control scheme for a grid-connected pulse width modulator(PWM) voltage source converter(GC-VSC) under imbalanced and distorted supply voltage conditions.The control scheme is implemented in the positive synchronously rotating reference frame and composed of a single proportional integral(PI) regulator and multi-frequency resonant controllers tuned at the frequencies of 2ω and 6ω,respectively.The experimental results,with the target of eliminating the active power oscillations and current harmonics on a prototype GC-VSC system,validate the feasibility of the proposed current control scheme during supply voltage imbalance and distortion.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

船用汽轮机变工况的遗传粒子群优化智能控制方法研究

为提升船用汽轮发电机组大幅变工况时的控制精度和鲁棒性,以船用汽轮机调节系统各部件的模块化数学模型为基础,建立汽轮机组数字电液(digital electric hydraulic,DEH)闭环模糊比例、积分、微分(proportion integration derivative,PID)控制模型;融合遗传算法的选择、交叉、变异和自适应递减权重法,提出遗传粒子群智能优化算法,并结合标准测试函数验证提出算法具有较高的收敛速度和精度;基于遗传粒子群智能优化算法建立汽轮机变工况自适应智能模糊PID控制模型,实现模糊PID的量化因子与比例因子最优化设计,进而开展船用汽轮发电机组大幅变工况动态特性及扰动因素影响分析,结果表明本文建立的自适应智能模糊PID控制模型具有更好的控制稳态性能与鲁棒性,为船用汽轮机组大幅度变工况智能控制优化设计提供了有力的技术支撑。

Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical networks.Therefore,in order to avoid this issue,WTs hybridization with a storage system is a mandatory.This paper investigates WT system operating at variable speed.The system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is proposed.Meanwhile,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal gains.To compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working conditions.The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.

Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

During the drilling process,stick-slip vibration of the drill string is mainly caused by the nonlinear friction gen-erated by the contact between the drill bit and the rock.To eliminate the fatigue wear of downhole drilling tools caused by stick-slip vibrations,the Fractional-Order Proportional-Integral-Derivative(FOPID)controller is used to suppress stick-slip vibrations in the drill string.Although the FOPID controller can effectively suppress the drill string stick-slip vibration,its structure isflexible and parameter setting is complicated,so it needs to use the cor-responding machine learning algorithm for parameter optimization.Based on the principle of torsional vibration,a simplified model of multi-degree-of-freedom drill string is established and its block diagram is designed.The continuous nonlinear friction generated by cutting rock is described by the LuGre friction model.The adaptive learning strategy of genetic algorithm(GA),particle swarm optimization(PSO)and particle swarm optimization improved(IPSO)by arithmetic optimization(AOA)is used to optimize and adjust the controller parameters,and the drill string stick-slip vibration is suppressed to the greatest extent.The results show that:When slight drill string stick-slip vibration occurs,the FOPID controller optimized by machine learning algorithm has a good effect on suppressing drill string stick-slip vibration.However,the FOPID controller cannot get the drill string system which has fallen into serious stick-slip vibration(stuck pipe)out of trouble,and the machine learning algorithm is required to mark a large amount of data on adjacent Wells to train the model.Set a reasonable range of drilling parameters(weight on bit/drive torque)in advance to avoid severe stick-slip vibration(stuck pipe)in the drill string system.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Harmonics Extraction Scheme for Power Quality Improvement Using Chbmli-Dstatcom Module

In recent day’s power distribution system is distress from acute power quality issues.In this work,for compensating Power Quality(PQ)disturbances a seven level cascaded H-bridge inverter is implemented in distribution static com-pensator which protects power quality problems in currents.Distribution Static Compensator(DSTATCOM)aid to enhances power factor and removes total har-monic distortion which is drawn from non-linear load.The D–Q reference theory based hysteresis current controller is employed to generate reference current for compensation of harmonics and reactive power,additionally Probabilistic Neural Network(PNN)classifier is used which easily separates exact harmonics.In the meantime fuzzy logic controller is also used to maintain capacitor DC-link poten-tial.When comparing to PI controller it decreases steady state time and reduces maximum peak overshoot.Cascaded H-bridge multilevel inverter converts direct current to Alternating current,through inductor opposite harmonics are injected in Power Control Centre reduces source current harmonics and reactive power.The implementation of CHBMLI in distribution STATic COMpensator simulation model is simulated by means of MATLAB.

CONTROL OF ROBOT DRIVEN BY MULTIPLE ULTRASONIC MOTORS BASED ON ROBUST PARAMETER DESIGN

An ultrasonic motor （USM） is difficlt to be mathematically described because of its complex energy conversion and nonlinear parameters from increasing temperature and changing operating conditions. To achieve good performance of a three-joint robot directly driven by USM, according to the operating characteristics of USM, a new position-velocity feedback control strategy is proposed. In the control strategy, there are a total of 18 controller gains to he tuned. Through a series of ＂Design of Experiments＂ by the robust parameter design, an optimal and robust set of proportional integral derivative （PID） controller gains is obtained. Results show that the control strategy can achieve the best performance of the robot and the robust parameter design is effective and convenient to USMs.

广义预测控制和PID控制在混凝投药中的应用

针对水处理过程中混凝投药的非线性和时滞特点,分析了其混凝投药的工作原理,采用传统的控制方法难以实现很好的控制效果.提出了一个混凝投药的方案,把广义预测控制算法和PID(proportion-integralderivative)控制算法结合起来,通过预测被控系统的若干个时刻的未来输出值,得到一个新的性能优化函数,通过实时优化被控对象的控制参数,计算出一个合理的混凝投药量.最后,采用Visual Basic软件编程完成该控制方案,并通过对混凝投药自动化控制的现场实验,得到较好的输出控制结果,从而验证了该控制方案的可行性.

Active Damping of Milling Vibration Using Operational Amplifier Circuit

The problem of chatter vibration is associated with adverse consequences that often lead to tool impairment and poor surface finished in a workpiece, and thus, controlling or suppressing chatter vibrations is of great significance to improve machining quality. In this paper, a workpiece and an actuator dynamics are considered in modeling and controller design. A proportional-integral controller(PI) is presented to control and actively damp the chatter vibration of a workpiece in the milling process. The controller is chosen on the basis of its highly stable output and a smaller amount of steady-state error. The controller is realized using analog operational amplifier circuit. The work has contributed to planning a novel approach that addresses the problem of chatter vibration in spite of technical hitches in modeling and controller design. The method can also lead to considerable reduction in vibrations and can be beneficial in industries in term of cost reduction and energy saving. The application of this method is verified using active damping device actuator(ADD) in the milling of steel.

Improved single-neuron PID controller for DC motor applied in robot system

An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.

PSO Based Multi-Objective Approach for Controlling PID Controller

CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system efficiency.It has a highly nonlinear characteristic that includes complexities in its control and design.Dynamic performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for CSTR.The reactor temperature changes in either direction from the defined reference value.It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass quality.Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential.In this paper,a conventional Proportional Integral Derivative(PID)controller is designed.The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters.Hence,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation.In the proposed technique,PID parameters are tuned by Particle Swarm Optimization(PSO).It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response.In this article,a multi-objective function is proposed for PSO based controller design of CSTR.

Simulation study on starting of dual clutch transmission for tracked vehicles

In order to study the application of dual clutch transmission （DCT） on tracked vehicles, a simulation moclel and two control methods were performed for starting analysis. Based on a certain transmission of an existing tracked vehicle, a DCT structure was proposed. Matlab/Simulink was a dopted as a platform to develop the simulation model. The engine speed was controlled to follow the target speed as a launch strategy. Two control methods, a proportional integral derivative （ PID ） control method and a fuzzy control method, were proposed to control the engine throttle and oil pressure in order to track the target engine speed. Simulation results show that either the PID control or fuzzy control method can improve the starting performance compared with no loop control meth od. Fuzzy control method can lead a better starting quality compared with PID control method.

Performance analysis of semi-active cab’s hydraulic system of the vibratory roller using optimal fuzzy-PID control

In order to evaluate the performance of semi-active cab’s hydraulic mounts(SHM)of the off-road vibratory roller with the optimal fuzzy-PID(proportional integral derivative)control,a nonlinear dynamic model of the vehicle interacting with off-road terrains is established based on Matlab/Simulink software.The weighted root-mean-square(RMS)acceleration responses of the driver’s seat heave and the cab’s pitch angle are chosen as objective functions.The SHM is then optimized and analyzed via the optimal fuzzy-PID control under different operation conditions.The simulations results show that the driver’s ride comfort and the cab shaking are greatly affected by the off-road terrains under various operating conditions of the vehicle,especially at the speed from 8 to 12 km/h on a very poor terrain surface of Grenville soil ground under the vehicle travelling.With SHM using the optimal fuzzy-PID control,the driver’s ride comfort and the cab shaking are clearly improved under various operation conditions of the vehicle,particularly at the speed from 6 to 7 km/h of the vehicle traveling.

Trajectory tracking control of the bionic joint of the musculoskeletal leg mechanism

Pneumatic artificial muscles(PAMs) have properties similar to biological muscles,which are widely used in robotics as actuators.It is difficult to achieve high-precision position control for robotics system driven by PAMs.A 3-DOF musculoskeletal bionic leg mechanism is presented,which is driven by PAMs for quadruped robots.PAM is used to simulate the compliance of biological muscle.The kinematics of the leg swing is derived,and the foot desired trajectory is planned as the sinusoidal functions.The swing experiments of the musculoskeletal leg mechanism are conducted to analyse the extension and flexion of joints.A proportional integral derivative(PID) algorithm is presented for controlling the flexion/extension of the joint.The trajectory tracking results of joints and the PAM gas pressure are obtained.Experimental results show that the developed leg mechanism exhibits good biological properties.

Automatic measurement of air-pressure sensor based on two-pressure control instrument

To measure the performance of high precision air-pressure sensors in below normal pressure,an automatic measurement instrument has been designed and implemented.It can simulate environment of low pressure from 300hPa to 1 000hPa with high accuracy by proportional-integral-derivative(PID)control quickly,and it can also generate various relative humidity by two-pressure control.The results show that this instrument can reach controlled pressure quickly.And it works well with the minimum average pressure difference,and the fluctuation is±0.02hPa at 500hPa.And it can keep in a stable status for a long time.It works well in performance testing of pressure sensors.The structure of the system is simple,takes small investment,and can be operated conveniently.

A discrete PI fault observer design and application in variable speed wind turbine system

For the discrete-time system which is subjected to uncoupled actuator faults and sensor faults simultaneously,a robust fault diagnosis method based on a proportional integral observer (PIO) is presented.The proposed PIO uses an additionally introduced integral term of the output errors to obtain the estimationof actuator faults. Besides, the sensor faults are regarded as the augment states so that the PIO cantrace them. Moreover, the convergence of the PIO is proved. A variable speed wind turbine(VWT) exampleis given to demonstrate the fast convergence and diagnosis precision of the proposed PIO.