Resonance Suppression Strategy for Humanoid Robot Arm

To address the problem of resonance in the control of a robot arm,a resonance suppression strategy is proposed for a single-joint humanoid robot arm based on the proportionalresonant(PR)controller.First,an arm joint model of the humanoid robot is established.Then the influence of resonance frequency on the performance of the control system with the robot arm is analyzed.The voltage fluctuation of the drive motor caused by the changes in arm motion is recognized as the disturbance of the current loop.The PR controller has the characteristic of disturbance rejection at a specific frequency.The output fluctuation of the driving system caused by the change of arm motion state at the resonance frequency is suppressed.Therefore the output current of the inverter will not be affected by the vibration of the arm at the resonance frequency.Finally,the control system is verified by MATLAB/Simulink simulation.The simulation results demonstrate that the control strategy for the humanoid robot arm based on the PR controller can suppress the resonance of the arm effectively,improving the dynamic performance and system stability.

DEVELOPMENT AND USAGE OF SIGNAL PR OCESSING AND SOUND SITIMULATING SYSTEM CONTROLLED BY COMPUTER

In hearing physiological experiments and clinic tests,we need not only a signal processing system,but also a synchronous sound stimulator’ Most of stimulators we are now using are function generators which are independent to processing units,and can be controlled only by hand. Although some of them have ports through which they can be controlled by computer,but as they are designed for industrial aims,not for hearing research,most of them can’t generate the special waveforms we need. We use the TDT signal processing system and develop a software package have both usage. On the interface of the program we can control the sampling parameters and generate stimulating waveforms’

Energy Saving Analysis and Simulation for Home Electricity

This paper presents the energy saving method by applying the voltage control technique on a single-phase AC source to a thyristor rectifier and an IGBT inverter with LC filter. Based on the LC filter parameter, the values of the gain for the controller are obtainable. The proposed controller structure consists of two loops arranged in a cascaded model. The output of the first loop is the capacitor current. This current is added to the load current in order to obtain the current reference. This reference current value will be compared with the inverter current which produces the error signal to be fed into the second loop in the cascade system. The output of the second loop is the inverter voltage. This voltage is added to the load voltage to produce the voltage reference. This reference is fed to the pulse width modulation generator via the controller and compared with the triangular wave. This energy-saving circuit is designed in blocks using MATLAB Simulink.

Double-loop Control Structure Using Proportional Resonant and Sequence-decoupled Resonant Controllers in Static Coordinates for Dynamic Voltage Restorer

Among incidents on grids,the sag/swell voltage is considered as the most frequent incident.To solve this problem,custom power devices are used.In particular,the dynamic voltage restorer(DVR)is a modern and efficient customer device.DVRs are used to mitigate voltage sag/swells and harmonics on the load bus,thus protecting the sensitive loads.The DVR is a serial compensator that applies a voltage to the point of common coupling to maintain the voltage of sensitive load at the nominal value.To improve the performance of DVRs,in this study,the control strategy of the two-stage loop circuit is implemented.The external voltage control loop uses a sequence-decoupled resonant(SDR)controller,and the inner current-control loop uses the proportional resonant(PR)controller implemented in the stationary frameαβ.

Artificial neural network with modified rider optimization for design and control of PV-integrated quasi Z-source cascaded multilevel inverter system

The modeling of the controller for quasi Z-Source Cascaded Multilevel Inverter(qZSCMI)-dependent 3-phase grid-tie Photovoltaic(PV)power system is considered in this paper.The state-of-the-art controller requires precise conceptual models and sophisticated optimization principles based on the derived models.However,such processes are limited to known system models,which are uncertain in future systems.Here,the controller for 3-phase qZS-CMI is modeled based on two phases,and the source PV voltage and output grid current are controlled.In Phase I,optimized Proportional Integral(PI)controller is used for finding out the total PV voltage,and Phase II utilizes the optimized Proportional Resonant(PR)controller enabled with the Artificial Neural Network(ANN)for controlling the grid current.For two phases,the modified optimization algorithm called Fitness Enabled-Rider Optimization Algorithm(FE-ROA)is used.Moreover,in Phase II,ANN is trained in an offline mode with the exact dataset arranged by the proposed FE-ROA,and it guarantees the control of grid current.The two phases plan to optimize the gain of both PI and PR controllers respectively using the same proposed algorithm.The main objective of phase I is to lessen the error among the reference PV voltage,and measured voltage,and phase II is to lessen the error among the reference and measured grid current.Hence,the grid-tie current injection is achieved by the developed module,and system-level control offers independent Maximum Power Point Tracking(MPPT).Lastly,the performance of the proposed controller for qZS-CMI is compared over the other controllers and substantiates the efficacy of the proposed one.