Some Simulation Results with Input - Output Allocation Model

1994 ◽  
Vol 36 (2) ◽  
pp. 113
Author(s):  
A. K. Sengupta
Keyword(s):  
Input Output ◽  
Allocation Model ◽  
Simulation Results

scholarly journals A modular framework to generate robust biped locomotion: from planning to control

2021 ◽  
Vol 3 (9) ◽  
Author(s):  
Mohammadreza Kasaei ◽  
Ali Ahmadi ◽  
Nuno Lau ◽  
Artur Pereira
Keyword(s):  
Numerical Simulations ◽  
Predictive Control ◽  
Biped Locomotion ◽  
Input Output ◽  
Dynamics Model ◽  
Biped Robots ◽  
The Core ◽  
Simulation Results ◽  
Reference Trajectories ◽  
Modular Framework

AbstractBiped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso, and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs, and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly.

Immersion and invariance-based filtered transformation with application to estimator design for a class of DC-DC converters

2018 ◽  
Vol 41 (5) ◽  
pp. 1323-1330 ◽  
Author(s):  
Milad Malekzadeh ◽  
Alireza Khosravi ◽  
Mehdi Tavan
Keyword(s):  
Asymptotic Convergence ◽  
Parametric Uncertainties ◽  
Input Output ◽  
Boost Converters ◽  
Immersion And Invariance ◽  
Simulation Results ◽  
Dynamic Filter ◽  
Proper Immersion ◽  
Immersion And Invariance Technique ◽  
Estimator Design

This paper addresses the problem of state and parameter estimation for a class of uncertain DC-DC such converters as DC–DC boost, buck and buck-boost converters. Using the advantages of Immersion and Invariance technique with input-output filtered transformation, a proper immersion and auxiliary dynamic filter is constructed in the proposed estimator. Uniform global asymptotic convergence of the estimator is proven for the system with parametric uncertainties. In the presence of both output and state dynamics perturbations, the performance of the proposed estimator has been theoretically analyzed and verified by means of simulation results. In addition, the effectiveness of this scheme is validated via experimental test for DC-DC boost converter.

The Design of a New Biaxial Decoupled Resonant Micro-Accelerometer

2013 ◽  
Vol 744 ◽  
pp. 466-469 ◽  
Author(s):  
Bo Yang ◽  
Hui Zhao ◽  
Bo Dai
Keyword(s):  
Basic Principle ◽  
Proof Mass ◽  
Mutual Interference ◽  
Scale Factor ◽  
Output Characteristic ◽  
Input Output ◽  
Simulation Results ◽  
Resonator Modes ◽  
Micro Accelerometer

A new biaxial decoupled resonant micro-accelerometer is researched. The new biaxial resonant micro-accelerometer consists of four same tuning forking resonators, four pair of decoupled beams, four lever mechanisms and a proof mass. The decoupling between two orthogonal axes is realized by the decoupling beams, which will benefit to isolate two axes acceleration detection. The simulation is implemented to verify the basic principle by the Ansys. The simulation results prove that the effective frequencies of two acceleration sensitive modes are 3.699 kHz and 3.718 kHz separately. Two pair of resonator modes which are 23.893 kHz, 23.946 kHz, 26.974 kHz and 26.999 kHz separately have about 3kHz difference in frequency in order to prevent the mutual interference. And the interference modes are isolated with effective mode apparently. The input-output characteristic simulation results indicate the y-axis scale factor is 57.1Hz/g and the coupling output in the x-axis is 0.0148Hz/g, while the x-axis scale factor is 56.1Hz/g and the coupling output in the y-axis is 0.0073Hz/g, which proves that the new biaxial resonant micro-accelerometer is practicable and has an excellent decoupled performance.

Data Use and the Simulation of Regional Input-Output Matrices

1986 ◽  
Vol 18 (8) ◽  
pp. 1061-1076 ◽  
Author(s):  
F Harrigan ◽  
I McNicoll
Keyword(s):  
Data Use ◽  
Estimation Method ◽  
Estimation Procedure ◽  
Input Output ◽  
Growing Body ◽  
Simulation Results

There is a growing body of evidence which suggests that, used in conjunction with a suitable estimation method, the incorporation of good quality exogenous data can enhance the accuracy of simulated or updated regional input—output matrices. However, there has been little attempt to measure explicitly the accuracy of simulation results in relation to the data used in their estimation. Within the context of programming estimation procedure, comparable measures of the ‘quantity’ of exogenous data and the accuracy of simulation are developed in this paper. Subsequently, this framework is demonstrated using Scottish and Washington input—output tables.

Comparison of Adaptive and Robust Controllers for Fully-Constrained and Redundant Planar Cable Robots

2014 ◽  
Author(s):  
Sergio J. Torres-Mendez ◽  
Gokhan Gungor ◽  
Baris Fidan ◽  
Amir Khajepour
Keyword(s):  
Pid Controller ◽  
Position Control ◽  
Sliding Mode ◽  
Uncertain Parameters ◽  
Input Output ◽  
Adaptive Controllers ◽  
Control Scheme ◽  
Control Schemes ◽  
Novel Method ◽  
Simulation Results

This work deals with the design and comparison of two adaptive position control schemes with a classical PID controller for fully constrained and redundant planar robots. First, a novel method based on inclusion of virtual cables facilitates the linear separation of the uncertain parameters from the input-output signals. Then, two Lyapunov based adaptive controllers based on the sliding mode and PD schemes are designed to compensate for the structure matrix uncertainties, which result from errors in the anchor point locations. Finally, the adaptive controllers are evaluated and compared with a classical PID controller through simulations for a desired 2D singularity-free pose of the mobile platform. The simulation results have shown that the adaptive PD control scheme has the best performance for both fully constrained and redundant cases.

Combined Sliding Mode Control with a Feedback Linearization for Speed Control of Induction Motor

2011 ◽  
Vol 7 (1) ◽  
pp. 19-24
Author(s):  
Aamir Ahmed ◽  
Martino Ajangnay ◽  
Shamboul Mohamed ◽  
Matthew Dunnigan
Keyword(s):  
Sliding Mode Control ◽  
Control Strategy ◽  
Output Feedback ◽  
Feedback Linearization ◽  
Sliding Mode ◽  
Speed Control ◽  
Input Output ◽  
Nonlinear Controller ◽  
Feedback Linearization Control ◽  
Simulation Results

Induction Motor (IM) speed control is an area of research that has been in prominence for some time now. In this paper, a nonlinear controller is presented for IM drives. The nonlinear controller is designed based on input-output feedback linearization control technique, combined with sliding mode control (SMC) to obtain a robust, fast and precise control of IM speed. The input-output feedback linearization control decouples the flux control from the speed control and makes the synthesis of linear controllers possible. To validate the performances of the proposed control scheme, we provided a series of simulation results and a comparative study between the performances of the proposed control strategy and those of the feedback linearization control (FLC) schemes. Simulation results show that the proposed control strategy scheme shows better performance than the FLC strategy in the face of system parameters variation.

Model Predictive Control of a Differential-Drive Mobile Robot

2018 ◽  
Vol 10 (1) ◽  
pp. 20-41
Author(s):  
Samir Bouzoualegh ◽  
El-Hadi Guechi ◽  
Ridha Kelaiaia
Keyword(s):  
Mathematical Model ◽  
Model Predictive Control ◽  
Mobile Robot ◽  
Predictive Control ◽  
Control Law ◽  
Input Output ◽  
Linearization Technique ◽  
Differential Drive ◽  
Predictive Controller ◽  
Simulation Results

Abstract This paper presents a model predictive control (MPC) for a differential-drive mobile robot (DDMR) based on the dynamic model. The robot’s mathematical model is nonlinear, which is why an input–output linearization technique is used, and, based on the obtained linear model, an MPC was developed. The predictive control law gains were acquired by minimizing a quadratic criterion. In addition, to enable better tuning of the obtained predictive controller gains, torques and settling time graphs were used. To show the efficiency of the proposed approach, some simulation results are provided.

scholarly journals Signal-Based Performance Evaluation of Dereverberation Algorithms

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Patrick A. Naylor ◽  
Nikolay D. Gaubitch ◽  
Emanuël A. P. Habets
Keyword(s):  
Performance Evaluation ◽  
Least Squares ◽  
Impulse Response ◽  
Time Varying ◽  
Normalization Procedure ◽  
Input Output ◽  
Before And After ◽  
Source Signal ◽  
Simulation Results

We address the measurement of reverberation in terms of the (DRR) in the context of the assessment of dereverberation algorithms for which we wish to quantify the level of reverberation before and after processing. The DRR is normally calculated from the impulse response of the reverberating system. However, several important dereverberation algorithms involve nonlinear and/or time-varying processing and therefore their effect cannot conveniently be represented in terms of modifications to the impulse response of the reverberating system. In such cases, we show that a good estimate of DRR can be obtained from the input/output signals alone using the Signal-to-Reverberant Ratio (SRR) only if the source signal is spectrally white and correctly normalized. We study alternative normalization schemes and conclude by showing a least squares optimal normalization procedure for estimating DRR using signal-based SRR measurement. Simulation results illustrate the accuracy of DRR estimation using SRR.

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