Nonlinear Inverse and Predictive End Point Trajectory Control of Flexible Macro-Micro Manipulators

1997 ◽  
Vol 119 (3) ◽  
pp. 412-420 ◽  
Author(s):  
Woosoon Yim ◽  
Sahjendra N. Singh
Keyword(s):  
Predictive Control ◽  
Tracking Error ◽  
Quadratic Function ◽  
Trajectory Control ◽  
Elastic Mode ◽  
End Effector ◽  
End Point ◽  
Micro Manipulator ◽  
Predictive Controller ◽  
Mode Stabilization

This paper presents a new approach to end-point trajectory control of flexible macro-micro manipulator based on nonlinear inversion and predictive control techniques. In this approach, precise control of the end-effector trajectory is accomplished by the inverse controller of the rigid micro manipulator, and the predictive controller steers the end point of the flexible macro manipulator with limited elastic oscillation. The predictive control law is obtained by minimizing a quadratic function of the tip tracking error, the elastic deflection, and the input torque of the flexible macro manipulator. The feedback parameters of the predictive controller are chosen such that zero dynamics are asymptotically stable. The combination of the inverse and the predictive controllers accomplishes precise end-effector trajectory tracking and elastic mode stabilization. These results are applied to a planar macro-micro manipulator system consisting of one flexible link and two micro rigid links. Simulation results are presented to show that in the closed-loop system time varying end point trajectory control and elastic mode stabilization are accomplished.

Compensatory model predictive control for post-impact trajectory tracking via active front steering and differential torque vectoring

2020 ◽  
pp. 095440702097908
Author(s):  
Mingcong Cao ◽  
Chuan Hu ◽  
Rongrong Wang ◽  
Jinxiang Wang ◽  
Nan Chen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Tracking Error ◽  
Collision Probability ◽  
Critical Conditions ◽  
Physical Analysis ◽  
Compensatory Model ◽  
Torque Vectoring ◽  
Post Impact

This paper investigates the trajectory tracking control of independently actuated autonomous vehicles after the first impact, aiming to mitigate the secondary collision probability. An integrated predictive control strategy is proposed to mitigate the deteriorated state propagation and facilitate safety objective achievement in critical conditions after a collision. Three highlights can be concluded in this work: (1) A compensatory model predictive control (MPC) strategy is proposed to incorporate a feedforward-feedback compensation control (FCC) method. Based on the definite physical analysis, it is verified that adequate reverse steering and differential torque vectoring render more potentials and flexibility for vehicle post-impact control; (2) With compensatory portions, the deteriorated states after a collision are far beyond the traditional stability envelope. Hence it can be further manipulated in MPC by constraint transformation, rather than introducing soft constraints and decreasing the control efforts on tracking error; (3) Considering time-varying saturation on input, input rate, and slip ratio, the proposed FCC-MPC controller is developed to improve faster deviation attenuation both in lateral and yaw motions. Finally two high-fidelity simulation cases implemented on CarSim-Simulink conjoint platform have demonstrated that the proposed controller has the advanced capabilities of vehicle safety improvement and better control performance achievement after severe impacts.

scholarly journals Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 870
Author(s):  
Md Rasedul Islam ◽  
Md Assad-Uz-Zaman ◽  
Brahim Brahmi ◽  
Yassine Bouteraa ◽  
Inga Wang ◽  
...  
Keyword(s):  
Upper Limb ◽  
Research Work ◽  
Human Robot Interaction ◽  
Control Technique ◽  
Upper Arm ◽  
Interaction Forces ◽  
End Effector ◽  
Upper Limb Rehabilitation ◽  
End Point ◽  
Limb Rehabilitation

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called ‘u-Rob’ that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer’s interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot.

scholarly journals Generalized ESO and Predictive Control Based Robust Autopilot Design

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Bhavnesh Panchal ◽  
S. E. Talole
Keyword(s):  
Predictive Control ◽  
Closed Loop ◽  
Specific Information ◽  
Disturbance Compensation ◽  
External Disturbances ◽  
Output Tracking ◽  
Control Gain ◽  
Predictive Controller ◽  
Mismatched Uncertainty ◽  
Acceleration Tracking

A novel continuous time predictive control and generalized extended state observer (GESO) based acceleration tracking pitch autopilot design is proposed for a tail controlled, skid-to-turn tactical missile. As the dynamics of missile are significantly uncertain with mismatched uncertainty, GESO is employed to estimate the state and uncertainty in an integrated manner. The estimates are used to meet the requirement of state and to robustify the output tracking predictive controller designed for nominal system. Closed loop stability for the controller-observer structure is established. An important feature of the proposed design is that it does not require any specific information about the uncertainty. Also the predictive control design yields the feedback control gain and disturbance compensation gain simultaneously. Effectiveness of GESO in estimation of the states and uncertainties and in robustifying the predictive controller in the presence of parametric uncertainties, external disturbances, unmodeled dynamics, and measurement noise is illustrated by simulation.

Nonlinear Model Predictive Control for Automatic Train Operation with Actuator Saturation and Speed Limit

2014 ◽  
Vol 678 ◽  
pp. 377-381
Author(s):  
Long Sheng Wang ◽  
Hong Ze Xu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
High Speed ◽  
Actuator Saturation ◽  
Tracking Error ◽  
Nonlinear Model Predictive Control ◽  
Speed Limit ◽  
Speed Tracking ◽  
Automatic Train Operation

This paper addresses a position and speed tracking problem for high-speed train automatic operation with actuator saturation and speed limit. A nonlinear model predictive control (NMPC) approach, which allows the explicit consideration of state and input constraints when formulating the problem and is shown to guarantee the stability of the closed-loop system by choosing a proper terminal cost and terminal constraints set, is proposed. In NMPC, a cost function penalizing both the train position and speed tracking error and the changes of tracking/braking forces will be minimized on-line. The effectiveness of the proposed approach is verified by numerical simulations.

scholarly journals Total Harmonic Distortion Oriented Finite Control Set Model Predictive Control for Single-Phase Inverters

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3467 ◽  
Author(s):  
Po Li ◽  
Ruiyu Li ◽  
Haifeng Feng
Keyword(s):  
Model Predictive Control ◽  
Cost Function ◽  
Predictive Control ◽  
Single Phase ◽  
Tracking Error ◽  
Harmonic Distortion ◽  
Total Harmonic Distortion ◽  
Finite Control ◽  
Control Set ◽  
The Cost

Inverters are commonly controlled to generate AC current and Total Harmonic Distortion (THD) is the core index in judging the control effect. In this paper, a THD oriented Finite Control Set Model Predictive Control (FCS MPC) scheme is proposed for the single-phase inverter, where a optimization problem is solved to obtain the switching law for realization. Different from the traditional cost function, which focuses on the instantaneous deviation of amplitude between predictive current and its reference, we redesign a cost function that is the linear combination of the current fundamental tracking error, instantaneous THD value and DC component in one fundamental cycle (for 50 Hz, it is 0.02 s). Iterative method is developed for rapid calculation of this cost function. By choosing a switching state from a FCS to minimize the cost function, a FCS MPC is finally constructed. Simulation results in Matlab/Simulink and experimental results on rapid control prototype platform show the effect of this method. Analyses illustrate that, by choosing suitable weight of the cost function, the performance of this THD oriented FCS MPC method is better than the traditional one.

scholarly journals A multivariable multiobjective predictive controller

2013 ◽  
Vol 23 (1) ◽  
pp. 35-45 ◽  
Author(s):  
Faten Ben Aicha ◽  
Faouzi Bouani ◽  
Mekki Ksouri
Keyword(s):  
Genetic Algorithm ◽  
Predictive Control ◽  
Mimo System ◽  
Weighting Factor ◽  
Nsga Ii ◽  
Weighted Sum Method ◽  
Prediction Horizon ◽  
Predictive Controller ◽  
Pareto Method ◽  
The Cost

Predictive control of MIMO processes is a challenging problem which requires the specification of a large number of tuning parameters (the prediction horizon, the control horizon and the cost weighting factor). In this context, the present paper compares two strategies to design a supervisor of the Multivariable Generalized Predictive Controller (MGPC), based on multiobjective optimization. Thus, the purpose of this work is the automatic adjustment of the MGPC synthesis by simultaneously minimizing a set of closed loop performances (the overshoot and the settling time for each output of the MIMO system). First, we adopt the Weighted Sum Method (WSM), which is an aggregative method combined with a Genetic Algorithm (GA) used to minimize a single criterion generated by the WSM. Second, we use the Non- Dominated Sorting Genetic Algorithm II (NSGA-II) as a Pareto method and we compare the results of both the methods. The performance of the two strategies in the adjustment of multivariable predictive control is illustrated by a simulation example. The simulation results confirm that a multiobjective, Pareto-based GA search yields a better performance than a single objective GA.

Energy Efficiency and Tracking Performance Evaluation for Dual-Mode Model Predictive Control of HVAC Systems

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Zicheng Cai ◽  
Asad A. Ul Haq ◽  
Michael E. Cholette ◽  
Dragan Djurdjanovic
Keyword(s):  
Energy Consumption ◽  
Predictive Control ◽  
Pid Control ◽  
Control Structure ◽  
Tracking Performance ◽  
System Control ◽  
Hvac System ◽  
Dual Mode ◽  
Different Types ◽  
Predictive Controller

This paper presents evaluation of the energy consumption and tracking performance associated with the use of a recently introduced dual-mode model predictive controller (DMMPC) for control of a heating, ventilation, and air conditioning (HVAC) system. The study was conducted using detailed simulations of an HVAC system, which included a multizone air loop, a water loop, and a chiller. Energy consumption and tracking performance are computed from the simulations and evaluated in the presence of different types and magnitudes of noise and disturbances. Performance of the DMMPC is compared with a baseline proportional-integral-derivative (PID) control structure commonly used for HVAC system control, and this comparison showed clear and consistent superiority of the DMMPC.

Damage-Mitigating Predictive Control of Airfoil Flutter for a General Hypersonic Flight Vehicle

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Xiaohui Zhang ◽  
Yuhui Wang ◽  
Xingkai Feng ◽  
Siyuan Hou
Keyword(s):  
Predictive Control ◽  
Degrees Of Freedom ◽  
Unsteady Aerodynamics ◽  
Flight Vehicle ◽  
Hypersonic Flight Vehicle ◽  
Hypersonic Flight ◽  
Online Simulation ◽  
Nonlinear Predictive Control ◽  
Predictive Controller ◽  
Damage Accumulation Model

Abstract This paper aims to investigate the airfoil flutter damage-mitigating problem in hypersonic flow. A new adaptive robust nonlinear predictive control law is designed in this paper to mitigate the damage during airfoil flutter of a generic hypersonic flight vehicle. A three-degrees-of-freedom airfoil dynamic motion model is established, in which the third piston theory is employed to derive the unsteady aerodynamics. Then, the complicated responses of the hypersonic airfoil flutter model are analyzed. In order to mitigate the damage of the airfoil, a predictive controller is designed by introducing an adaptive predictive period, and asymptotical stability analysis of the robust nonlinear predictive controller is performed. Subsequently, based on the nonlinear aerodynamics of the airfoil and damage accumulation model, the damage of the airfoil is observed online. Simulation results illustrate the effectiveness of the proposed method.

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