Analysis the Effect of Undesirable Factors on Stability of Model Predictive Controller

2008 ◽  
Author(s):  
Shadi Ansarpanahi ◽  
Samsul Bahari Mohd Noor
Keyword(s):  
Predictive Control ◽  
Time Delays ◽  
Control Algorithm ◽  
Computer Control ◽  
Phase System ◽  
Control Scheme ◽  
Predictive Controller ◽  
Noise Error ◽  
The Stability ◽  
Drive Model

MPC also known as moving or receding horizon control, is a feedback control scheme that has originated in industry as a real-time computer control algorithm to solve linear and nonlinear multi-variable problems that have constraints and time delays. Since disturbances can drive model predictive control into non-convexity and instability this problem has attracted many researchers. The stability studies in this paper are illustrated in presence of colored noise, error in delay estimation, unstable and non-minimum phase system by means of numerical example. The simulation is carried out using an example, which is the main contribution of the paper.

scholarly journals Improved Distributed Model Predictive Control with Control Planning Set

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Wei Chen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
System Performance ◽  
Control Algorithm ◽  
Distributed Model ◽  
Distributed Model Predictive Control ◽  
Exchange Information ◽  
Predictive Controller ◽  
Model Predictive Control Algorithm ◽  
The Stability

We focus on distributed model predictive control algorithm. Each distributed model predictive controller communicates with the others in order to compute the control sequence. But there are not enough communication resources to exchange information between the subsystems because of the limited communication network. This paper presents an improved distributed model predictive control scheme with control planning set. Control planning set algorithm approximates the future control sequences by designed planning set, which can reduce the exchange information among the controllers and can also decrease the distributed MPC controller calculation demand without degrading the whole system performance much. The stability and system performance analysis for distributed model predictive control are given. Simulations of the four-tank control problem and multirobot multitarget tracking problem are illustrated to verify the effectiveness of the proposed control algorithm.

Levitation System Controller Design Based on the Implicit General Predictive Control Algorithm

2013 ◽  
Vol 444-445 ◽  
pp. 806-811
Author(s):  
Yu Yin Wang ◽  
Jie Li
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Controller Design ◽  
Linear Character ◽  
Maglev System ◽  
Control Scheme ◽  
Levitation System ◽  
The Stability ◽  
General Predictive Control ◽  
System Controller

The levitation control system is a key technique of the maglev system. Due to the strong non-linear character of the magnetic force, as well as the model uncertainties and external interferences of the maglev system, the Implicit General Predictive Control algorithm, which adjusts the parameters of the control scheme by using the input and output data, is adopted in this article. Taking the single electro-magnet levitation system as the research object, this algorithm not only guarantees the stability of the system, but also suppresses the vibration caused by the flexibility of the track. The advantages of this algorithm include: the superior control capacity, roll over optimization and little dependence on model. The simulation approves the validity of this method.

scholarly journals An adaptive hierarchical control for aerial manipulators

Robotica ◽  
2018 ◽  
Vol 36 (10) ◽  
pp. 1527-1550 ◽  
Author(s):  
Francesco Pierri ◽  
Giuseppe Muscio ◽  
Fabrizio Caccavale
Keyword(s):  
Control Algorithm ◽  
Hierarchical Control ◽  
Bottom Layer ◽  
Trajectory Tracking Control ◽  
Aerial Manipulator ◽  
Control Scheme ◽  
Modelling Uncertainties ◽  
Aerial Vehicle ◽  
The Stability

SUMMARYThis paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.

Research on Accurate Modeling and Control for Pneumatic Electric Braking System of Commercial Vehicle Based on Multi-Dynamic Parameters Measurement

2020 ◽  
Author(s):  
Yongtao Zhao ◽  
Yiyong Yang ◽  
Xiuheng Wu ◽  
Xingjun Tao
Keyword(s):  
Dynamic Response ◽  
Real Time ◽  
Predictive Control ◽  
Control Algorithm ◽  
Control Algorithms ◽  
Dynamic Parameters ◽  
Braking System ◽  
Control Scheme ◽  
Braking Force ◽  
Electric Braking

Abstract Accurate pressure control and fast dynamic response are vital to the pneumatic electric braking system (PEBS) for that commercial vehicles require higher regulation precision of braking force on four wheels when braking force distribution is carried out under some conditions. Due to the lagging information acquisition, most feedback-based control algorithms are difficult to further improve the dynamic response of PEBS. Meanwhile, feedforward-based control algorithms like predictive control perform well in improving dynamic performance. but because of the large amount of computation and complexity of this kind of control algorithm, it cannot be applied in real-time on single-chip microcomputer, and it is still in the stage of theoretical research at present. To address this issue and for the sake of engineering reliability, this article presents a logic threshold control scheme combining analogous model predictive control (AMPC) and proportional control. In addition, an experimental device for real-time measuring PEBS multi-dynamic parameters is built. After correcting the key parameters, the precise model is determined and the influence of switching solenoid valve on its dynamic response characteristics is studied. For the control scheme, numerical and physical validation are executed to demonstrate the feasibility of the strategy and for the performance of the controller design. The experimental results show that the dynamic model of PEBS can accurately reflect its pressure characteristics. Furthermore, under different air source pressures, the designed controller can stably control the pressure output of PEBS and ensure that the error is within 8KPa. Compared with the traditional control algorithm, the rapidity is improved by 32.5%.

scholarly journals Model Predictive Control for a Small Scale Unmanned Helicopter

10.5772/10583 ◽  
2008 ◽  
Vol 5 (4) ◽  
pp. 34 ◽  
Author(s):  
Jianfu Du ◽  
Konstantin Kondak ◽  
Markus Bernard ◽  
Yaou Zhang ◽  
Tiansheng Lü ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Time Delays ◽  
Control Algorithm ◽  
Controller Design ◽  
Control Mode ◽  
Small Scale ◽  
Unmanned Helicopter ◽  
Dynamical Equations ◽  
Novel Method

Kinematical and dynamical equations of a small scale unmanned helicoper are presented in the paper. Based on these equations a model predictive control (MPC) method is proposed for controlling the helicopter. This novel method allows the direct accounting for the existing time delays which are used to model the dynamics of actuators and aerodynamics of the main rotor. Also the limits of the actuators are taken into the considerations during the controller design. The proposed control algorithm was verified in real flight experiments where good perfomance was shown in postion control mode.

scholarly journals A Robust Control Scheme for Renewable-Based Distributed Generators Using Artificial Hydrocarbon Networks

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1896 ◽  
Author(s):  
Antonio Rosales ◽  
Pedro Ponce ◽  
Hiram Ponce ◽  
Arturo Molina
Keyword(s):  
Robust Control ◽  
Control Algorithm ◽  
Solar Panels ◽  
Lyapunov Techniques ◽  
Distributed Generators ◽  
Stability Robustness ◽  
Network Controller ◽  
Control Scheme ◽  
Power Regulation ◽  
The Stability

Distributed generators (DGs) based on renewable energy systems such as wind turbines, solar panels, and storage systems, are key in transforming the current electric grid into a green and sustainable network. These DGs are called inverter-interfaced systems because they are integrated into the grid through power converters. However, inverter-interfaced systems lack inertia, deteriorating the stability of the grid as frequency and voltage oscillations emerge. Additionally, when DGs are connected to the grid, its robustness against unbalanced conditions must to be ensured. This paper presents a robust control scheme for power regulation in DGs, which includes inertia and operates under unbalanced conditions. The proposed scheme integrates a robust control algorithm to ensured power regulation, despite unbalanced voltages. The control algorithm is an artificial hydrocarbon network controller, which is a chemically-inspired technique, based on carbon networks, that provides stability, robustness, and accuracy. The robustness and stability of the proposed control scheme are tested using Lyapunov techniques. Simulation, considering one- and three-phase voltage sags, is executed to validate the performance of the control scheme.

Adaptive Generalized Predictive Controller and Cartesian Force Control for Robot Arm Using Dynamics and Geometric Identification

2018 ◽  
Vol 30 (6) ◽  
pp. 927-942 ◽  
Author(s):  
Shohei Hagane ◽  
Liz Katherine Rincon Ardila ◽  
Takuma Katsumata ◽  
Vincent Bonnet ◽  
Philippe Fraisse ◽  
...  
Keyword(s):  
Predictive Control ◽  
High Performance ◽  
Wall Painting ◽  
Robot Arm ◽  
Inertial Parameters ◽  
Control Scheme ◽  
Predictive Controller ◽  
Adaptive Predictive Control ◽  
Predictive Controllers ◽  
Contact Tasks

In realistic situations such as human-robot interactions or contact tasks, robots must have the capacity to adapt accordingly to their environment, other processes and systems. Adaptive model based controllers, that requires accurate dynamic and geometric robot’s information, can be used. Accurate estimations of the inertial and geometric parameters of the robot and end-effector are essential for the controller to demonstrate a high performance. However, the identification of these parameters can be time-consuming and complex. Thus, in this paper, a framework based on an adaptive predictive control scheme and a fast dynamic and geometric identification process is proposed. This approach was demonstrated using a KUKA lightweight robot (LWR) in the performance of a force-controlled wall-painting task. In this study, the performances of a generalized predictive control (GPC), adaptive proportional derivative gravity compensation, and adaptive GPC (AGPC) were compared. The results revealed that predictive controllers are more suitable than adaptive PD controllers with gravitational compensation, owing to the use of well-identified geometric and inertial parameters.

Vehicle stability enhancement and rollover prevention by a nonlinear predictive control method

2018 ◽  
Vol 41 (8) ◽  
pp. 2135-2149 ◽  
Author(s):  
M. Selçuk Arslan ◽  
Mert Sever
Keyword(s):  
Predictive Control ◽  
Control Method ◽  
Vertical Load ◽  
Steering Control ◽  
Yaw Rate ◽  
Rollover Prevention ◽  
Nonlinear Predictive Control ◽  
Predictive Controller ◽  
The Stability ◽  
Stability Enhancement

In this study, a nonlinear predictive control method is developed for the active steering control of a sport utility vehicle. The method is tested on a nonlinear mathematical model of an 11-degree-of-freedom vehicle. The system performance is evaluated by considering that the control law must keep the actual yaw rate close to the desired yaw rate and minimizing the vertical load changes at each wheel. The latter is proposed for this work. The vertical load changes play an important role in the dynamics and the stability of the system. The effectiveness of the control method is demonstrated through numerical simulation by using a vehicle model that includes three case studies: rapid lane change at low and high velocities and the fishhook manoeuvre. The results show that the stability of the vehicle is maintained and its rollover propensity is decreased. In addition, the proposed controller is compared with a well-known linear model predictive controller.

Spherical Modeling and Nonlinear Model Predictive Control of Electroporation

2011 ◽  
Author(s):  
Jingang Yi ◽  
Jianbo Li ◽  
Hao Lin
Keyword(s):  
Pore Size ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Transmembrane Potential ◽  
Dynamic Models ◽  
Effective Means ◽  
Spherical Model ◽  
Biological Research ◽  
Control Scheme ◽  
Predictive Controller

Electroporation is an effective means to deliver molecules into the cellular cytoplasm, and has been widely applied in both biological research and clinical applications. The process however suffers from low viability and efficiency. In this work, we present a multi-pulse feedback control scheme for enhancing viability and efficiency of electroporation process. We first present a spherical model for cell transmembrane potential (TMP) dynamics to describe the spatial distribution of electric potential on cell membrane. Then we analyze the models and discuss the bifurcation property of the system. Based on the dynamic models, we design a nonlinear model predictive controller (NMPC) to track pore size profiles in electroporation. We demonstrate that by using NMPC, the pore size can be precisely regulated to targeted values for drug delivery applications. The control design is illustrated through simulation examples.

Transparency Improvement by External Force Estimation in a Time-Delayed Nonlinear Bilateral Teleoperation System

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
H. Amini ◽  
S. M. Rezaei ◽  
Ahmed A. D. Sarhan ◽  
J. Akbari ◽  
N. A. Mardi
Keyword(s):  
Control Algorithm ◽  
Force Measurement ◽  
Bilateral Teleoperation ◽  
Force Estimation ◽  
Teleoperation System ◽  
Control Scheme ◽  
Environmental Force ◽  
The Stability ◽  
External Forces ◽  
Teleoperation Systems

Teleoperation systems have been developed in order to manipulate objects in environments where the presence of humans is impossible, dangerous or less effective. One of the most attractive applications is micro telemanipulation with micropositioning actuators. Due to the sensitivity of this operation, task performance should be accurately considered. The presence of force signals in the control scheme could effectively improve transparency. However, the main restriction is force measurement in micromanipulation scales. A new modified strategy for estimating the external forces acting on the master and slave robots is the major contribution of this paper. The main advantage of this strategy is that the necessity for force sensors is eliminated, leading to lower cost and further applicability. A novel control algorithm with estimated force signals is proposed for a general nonlinear macro–micro bilateral teleoperation system with time delay. The stability condition in the macro–micro teleoperation system with the new control algorithm is verified by means of Lyapunov stability analysis. The designed control algorithm guarantees stability of the macro–micro teleoperation system in the presence of an estimated operator and environmental force. Experimental results confirm the efficiency of the novel control algorithm in position tracking and force reflection.

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