Optimal Dubins Path Generation, System Identification and Control of a Paramotor

2019 ◽  
Author(s):  
William Habib ◽  
Ramy Elsabbagh ◽  
Ayman El-Badawy
Keyword(s):  
System Identification ◽  
Path Generation ◽  
Generation System ◽  
Dubins Path ◽  
And Control

System Identification and Control of the Activated Sludge Process by Use of a Statistical Model

1989 ◽  
Vol 21 (10-11) ◽  
pp. 1161-1172 ◽  
Author(s):  
M. Hiraoka ◽  
K. Tsumura
Keyword(s):  
Control System ◽  
System Identification ◽  
Statistical Model ◽  
Activated Sludge ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Ar Model ◽  
Diurnal Changes ◽  
Activated Sludge Process ◽  
And Control

The authors have been developing a hierarchical control system for the activated sludge process which consists of an upper level system controlling long-term seasonal variations, a control system of intermediate level aiming at optimization of the process and a control system of lower level controlling diurnal changes or hourly fluctuations. The control system using the multi-variable statistical model is one of the most appropriate control systems based on the modern control theory, for applying the lower level control of the activated sludge process. This paper introduces our efforts for developing the reliable data acquisition system, the control experiments applying the AR-model, one of the statistical models which were conducted at a pilot plant and present studies on the system identification and control at a field sewage treatment plant.

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

Optimal Design and Control of a Slider-Crank Mechanism System

2012 ◽  
Vol 487 ◽  
pp. 608-612 ◽  
Author(s):  
Chih Cheng Kao
Keyword(s):  
Particle Swarm Optimization ◽  
System Identification ◽  
Optimal Design ◽  
Fitness Function ◽  
Local Optimum ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Pm Synchronous Motor ◽  
And Control ◽  
Crank Mechanism

This paper mainly proposes an efficient modified particle swarm optimization (MPSO) method, to identify a slider-crank mechanism driven by a field-oriented PM synchronous motor. The parameters of many industrial machines are difficult to obtain if these machines cannot be taken apart. In system identification, we adopt the MPSO method to find parameters of the slider-crank mechanism. This new algorithm is added with “distance” term in the traditional PSO’s fitness function to avoid converging to a local optimum. Finally, the comparisons of numerical simulations and experimental results prove that the MPSO identification method for the slider-crank mechanism is feasible.

Path Following System for Cooperative Mobile Robots

2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu
Keyword(s):  
Artificial Intelligence ◽  
Mobile Robots ◽  
Path Following ◽  
Path Generation ◽  
Cooperative Robots ◽  
Generation System ◽  
Robot Systems ◽  
Simulation Results ◽  
Trajectory Generator

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.

Sign in / Sign up

Export Citation Format

Share Document