Combined Robust Design and Robust Control of an Electric DC Motor

2006 ◽  
Author(s):  
Sulaiman F. Alyaqout ◽  
Panos Y. Papalambros ◽  
A. Galip Ulsoy
Keyword(s):  
Robust Control ◽  
Robust Design ◽  
Computational Cost ◽  
Minimax Problem ◽  
Dc Motor ◽  
Engineering Systems ◽  
Control Optimization ◽  
Minimax Design ◽  
And Control

System performance can significantly benefit from optimally integrating the design and control of engineering systems. To improve the robustness properties of systems, the present article introduces an approach that combines robust design with robust control and investigates the coupling between them. However, the computational cost of improving this robustness can often be high due to the need to solve a resulting minimax design and control optimization problem. To reduce this cost, sequential and iterative strategies are proposed and compared to an all-in-one strategy for solving the minimax problem. These strategies are then illustrated for a case-study: Robust design and robust control of a DC motor. Results show that the resulting strategies can improve the robustness properties of the DC motor. In addition, the coupling strength between robust design and robust control tends to increase as the applied level of uncertainty increases.

Synthesis Method of Mixed Sensitivity for H-infinity Robust Control Optimization on DC Motor of Mechatronics Model

2021 ◽  
Author(s):  
Jalu A. Prakosa ◽  
Edi Kurniawan ◽  
Suryadi ◽  
Bernadus H. Sirenden ◽  
Purwowibowo ◽  
...  
Keyword(s):  
Robust Control ◽  
Synthesis Method ◽  
Dc Motor ◽  
H Infinity ◽  
Control Optimization

Robust Design Through the Use of a Hybrid Genetic Algorithm

2002 ◽  
Author(s):  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Hybrid Genetic Algorithm ◽  
Design Parameters ◽  
Optimization Approach ◽  
Engineering Systems ◽  
Local Optima ◽  
Good Design ◽  
Mean And Variance ◽  
The Mean

In this paper we present a hybrid optimization approach to perform robust design. The motivation for this work is the fact that many realistic engineering systems are mutimodal in nature with multiple local optima, and moreover may have one or more uncertain design parameters. The approach that is presented utilizes both local and global optimization algorithms to find good design points more efficiently than either could alone. The mean and variance of the objective function at a design point is calculated using Monte Carlo simulation and is used to drive the optimization process. To demonstrate the usefulness of this approach a case study is considered involving the design of a beam with dimensional uncertainty.

Optimal Design and Control of an Electric DC Motor

1999 ◽  
Author(s):  
Julie A. Reyer ◽  
Panos Y. Papalambros
Keyword(s):  
Control Strategy ◽  
Decision Model ◽  
Control Design ◽  
Dc Motor ◽  
Physical Structure ◽  
Pareto Analysis ◽  
Design And Optimization ◽  
Overall Design ◽  
And Control

Abstract In the design and optimization of artifacts requiring both mechanical and control design, the process is typically divided and performed in separate steps. The physical structure is designed first, a control strategy is selected, and the actual controller is then designed. This paper examines how this separation could affect the overall system design and how the combination of the separate problems into a single decision model could improve the overall design, using an electric DC motor as a case study. The combination is challenging since the two problems often have different design criteria and objectives and mathematical model properties. A Pareto analysis is suggested as a rigorous way to compare a variety of design scenaria.

A Problem Class With Combined Architecture, Plant, and Control Design Applied to Vehicle Suspensions

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Daniel R. Herber ◽  
James T. Allison
Keyword(s):  
Dynamic Optimization ◽  
Design Problem ◽  
Control Design ◽  
Vehicle Suspension ◽  
Engineering Systems ◽  
Linear Quadratic ◽  
Problem Class ◽  
Physical Elements ◽  
And Control

Here we describe a problem class with combined architecture, plant, and control design for dynamic engineering systems. The design problem class is characterized by architectures comprised of linear physical elements and nested co-design optimization problems employing linear-quadratic dynamic optimization. The select problem class leverages a number of existing theory and tools and is particularly effective due to the symbiosis between labeled graph representations of architectures, dynamic models constructed from linear physical elements, linear-quadratic dynamic optimization, and the nested co-design solution strategy. A vehicle suspension case study is investigated and a specifically constructed architecture, plant, and control design problem is described. The result was the automated generation and co-design problem evaluation of 4374 unique suspension architectures. The results demonstrate that changes to the vehicle suspension architecture can result in improved performance, but at the cost of increased mechanical complexity. Furthermore, the case study highlights a number of challenges associated with finding solutions to the considered class of design problems. One such challenge is the requirement to use simplified design problem elements/models; thus, the goal of these early-stage studies are to identify new architectures that are worth investigating more deeply. The results of higher-fidelity studies on a subset of high-performance architectures can then be used to select a final system architecture. In many aspects, the described problem class is the simplest case applicable to graph-representable, dynamic engineering systems.

The control of the electro-hydraulic shaking table based on dynamic surface adaptive robust control

2016 ◽  
Vol 39 (8) ◽  
pp. 1271-1280 ◽  
Author(s):  
Wei Shen ◽  
Jun-zheng Wang ◽  
Shou-kun Wang
Keyword(s):  
Robust Control ◽  
Computational Cost ◽  
Adaptive Robust Control ◽  
Working Environment ◽  
Shaking Table ◽  
Parameter Uncertainties ◽  
Robust Controller ◽  
Dynamic Surface ◽  
Vibration Direction ◽  
And Control

The electro-hydraulic shaking table is investigated, in the present paper, to simulate the vibrational working environment of industrial components and equipment. Adaptive robust control can be applied to the shaking table system because electro-hydraulic systems suffer from internal parameter uncertainties and external disturbances. However, the adaptive robust controller design is complicated and has a large computational cost owing to the ‘explosion of terms’ problem. Thus dynamic surface control is applied in the design procedure of adaptive robust controllers to overcome the ‘explosion of terms’ problem. In this work, dynamic surface adaptive robust control is proposed. It simplifies the designed procedure of the controller and decreases its computational cost. Firstly, the structure of a shaking table is formulated and the operation principles of the shaking table, including the hydraulic and control principles, are analysed. A change is made in the mechanical-hydraulic system of the fluid circuit to address the problem of changing the vibration direction. Secondly, a dynamic model of a shaking table is proposed. Based on analysis of this model, the design of a dynamic surface adaptive robust controller for a shaking table is presented so as to improve its performance. Finally, comparative simulations and experiments are carried out. The comparison of performance results with proportional-integral-derivative control verify the correctness of the hydraulic scheme and control principle, as well as the high-performance of the dynamic surface adaptive robust controller. The shaking table achieves a guaranteed dynamical performance and tracking accuracy for the output in the presence of parameter and load uncertainties.

A Comprehensive Robust Design Approach for Decision Trade-Offs in Complex Systems Design

1999 ◽  
Vol 123 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Monu Kalsi ◽  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Systems Design ◽  
Decision Makers ◽  
Engineering Systems ◽  
Trade Offs ◽  
Design Variables ◽  
Complex Engineering ◽  
The Cost ◽  
Passenger Aircraft

In this paper we introduce a technique to reduce the effects of uncertainty and incorporate flexibility in the design of complex engineering systems involving multiple decision-makers. We focus on the uncertainty that is created when a disciplinary designer or design team must try to predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and design teams, each of which may only have control over a portion of the total set of system design variables. Modeling the interaction among these decision-makers and reducing the effect caused by lack of global control by any one designer is the focus of this paper. We use concepts from robust design to reduce the effects of decisions made during the design of one subsystem on the performance of the rest of the system. Thus, in a situation where the cost of uncertainty is high, these tools can be used to increase the robustness, or independence, of the subsystems, enabling designers to make more effective decisions. To demonstrate the usefulness of this approach, we consider a case study involving the design of a passenger aircraft.

scholarly journals Quadrature as applied to computer models for robust design: theoretical and empirical assessment

2021 ◽  
Vol 7 ◽  
Author(s):  
Daniel D. Frey ◽  
Yiben Lin ◽  
Petra Heijnen
Keyword(s):  
Case Studies ◽  
Robust Design ◽  
Probability Model ◽  
Computer Experiments ◽  
Engineering Systems ◽  
Probability Models ◽  
Model Based ◽  
Mean And Variance ◽  
Gauss Hermite Quadrature

Abstract This paper develops theoretical foundations for extending Gauss–Hermite quadrature to robust design with computer experiments. When the proposed method is applied with m noise variables, the method requires 4m + 1 function evaluations. For situations in which the polynomial response is separable, this paper proves that the method gives exact transmitted variance if the response is a fourth-order separable polynomial response. It is also proven that the relative error mean and variance of the method decrease with the dimensionality m if the response is separable. To further assess the proposed method, a probability model based on the effect hierarchy principle is used to generate sets of polynomial response functions. For typical populations of problems, it is shown that the proposed method has less than 5% error in 90% of cases. Simulations of five engineering systems were developed and, given parametric alternatives within each case study, a total of 12 case studies were conducted. A comparison is made between the cumulative density function for the hierarchical probability models and a corresponding distribution function for case studies. The data from the case-based evaluations are generally consistent with the results from the model-based evaluation.

scholarly journals Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Magdi M. El-Saadawi ◽  
Eid Abdelbaqi Gouda ◽  
Mostafa A. Elhosseini ◽  
Mohamed Said Essa
Keyword(s):  
Fractional Order ◽  
Pid Control ◽  
Pid Controller ◽  
Dc Motor ◽  
Grey Wolf ◽  
Control Effect ◽  
Grey Wolf Optimization ◽  
And Control ◽  
Fractional Order Pid

This paper uses Fractional-order PID control (FOPID) to control the speed of the DC motor.  FOPID is more flexible and confident in controlling control higher-order systems compared to classical PID. In this work, the FOPID controller tuning is carried out using different methods ranging from classical techniques to most recent heuristic methods are Fractional Grey wolf Optimization and Nelder-Mead. Moreover, parameter estimation of real-world DC motor is carried out experimentally using Matlab/Simulink interfaced to an Arduino Uno board. The feasibility of FOPID is demonstrated through applications to well-known DC motor case study and the estimated DC motor. Based on ISE, ITE, and ISTE performance measures, the proposed approach provide less settling time, rise time and comparable overshoot compared with existing literature approaches. A robustness assessment with differences in the DC motor components is performed. Simulation finding provide validation of the suggested work and the FOPID controller effectiveness as compared to classical PID controller in terms of robustness and control effect.

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