Towards a generic optimal co-design of hardware architecture and control configuration for interacting subsystems

Haemers, Michiel; Derammelaere, Stijn; Rosich, Albert; Ionescu, Clara-Mihaela; Stockman, Kurt

doi:10.1016/j.mechatronics.2019.102275

Cited by 10 publications

(8 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The actual hardware and control optimization algorithm is performed on the closed-loop state-space system SS CL with an objective function related to the trajectory tracking and acceleration vibration reduction. Details on the different possible hardware types, related costs, non-linear constraints, and optimization results can be found in [12]. Fig.…”

Section: Optimization Results and Comparison With Existing Methodsmentioning

confidence: 99%

“…The first and most important advantage of this proposed methodology is that it enables a thorough optimization of both the hardware architecture and the control configuration [12]. That is because when applying the presented methodology, the impact of adding or omitting specific controller structures can be investigated quickly by adjusting the corresponding controller gains.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hardware and control co-design enabled by a state-space formulation of cascaded, interconnected PID controlled systems

Haemers

Ionescu

Depraetere

et al. 2021

2021 7th International Conference on Optimization and Applications (ICOA)

Self Cite

View full text Add to dashboard Cite

In recent years, more and more attention has been paid to the simultaneous optimization of hardware and control to achieve an optimal design of complex and interacting systems. To efficiently carry out this co-design optimization, there is a need for flexible methods to apply the variable hardware and control co-design aspects while also allowing a faster system response calculation compared to traditional methods. These time savings in the response calculations are of significant importance when using iterative optimization algorithms that typically require a large number of simulations to arrive at a solution.That is why this paper proposes a general methodology to create a closed-loop state-space model consisting of an open-loop process with an observer and extensive control loop structures. These structures comprise a combination of cascaded decentralized and distributed controllers, synchronizing controllers, and feedforward controllers while taking into account reference trajectories and input disturbances. It is shown that with the proposed methodology, response calculations for a motion application are much faster compared to traditional graphical programming tools that enable to apply flexible control architecture features. This shows that the presented methodology permits the efficient co-design optimization of hardware en control aspects.

show abstract

Section: Optimization Results and Comparison With Existing Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hardware and control co-design enabled by a state-space formulation of cascaded, interconnected PID controlled systems

Haemers

Ionescu

Depraetere

et al. 2021

2021 7th International Conference on Optimization and Applications (ICOA)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The co-design examples mentioned so far succeed in the simultaneous optimization of separate hardware parts and controller tuning for fixed and rather modest feedback loops. In contrast, the author of this work recently proposed an optimization methodology to perform a thorough co-design of the hardware architecture and control configuration [13]. The proposed methodology can perform a hardware architecture and control configuration co-design in which more parts can be optimized at the same time, while considering more extensive and also changing controller architectures.…”

Section: Introductionmentioning

confidence: 99%

Optimal Hardware and Control Co-Design Applied to an Active Car Suspension Setup

et al. 2021

Self Cite

View full text Add to dashboard Cite

For complex systems, it is not easy to obtain optimal designs for the hardware architecture and control configurations. Every design aspect influences the final performance, and often the interactions of the different components cannot be clearly determined in advance. In this work, a novel co-design optimization method was applied that allows the optimal placement and selection of actuators and sensors to be performed simultaneously with the determination of the control architecture and associated controller tuning parameters. This novel co-design method was applied to a state-space model of a downscaled active car suspension laboratory setup. This setup mimics a car driving over a specific road surface while active components in the suspension have to increase the driver’s comfort by counteracting unwanted vibrations. The result of this co-design optimization methodology is a Pareto front that graphically represents the trade-off between the maximum performance and the total implementation cost; the co-design results were validated with measurements of the physical active car suspension setup. The obtained controller tuning parameters are compared herein with existing controller tuning methods to demonstrate that the co-design method is able to determine optimal controller tuning parameters.

show abstract

“…To deal with the interactions between sub-loops in a process, a theoretical framework was proposed, which is useful for controller design problems [27]. An optimization method was proposed to make a trade-off between implementation cost and achievable performance for multiple interacting subsystems [28]. In order to optimize the choice of the cost function and their effect to the overall system performance, strategy for selection of the optimal criteria according to context conditions was proposed and a windmill park experiment was conducted to validate the performance [29].…”

Section: Introductionmentioning

confidence: 99%

The Application of a New PID Autotuning Method for the Steam/Water Loop in Large Scale Ships

et al. 2020

Self Cite

View full text Add to dashboard Cite

In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a ‘forbidden region’ on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller’s parameters can be obtained by locating the frequency response of the controlled system at the edge of the ‘forbidden region’. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method.

show abstract

Towards a generic optimal co-design of hardware architecture and control configuration for interacting subsystems

Cited by 10 publications

References 54 publications

Hardware and control co-design enabled by a state-space formulation of cascaded, interconnected PID controlled systems

Hardware and control co-design enabled by a state-space formulation of cascaded, interconnected PID controlled systems

Optimal Hardware and Control Co-Design Applied to an Active Car Suspension Setup

The Application of a New PID Autotuning Method for the Steam/Water Loop in Large Scale Ships

Contact Info

Product

Resources

About