The New Design Strategy on PID Controllers

Wang, Wei

doi:10.5772/34670

Cited by 6 publications

(6 citation statements)

References 40 publications

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“…We could only confirm that the SAF implements a proportional-derivative (PD) control of the steering in that both (i) the direct values of parameters and (ii) their derivatives are incorporated in its code. The only integral term included in the terminal set of the GP-the integral of the lateral deviation-is not incorporated by the GP in the best-evolved SAF, which is consonant with the findings that the integral term could be obsolete in some nonlinear PID controllers [27].…”

Section: Resultssupporting

confidence: 52%

“…Moreover, even if we assume that it is possible to handcraft the code (applying various top-down, theoretical approaches based on vehicle dynamics [25,27,28]) of a more complex, nonlinear PID SAF that controls the steering of an unstable, skidding car in such a way so it regains its stability in a more effective way than the simple PD and PID controllers based on the servo-control model, neither the…”

Section: Evolving the Steering Controller Via Gpmentioning

confidence: 99%

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Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

Алексеева¹,

Tanev²,

Shimohara³

2018

Algorithms

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Abstract:The most important characteristics of autonomous vehicles are their safety and their ability to adapt to various traffic situations and road conditions. In our research, we focused on the development of controllers for automated steering of a realistically simulated car in slippery road conditions. We comparatively investigated three implementations of such controllers: a proportional-derivative (PD) controller built in accordance with the canonical servo-control model of steering, a PID controller as an extension of the servo-control, and a controller designed heuristically via the most versatile evolutionary computing paradigm: genetic programming (GP). The experimental results suggest that the controller evolved via GP offers the best quality of control of the car in all of the tested slippery (rainy, snowy, and icy) road conditions.

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Section: Resultssupporting

confidence: 52%

Section: Evolving the Steering Controller Via Gpmentioning

confidence: 99%

Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

Алексеева¹,

Tanev²,

Shimohara³

2018

Algorithms

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“…Compared with the performance based on using other methods ( [14], [22]), the time taking for the stability reduces from 5 second to 2 second.…”

Section: B Simulation Examplesmentioning

confidence: 83%

The optimization method for a kind of uncertain networked systems based on the stripping principle and optimal control

Wang

2012

Proceedings of the 10th World Congress on Intelligent Control and Automation

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We consider the problem of optimal control for a kind of uncertain networked systems which are composed of some heteromorphic subsystems in this paper. For the trouble of encountering the complex structure, the unavoidable uncertainties and/or disturbances of networked systems, we try to remove or eliminate the interconnected parts, uncertainties and disturbances from the system by using the method based on the stripping principle. So we can translate the control problem of uncertain networked systems into that of decentralized control. And then we use optimal control method for the remainder parts of the subsystems respectively. It is the certain kind of optimization in the rejection of uncertainties or disturbances and the optimal control for the remaining parts that we can implement the optimal control for the whole of uncertain networked systems. The theoretical analysis and simulation results are provided to indicate the effectiveness of the proposed approach.

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“…The control output, u of this generalized continuous-form PID control function, has a distinct signal path to the reference set-point r and the output tracked signal y as illustrated in Figure 2. This kind of control structure exhibits the separation principle [10,45] that the design problems of set-point tracking and robustness plus disturbance rejection can be achieved independently and at the same time in a control law [4,46]. Simplifying (2) by assuming λ p , λ i , λ d = 1 and rearranging, the result is a compact PID structure given by (7d) and illustrated in Figure 2.…”

Section: Critic Pid Controllermentioning

confidence: 99%

“…To compute ω n using (42), our approach is to encode the fuzzy behaviour of the optimal response of the closed PID-loop model with changing b and c as a fuzzy inference system (FIS), defined by (44), and synthesized as a fuzzy basis function (FBF) [8] defined in (45). This method is used to automatically compute the appropriate x s or x pk with respect to the inputs b and c respectively.…”

Section: Setting ω N By Fuzzy Inference Of the Closed Pid-loop Responsementioning

confidence: 99%

Speed Control of DC Motors: Optimal Closed PID-Loop Model Predictive Control

Somefun¹,

Akingbade²,

Dahunsi³

2020

ujca

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One of the lowest level control tasks, especially in robotics and other manufacturing industries, upon which other high-level controls are dependent, is the speed control of a dc motor. Usually, tuning the parameters of the proportional integral derivative (PID) controller for this task employs established conventional methods that expose the knowledge of nominal process model parameters to the control algorithm. These methods have found widespread use. Notwithstanding, a promising line of inquiry is: to search alternate possibilities of a PID being designed to automatically achieve comparable good control performance without using a formal mathematical process model approximation of the actual physical system, such as dc motor plant, in the frequency or time domain. In this paper, we propose an intelligent PID design method, "optimal closed PID-loop model predictive control", that answers this question using the characteristic settling-time (including delay-time) property of dynamic processes. The performance of this proposed method is benchmarked with popular process-model based methods. Simulation results illustrate the promise and effectiveness of the proposed tuning method, in ensuring good closed-loop performance quality for the dc motor, without using formal process models.

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The New Design Strategy on PID Controllers

Cited by 6 publications

References 40 publications

Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

The optimization method for a kind of uncertain networked systems based on the stripping principle and optimal control

Speed Control of DC Motors: Optimal Closed PID-Loop Model Predictive Control

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