Simulation of a suspension system with adaptive fuzzy active force control

Mailah

Journal of Vibration and Control

et al. 2017

Since one of the influential factors that affects the spray distribution pattern is the spray boom movements which are mostly induced by soil unevenness, most of the recent sprayers are equipped with suspensions for improving the uniformity of spray application in the field. This paper investigates the suitability of improving the sprayer suspension dynamics performance by employing a robust intelligent control scheme, namely active torque control (ATC) based method in reducing the undesired vibration through a simulation study. The ATC scheme with a self-tuning fuzzy proportional-integral-derivative (PID) (ATC-STF-PID) controller was first designed and simulated. Then an artificial intelligence (AI) method using iterative learning (IL) was embedded and implemented into the ATC loop to compute the estimated inertial parameter of the system; this scheme is known as ATCAIL. Thereafter, the performance of the ATCAIL scheme is later compared to the ATC with artificial neural network (ATCANN), ATC-STF-PID and STF-PID controllers in time and frequency domains. The results of simulation work affirm that ATC-based schemes can improve the system performance of the active rolling suspension in relation to roll vibration suppression. In other words, both the ATCAIL and ATCANN schemes show better responses in comparison to the ATC-STF-PID controller scheme. The results also imply that the ATCAIL scheme is indeed effective in suppressing the vibration of a sprayer boom structure.

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vibration suppression of sprayer boom structure using active torque control and iterative learning. Part I: Modelling and control via simulation

Mailah

Journal of Vibration and Control

et al. 2017

“…Consequently, after scrutinizing the literature on the related subject matters, it was found that the active force control (AFC) method is a potential and seemingly the most appropriate approach to overcome the problem. While the integration of AFC with a classical controller has been used in active suspension systems of vehicles to reduce the amplitude of undesired vibrations in (Mailah and Priyandoko, 2007; Priyandoko et al., 2009), the application of AFC strategy to control the unwanted vibration of a sprayer boom directly has been carried out through simulation works (Tahmasebi et al., 2012, 2013a, 2013b, 2017). It should be noted that since only the torque of the actuator of the spray boom is exclusively controlled in the proposed active suspension, the term ‘force’ is substituted with ‘torque’ and hence the term, active torque control (ATC) is consistently used throughout the paper in place of AFC.…”

Section: Introductionmentioning

confidence: 99%

Vibration suppression of sprayer boom structure using active torque control and iterative learning. Part II: Experimental implementation

Journal of Vibration and Control

Mailah

et al. 2017

The most common technique of protecting crops from diseases is by applying a chemical process whereby a mixture of chemicals and water are sprayed onto the crops via a sprayer. Nowadays, modern sprayers are generally implemented to suspension systems for reducing the unwanted vibration of the spray boom structure to improve the uniformity of spray distribution in the agricultural field environment. This paper serves to present a new alternative to address and resolve the vibration control problem of the moving sprayer structures. The application of an active torque control (ATC) method to cancel the undesired vibration of the sprayer boom is thus proposed. As a continuation from Part I that deals with the modeling and simulation aspect, Part II explains the practical facet of the study through the implementation of ATC and iterative learning (ATCAIL) control scheme to an experimental spray boom structure as a basis to validate the effectiveness and robustness of the scheme as simulated and described at length in Part I. A sprayer boom suspension system test rig was specifically designed and developed to verify this control scheme that was principally chosen due to its ease of implementation through the exploitation of simple proportional–integral–derivative (PID), ATC and iterative learning algorithms. The system performance was evaluated and compared to the PID and ATC–PID control schemes for benchmarking. The results demonstrate the capability of the practical ATCAIL scheme to improve the vibration suppression in both time and frequency domains, thereafter guaranteeing a more uniform spray distribution of chemicals on a bumpy terrain. The experimental outcomes are in good agreements with the simulation counterpart.

“…The AFC approach was primarily used for vibration control by Hewit et al [20] to control motion of a flexible manipulator. Furthermore, the AFC integrated with conventional controller was employed in active suspension systems of vehicles [19,[21][22][23] though it has been applied to roll vibration cancellation of a spray boom [24][25][26][27]. In addition, AFC was utilized in trajectory control of a mobile robot [28].…”

Section: Introductionmentioning

confidence: 99%

Active Off-Road Seat Suspension System Using Intelligent Active Force Control

Journal of Low Frequency Noise, Vibration and Active Control

2015

Transmitted vibration from vehicles to driver body generates some problems in the long term. Passive and active seat suspensions are used in heavy duty vehicles to reduce unwanted vibration and prevent health problems due to oscillation. Seat suspension must minimize the driver's body displacement and acceleration to increase riding convenience. Active force control (AFC) method is a new technique which is used in active controllers and makes them more accurate. Therefore, this work represents the possibility of applying AFC strategy for an active seat suspension control to increase its robustness. An AFC-based scheme is designed and simulated in MATLAB software. In addition, artificial neural network (ANN) is integrated into the AFC loop to approximate estimated mass of the seat and human body for the proposed controller. The training of ANN with multi-layer feedforward structure is carried out using Levenberg-Marquardt learning algorithm. To evaluate the neuro-AFC control system robustness, the seat is subjected to various types of disturbances. The results of the present study illustrate that the neuro-AFC technique is computationally simple and efficient compared to the classic proportional-integral-derivative (PID) controller in suppressing undesired vibration of heavy duty vehicles' seat. The neuro-AFC scheme is found to demonstrate superior performance for various road profiles compared to pure PID controller, and it can be successfully utilized in heavy duty vehicles such as industrial and agricultural tractors.