Multi-objective optimization of active suspension predictive control based on improved PSO algorithm

The design and control for active suspension is of great significance for improving the vehicle performance, which requires considering simultaneously three indexes including ride comfort, packaging requirements and road adaptability. To find optimal suspension parameters and provide a better tradeoff among these three performances, this paper presents a novel multi-objective particle swarm optimization (MPSO) algorithm for the suspension design. The mathematical model of quarter-car suspension is first established, and it integrates the hydraulic servo actuator model. Further a model predictive controller is designed for the suspension by using the control strategies of multi-step forecast, rolling optimization and online correction of predictive control theory. To use vehicle body acceleration, tire deflection and suspension stroke to represent the above three performances respectively, a multi-objective optimization model is constructed to optimize the suspension stiffness and damping coefficients. The MPSO algorithm includes extra crossover operations, which are applied to find the Pareto optimal set. The rule to update the Pareto pool is that the newly selected solutions must have two better performances compared with at least one already existed in the Pareto pool, which ensures that each solution is non-dominated within the Pareto set. Finally, numerical simulations on a vehicle-type example are done under B-level road surface excitation. Simulation results show that the optimized suspension can effectively reduce the vertical vibrations and improve the road adaptability. The model predictive controller also shows high robustness with vehicle under null load, half load and full load. Therefore, the proposed MPSO algorithm provides a new valuable reference for the multi-objective optimization of active suspension control

Active vibration control of flexible bodied railway vehicles via smart structures

Future railway vehicles are going to be designed lighter in order to achieve higher speed. Suppressing the flexible modes becomes a crucial issue for improving the ride quality of the light-weight high speed railway vehicles. The concept of smart structure brings structural damping to flexible structures by integrating smart actuators and sensors onto the structure. Smart structure eliminates the need for extensive heavy mechanical actuation systems and achieves higher performance levels through their functionality for suppressing the flexible modes. Active secondary suspension is the effective conventional approach for vibration control of the railway vehicle to improve the ride quality. But its ability in suppressing the flexible modes is limited. So it is motivated to combine active structural damping for suppressing the flexible modes and the vibration control through active secondary suspension which has an effect on both rigid and flexible modes. The side-view model of the flexible-bodied railway vehicle integrated with piezoelectric actuators and sensors is derived. The procedure for selection of placement configurations of the piezoelectric actuators and sensors using structural norms is presented. Initial control studies show that the flexibility of the vehicle body will cause a considerable degradation in ride quality if it is neglected in the design model. Centralized and decentralized control strategies with various control approaches (e.g. modal control with skyhook damping, LQG/H2 control, H_infinity control and model predictive control (MPC))are applied for the combined control of active structural damping and active suspension control. The active structural damping effectively suppresses the flexible modes as a complement to the work of the active suspension control

Performance Comparison between Sliding Mode Control with PID Sliding Surface and PID Controller for an Electro-hydraulic Positioning System

In this paper, the position tracking performance of an electro-hydraulic hydraulic servo (EHS) system using sliding mode control (SMC) with proportional-integral-derivative (PID) sliding surface is presented. The dynamics of the EHS system in modelling process are developed by consider its nonlinearities incorporating a friction model. Then, SMC with PID scheme is derived from the developed dynamics equation and stability of the control system is theoretically proven by Lyapunov theorem. Finally, simulation work is demonstrated and the result shows the proposed controller can achieve better tracking performance compared with conventional PID controller with good accuracy for any desired trajectory

Third-order robust fuzzy sliding mode tracking control of a double-acting electrohydraulic actuator

In the industrial sector, an electrohydraulic actuator (EHA) system is a common technology. This system is often used in applications that demand high force, such as the steel, automotive, and aerospace industries. Furthermore, since most mechanical actuators' performance changes with time, it is considerably more difficult to assure its robustness over time. Therefore, this paper proposed a robust fuzzy sliding mode proportional derivative (FSMCPD) controller. The sliding mode controller (SMC) is accomplished by utilizing the exponential law and the Lyapunov theorem to ensure closed loop stability. By replacing the fuzzy logic control (FLC) function over the signum function, the chattering in the SMC controller has been considerably reduced. By using the sum of absolute errors as the objective function, particle swarm optimization (PSO) was used to optimize the controller parameter gain. The experiment results for trajectory tracking and the robustness test were compared with the sliding mode proportional derivative (SMCPD) controller to demonstrate the performance of the FSMCPD controller. According to the findings of the thorough study, the FSMCPD controller outperforms the SMCPD controller in terms of mean square error (MSE) and robustness index (RI)

The strengthening of Islamic values on students through the metaphor of accepting death: an Indonesian perception

Death is a sure entity for every human that cannot be avoided in human life. The purpose of this research was to reveal that the usage of metaphor technique called, “The Acceptance of Death” in group counselling can improve Islamic values on Muslim students. This study employed an action research using The Kemmis Model with the stages of planning, action, observation, and reflection. This research implemented group counselling with metaphor technique of accepting death by students. The research subjects were 20 female students of State Islamic University of Sultan Syarif Kasim Riau who lived in the campus dormitory. The selection of the research subjects was done randomly by choosing the female students who were willing to join the group counselling activity. The research results showed that the practice of metaphor technique of “The Acceptance of Death” in the group counselling can strengthen the Islamic values and their characteristics as Muslims. They understand their previous mistakes and are willing to be better for the sake of their life. They have the commitment to become the best students and the best Muslims

Model based control strategies for a class of nonlinear mechanical sub-systems

This paper presents a comparison between various control strategies for a class of mechanical actuators common in heavy-duty industry. Typical actuator components are hydraulic or pneumatic elements with static non-linearities, which are commonly referred to as Hammerstein systems. Such static non-linearities may vary in time as a function of the load and hence classical inverse-model based control strategies may deliver sub-optimal performance. This paper investigates the ability of advanced model based control strategies to satisfy a tolerance interval for position error values, overshoot and settling time specifications. Due to the presence of static non-linearity requiring changing direction of movement, control effort is also evaluated in terms of zero crossing frequency (up-down or left-right movement). Simulation and experimental data from a lab setup suggest that sliding mode control is able to improve global performance parameters

Optimization of Modified Sliding Mode Controller for an Electro-hydraulic Actuator System with Mismatched Disturbance

This paper presents the design of the modified sliding mode controller (MSMC) for the purpose of tracking the nonlinear system with mismatched disturbance. Provided that the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA), and particle swarm optimization (PSO) techniques are used to optimize these parameters in order to achieve a predefined system’s performance. In respect of system’s performance, it is evaluated based on the tracking error present between reference inputs transferred to the system and the system output. This is followed by verification of the efficiency of the designed controller in simulation environment under various values, with and without the inclusion of external disturbance. It can be seen from the simulation results that the MSMC with PSO exhibits a better performance in comparison to the performance of the similar controller with GSA in terms of output response and tracking error

Volume 3 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 8: Pneumatics Group 9 | 11: Mobile applications Group 10: Special domains Group 12: Novel system architectures Group 13 | 15: Actuators & sensors Group 14: Safety & reliabilit

Modelling of an electro-hydraulic actutor using extended adaptive distance gap statistic approach

The existence of high degree of non-linearity in Electro-Hydraulic Actuator (EHA) system has imposed a challenging task in developing its model so that effective control algorithm can be proposed. In general, there are two modelling approaches available for EHA system, which are the dynamic equation modelling method and the system identification modelling method. Both approaches have disadvantages, where the dynamic equation modelling is hard to apply and some parameters are difficult to obtain, while the system identification method is less accurate when the system’s nature is complicated with wide variety of parameters, nonlinearity and uncertainties. This thesis presents a new modelling procedure of an EHA system by using fuzzy approach. Two sets of input variables are obtained, where the first set of variables are selected based on mathematical modelling of the EHA system. The reduction of input dimension is done by the Principal Component Analysis (PCA) method for the second set of input variables. A new gap statistic with a new within-cluster dispersion calculation is proposed by introducing an adaptive distance norm in distance calculation. The new gap statistic applies Gustafson Kessel (GK) clustering algorithm to obtain the optimal number of cluster of each input. GK clustering algorithm also provides the location and characteristic of every cluster detected. The information of input variables, number of clusters, cluster’s locations and characteristics, and fuzzy rules are used to generate initial Fuzzy Inference System (FIS) with Takagi-Sugeno type. The initial FIS is trained using Adaptive Network Fuzzy Inference System (ANFIS) hybrid training algorithm with an identification data set. The ANFIS EHA model and ANFIS PCA model obtained using proposed modelling procedure, have shown the ability to accurately estimate EHA system’s performance at 99.58% and 99.11% best fitting accuracy compared to conventional linear Autoregressive with External Input (ARX) model at 94.97%. The models validation result on different data sets also suggests high accuracy in ANFIS EHA and ANFIS PCA model compared to ARX model

Legged Robots

International audienc