Experimental investigation of feedforward inverse control with disturbance observer for acceleration tracking of electro-hydraulic shake table

Electro-hydraulic shake tables (EHSTs) are indispensable equipments in laboratory for evaluating structural performance subject to vibration environment. A novel feedforward inverse control with disturbance observer strategy is proposed in this paper in order to improve the acceleration tracking performance of the EHST system. The EHST system is firstly controlled by the three variable controller (TVC) to obtain a coarse time waveform replication accuracy, and then the parametric transfer function of the TVC controlled EHST system is identified with the H1 estimation method and complex curving fitting technology. Next, the zero magnitude error tracking control technology is employed to deal with the estimated non-minimum phase transfer function so as to design a stable and casual inverse model, and the proposed controller comprised of feedforward inverse controller and disturbance observer is further established based on the designed inverse model. Therefore, the proposed algorithm combines the virtues of feedforward inverse control and disturbance observer. The proposed algorithm is firstly programmed by MATLAB/Simulink software and then is compiled to an Advantech computer with real-time operating system for implementation. Finally, experiments are carried out on a unidirectional EHST system and the results demonstrate that a better acceleration tracking performance is achieved with the proposed controller than with the other conventional controllers

Simulation method of impact load for vehicle drivetrain on durability test rig

Fatigue and durability tests are important to develop or to optimize the vehicle drivetrain system. Using the vehicle drivetrain road load simulation test rig to reproduce the longitudinal driving load of the vehicle on the real road and the vertical impact load caused when the vehicle is on a bumpy pavement. In order to improve the control accuracy and convergence speed, an iterative learning control (ILC) method is presented. After 10 times of learning, the control error of iterative learning control method is 4.8 %, it is better than the 7.1 % error achieved by proportional-integral-derivative (PID) control. The simulation results demonstrate that the ILC can improve the convergence rate and increase the tracking accuracy than the PID control method

Hydraulic Actuated Automotive Cooling Systems - Nonlinear Control and Test

The replacement of traditional automotive mechanical cooling system components with computer controlled servo-motor driven actuators can improve temperature tracking and reduce parasitic losses. The integration of hydraulic actuators in the engine cooling circuit offers greater power density in a smaller package space when compared with electric actuators. In this paper, a comprehensive nonlinear backstepping robust control technique is developed to regulate the engine coolant temperature by controlling a hydraulic coolant pump and radiator fan. An experimental test bench has been assembled to investigate the hydraulic automotive thermal system performance. Representative numerical and experimental results are presented and discussed. Overall, the proposed controller was successful in tracking prescribed engine temperature profiles while harmoniously regulating the power consumption of the coolant pump and radiator fan

Pneumatic motion control systems for modular robots

This thesis describes a research study in the design, implementation, evaluation and commercialisation of pneumatic motion control systems for modular robots. The research programme was conducted as part of a collaborative study, sponsored by the Science and Engineering Research Council, between Loughborough University and Martonair (UK) Limited. Microprocessor based motion control strategies have been used to produce low cost pneumatic servo-drives which can be used for 'point-to-point' positioning of payloads. Software based realtime control strategies have evolved which accomplish servo-controlled positioning while compensating for drive system non-linearities and time delays. The application of novel compensation techniques has resulted in a significant improvement in both the static and dynamic performance of the drive. A theoretical foundation is presented based on a linearised model of a pneumatic actuator, servo-valve, and load system. The thesis describes the design and evolution of microprocessor based hardware and software for motion control of pneumatic drives. A British Standards based test-facility has allowed control strategies to be evaluated with reference to standard performance criteria. It is demonstrated in this research study that the dynamic and static performance characteristics of a pneumatic motion control system can be dramatically improved by applying appropriate software based realtime control strategies. This makes the application of computer controlled pneumatic servos in manufacturing very attractive with cost performance ratios which match or better alternative drive technologies. The research study has led to commercial products (marketed by Martonair Ltd), in which realtime control algorithms implementing these control strategy designs are executed within a microprocessor based motion controller

Model-Based Control Design of an EHA Position Control Based on Multicriteria Optimization

For the control of dynamic systems such as an Electro-Hydraulic Actuator (EHA), there is a need to optimize the control based on simulations, since a prototype or a physical system is usually not available during system design. In consequence, no system identification can be performed. Therefore, it is unclear how well a simulation model of an EHA can be used for multicriteria optimization of the position control due to the uncertain model quality. To evaluate the suitability for control optimization, the EHA is modeled and parameterized as a grey-box model using existing parameters independent of test bench experiments. A method for multi-objective optimization of a controller is used to optimize the position control of the EHA. Finally, the step responses are compared with the test bench. The evaluation of the step responses for different loads and control parameters shows similar behavior between the simulation model and the physical system on the test bench, although the essential phenomena could not be reproduced. This means that the model quality achieved by modeling is suitable as an indication for the optimization of the control by simulation without a physical system

The Fourteenth Scandinavian International Conference on Fluid Power, SICFP15: Abstracts

At this time the conference includes various themes like hybrids, drives, digital hydraulics and pneumatics. Special attention in the program is given for energy efficiency, renewable energy production and energy recovery. They are reflecting well the situation, where environmental issues and energy saving are increasingly important issues

Implementation of Iterative Learning Control on a Pneumatic Actuator.

Masters Degree. University of KwaZulu-Natal, Durban.Pneumatic systems play a pivotal role in many industrial applications, such as in petrochemical industries, steel manufacturing, car manufacturing and food industries. Besides industrial applications, pneumatic systems have also been used in many robotic systems. Nevertheless, a pneumatic system contains different nonlinear and uncertain behaviour due to gas compression, gas leakage, attenuation of the air in pipes and frictional forces in mechanical parts, which increase the system’s dynamic orders. Therefore, modelling a pneumatic system tends to be complicated and challenges the design of the controller for such a system. As a result, employing an effective control mechanism to precisely control a pneumatic system for achieving the required performance is essential. A desirable controller for a pneumatic system should be capable of learning the dynamics of the system and adjusting the control signal accordingly. In this study, a learning control scheme to overcome the highlighted nonlinearity problems is suggested. Many industrial processes are repetitive, and it is reasonable to make use of previously acquired data to improve a controller’s convergence and robustness. An Iterative Learning Control (ILC) algorithm uses information from previous repetitions to learn about the system’s dynamics. The ILC algorithm characteristics are beneficial in real-time control given its short time requirements for responding to input changes. Cylinder-piston actuators are the most common pneumatic systems, which translate the air pressure force into a linear mechanical motion. In industrial automation and robotics, linear pneumatic actuators have a wide range of applications, from load positioning to pneumatic muscles in robots. Therefore, the aim of this research is to study the performance of ILC techniques in position control of the rod in a pneumatic position-cylinder system. Based on theoretical analysis, the design of an ILC is discussed, showing that the controller can satisfactorily overcome nonlinearities and uncertainties in the system without needing any prior knowledge of the system’s model. The controller has been designed in such a way to even work on non-iterative processes. The performance of the ILC-controlled system is compared with a well-tuned PID controller, showing a faster and more accurate response