Large Extent Of Model Uncertainties Research Articles

High Performance Motion Trajectory Tracking Control of Pneumatic Cylinders: A Comparison of Some Nonlinear Control Algorithms

The dynamics of pneumatic systems are highly nonlinear, and there normally exists a large extent of model uncertainties; the precision motion trajectory tracking control of pneumatic cylinders is still a challenge. In this paper, two typical nonlinear controllers—adaptive controller and deterministic robust controller—are constructed firstly. Considering that they have both benefits and limitations, an adaptive robust controller (ARC) is further proposed. The ARC is a combination of the first two controllers; it employs online recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the robust control method to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. In order to solve the conflicts between the robust control design and the parameter adaption law design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Theoretically, ARC possesses the advantages of the adaptive control and the deterministic robust control, and thus an even better tracking performance can be expected. Extensive comparative experimental results are presented to illustrate the achievable performance of the three proposed controllers and their performance robustness to the parameter variations and sudden disturbance.

PID Parameters Optimization Using Genetic Algorithm Technique for Electrohydraulic Servo Control System

Electrohydraulic servosystem have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to increase the reliability, controllability and utilizing the superior speed of response achievable from electrohydraulic systems, further research is required to develop a control software has the ability of overcoming the problems of system nonlinearities. In This paper, a Proportional Integral Derivative (PID) controller is designed and attached to electrohydraulic servo actuator system to control its angular position. The PID parameters are optimized by the Genetic Algorithm (GA). The controller is verified on the state space model of servovalve attached to a rotary actuator by SIMULINK program. The appropriate specifications of the GA for the rotary position control of an actuator system are presented. It is found that the optimal values of the feedback gains can be obtained within 10 generations, which corresponds to about 200 experiments. A new fitness function was implemented to optimize the feedback gains and its efficiency was verified for control such nonlinear servosystem.

Comparative implementation studies of the minimal controller synthesis algorithm on an electrohydraulic actuator plant

Electrohydraulic servosystems have large extent of model uncertainties and generally difficult to control. The current paper studies the application of the direct adaptive minimal controller synthesis (MCS) algorithm to an electrohydraulic positioning system. Comparative implementation studies are presented of a typical servohydraulic positioning system, as used in aerospace applications. The performance of the MCS controller is evaluated through experimental and analytical studies. In order to investigate the robustness of the MCS control, the system is operated away from nominal working condition (by changing the supply pressure and/or accumulators settings) and the performances of both the MCS control and the proportional plus derivative feedback (P + DFB) controller were compared. The results show that MCS is fairly insensitive to parameter variations, unmodelled dynamics and external disturbances, yielding much better response characteristics, compared with those of a conventional P + DFB controller.

Nonlinear control for a class of hydraulic servo system

The dynamics of hydraulic systems are highly nonlinear and the system may be subjected to non-smooth and discontinuous nonlinearities due to directional change of valve opening, friction, etc. Aside from the nonlinear nature of hydraulic dynamics, hydraulic servo systems also have large extent of model uncertainties. To address these challenging issues, a robust state-feedback controller is designed by employing backstepping design technique such that the system output tracks a given signal arbitrarily well, and all signals in the closed-loop system remain bounded. Moreover, a relevant disturbance attenuation inequality is satisfied by the closed-loop signals. Compared with previously proposed robust controllers, this paper's robust controller based on backstepping recursive design method is easier to design, and is more suitable for implementation.

Non-linear adaptive robust control of electro-hydraulic systems driven by double-rod actuators

This paper studies the high performance robust motion control of electro-hydraulic servo-systems driven by double-rod hydraulic actuators. The dynamics of hydraulic systems are highly non-linear and the system may be subjected to non-smooth and discontinuous non-linearities due to directional change of valve opening, friction and valve overlap. Aside from the non-linear nature of hydraulic dynamics, hydraulic servosystems also have large extent of model uncertainties. To address these challenging issues, the recently proposed adaptive robust control (ARC) is applied and a discontinuous projection based ARC controller is constructed. The resulting controller is able to take into account the effect of the parameter variations of the inertia load and the cylinder hydraulic parameters as well as the uncertain non-linearities such as the uncompensated friction forces and external disturbances. Non-differentiability of the inherent non-linearities associated with hydraulic dynamics is carefully examined and addressing strategies are provided. Compared with previously proposed ARC controller, the controller in the paper has a more robust parameter adaptation process and may be more suitable for implementation. Finally, the controller guarantees a prescribed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain non-linearities while achieving asymptotic tracking in the presence of parametric uncertainties.