Institute of Fundamental Technological Research

A novel method for adaptive semi-active vibration control of structures subjected to a movingload is studied. The velocity of the load is assumed to be time-varying. The controller consistsof an internal model of the moving load, which is being frequently updated to accommodatechanges in the load's velocity. The control method relies on a near-optimal switching con-trol law that is based on the solution to the algebraic Lyapunov equation. The infinite-horizonformulation of the control problem enables us to use efficient numerical algorithms for adap-tive recomputing of the control signal. The asymptotic stability of the closed-loop system andperformance improvement in comparison to the passive method are analysed and formallyproven. The controller is tested by means of numerical experiments involving a flexible beamequipped with a set of semi-active viscous dampers. We investigate three distinct simulationscenarios, which correspond to highly non-uniform motions of the load that consist of accel-eration, deceleration and temporary halt phases. The results of the simulations are comparedto passive and optimal open-loop strategies.

vibration control, adaptive control, semi-active control, moving load, stabilisation

A novel adaptive control for structures subjected to seismic excitation is presented. The aim of the control is to provide a high stabilizing performance involving a limited computational burden while allowing for frequent update of the control decision to cope with the changes in the excitation characteristics. Consequently, the control is based on a computationally efficient solution to the infinite-horizon linear optimal control problem, which employs the autoregressive model for excitation signals and the alpha-shift method for a performance index. Based on numerical simulations involving an actively controlled 20-story building subjected to different earthquake scenarios, we demonstrate that the adaptive control outperforms the standard LQG and H∞ regulators. Our analysis of the controller's computational complexity has confirmed that the presented method can be successfully implemented in large-scale structures that are equipped with active control devices. Our follow up research will validate the performance of the designed control on a real environment platform and we will design an adaptive controller to mitigate vibration in semi-active structures.

adaptive control, structural control, autoregressive model, vibration, optimal stabilization

Torsional vibrations induced in drilling systems are detrimental to the condition of the machine and to the effectiveness of the engineering process. The cause of vibrations is a nonlinear and unknown friction between a drill string and the environment, containing jumps in its characteristics. Nonlinear behaviour of the friction coefficient results in self-excited vibration and causes undesirable stick-slip oscillations. The aim of this paper is to present a novel adaptive technique of controlling vibrating systems. The scheme is based on the linear quadratic regulator and uses direct measurements of the friction torque to synthesize its linear dynamic approximation. This approach allows generating a control law that takes into account the impact of the friction on the system dynamics and optimally steers the system to the desired trajectory. The controller's performance is examined via numerical simulations of the stabilization of the drilling system. The proposed solution outperforms the comparative LQG regulator in terms of the minimization of the assumed cost functional and the overall stability of the control system under the nonlinear disturbance.

vibration control, adaptive control, linear-quadratic-regulator, drilling control

In this paper, an online adaptive continuous-time control algorithm will be studied in the vibration control problem. The examined algorithm is a Reinforcement Learning based scheme able to adapt to the changing system’s dynamics and providing control converging to the optimal control. Firstly, a brief description of the algorithm is provided. Then, the algorithm is studied by the numeric simulation. The controlled model is a simple conjugate oscillator with a sudden change of its rigidity. The effectiveness of the adaptation of the algorithm is compared to the simulation results of controlling the same object by the traditional Linear Quadratic Regulator. Because of the lack of constraints for a system size or its linearity, this algorithm is suitable for optimal stabilization of more complex vibrating structures.

Vibration control, Adaptive control, Optimal control, Policy iterations, Hamilton-Jacobi-Bellman equation

An efficient suboptimal semi-active control for mitigating structural vibration is studied. The control relies on a practical state-feedback switching law and, as demonstrated in the previous research, it guarantees the asymptotic stability. The focus of this work is to provide the qualitative and quantitative analysis on the control’s optimality in the sense of an energy-related performance index. Firstly, a method for optimal selection of the passive strategy that underlies a design of the control’s switching law is proposed. Next, the conditions asserting the performance of the semi-active control are formulated and proven. Finally, the controller’s performance is validated by numerical experiments involving a 2DOF semi-active structure, where the suboptimal control is compared to the optimal open-loop solution and a heuristic strategy.

In this paper, a novel control algorithm for vibration attenuation is presented. The proposed scheme is developed to control linear systems with a presence of an external disturbance. The goal of the control is to steer the system to prescribed reference trajectory by minimizing associated quadratic performance index. The synthesis of the control law consists of two steps. At the first step, past measures of disturbance are used to develop a local linear approximation of dynamics of the disturbance signal. Weights of the associated auto-regressive model are calculated by the least-square algorithm. At the second step, the calculated model is used to obtain a linear time-invariant approximation of the control system. The receding horizon control law is then calculated by using finite horizon Linear Quadratic Regulator. The algorithm is verified numerically for a torsional vibrating system under nonlinear, time-varying friction. The results of the simulation are compared to a standard Linear Quadratic Gaussian control.

The aim of this paper is to present a novel adaptive technique of control of the vibrating drilling systems. The algorithm constitutes an adaptive linear quadratic regulator that uses direct measurements of the disturbance to synthesize its linear dynamic approximation. This approach allows generating control law that includes the impact of the friction on the system dynamics and optimally steers the system to the desired trajectory. The effectiveness of the algorithm is validated via comprehensive numerical simulations of the control of the simplified drilling model. The results are compared to these obtained with the use of the Linear Quadratic Gaussian regulator.

vibration control, drillstring, adaptive control, auto-regressive model