This paper presents a robust control scheme for flexible link robotic manipulators, which is based on considering the flexible mechanical structure as a system with slow (rigid) and fast (flexible) modes that can be controlled separately. The rigid dynamics is controlled by means of a robust sliding-mode approach with wellestablished stability properties while an LQR optimal design is adopted f...

In this paper, we look at a model depicting the relationship of cancer cells in different development stages with immune cells and a cell cycle specific chemotherapy drug. The model includes a constant delay in the mitotic phase. By applying optimal control theory, we seek to minimize the cost associated with the chemotherapy drug and to minimize the number of tumor cells. Global existence of a...

A covariance condition is shown to be a necessary condition for the existence of a finite control law associated with discrete-time quadratic loss-minimisation problems. Sufficient conditions (including the covariance condition) are then determined which extend the range of optimal-control problems, for which a well defined control law may be calculated. The results may also be applied to solvi...

The tracking control problem with saturation constraint for a class of unicycle-modeled mobile robots is formulated and solved using the backstepping technique and the idea from the LaSalle’s invariance principle. A global result is presented in which several constraints on the linear and the angular velocities of the mobile robot from recent literature are dropped. The proposed controller can ...

The NOCH framework was designed to serve as a foundation for development of models of neural motor control. The driving purpose behind the NOCH is bridging the gap between the control theory and neuroscience research in the field of motor control. This is done by identifying the underlying functions in control theory models of motor control and examining the structure/connections of the neural ...

Diierential-geometric methods can and have been successfully used in control theory, not only to pose and solve new problems, but also to get new insights and prove new results about classical problems of optimal control. In particular, they yield new results on local controllability, continuity properties of value functions, the structure of reachable sets, and the properties of optimal trajec...

Continuous motorization and urbanization around the globe leads to an expansion of population in major cities. Therefore, ever-growing pressure imposed on the existing mass transit systems calls for a better technology, Intelligent Transportation Systems (ITS), to solve many new and demanding management issues. Many studies in the extant ITS literature attempted to address these issues within w...

In this paper the use of tools from optimal control theory, namely the Kalman filter, is introduced for chaotic Lur’e systems to replace the widely used error feedback synchronization. This allows to take into account observation noise on the strange attractor to be filtered. We show that the filtering performance is superior to that of synchronization, in particular if the noise level is non-n...

Present work aims at developing an active suspension for a passenger car by designing a controller using linear quadratic optimal control theory, based on two different control approaches [conventional method (CM), acceleration dependent method (ADM)]. Performance of the active suspension system of a quarter car model with 3 degrees-of-freedom with two control approaches has been compared with ...

This paper proposes a framework for optimal control of mechanical systems possessing conserved quantities such as control moment gyros (CMGs). It will be shown that output regulation theory is appropriate to handle such constraints and that the center-stable manifold method for solving the associated Hamilton-Jacobi equation is effective for computing the optimal feedback control. With this fra...