Two of the fundamental concepts appearing in the earlier studies on linear control systems are controllability and observability. In particular, it was through the work of R.E. Kalman that the notion of controllability of a linear system was shown to be of interest in itself, and not only as it was appearing in the context of optimal control. Linear controllability turns out to be of importance...

Optimal control system design traditionally involves the adjustment of state and input variables to optimize a specified performance index. However, in practice there may exist variables, such as plant parameters, that offer extra freedom in the design of systems that can achieve even better performance. In this paper, we describe an integrated approach for dynamic system/control system design ...

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear stochastic control systems. The approach is suboptimal though robust and relies upon the approximation of the forward and inverse plant models by neural networks, which also estimate the intrinsic uncertainty. Sampling from the resulting Gaussian distributions of the inversion based neurocontroller allows us t...

This paper presents a survey on quantum control theory and applications from a control systems perspective. Some of the basic concepts and main developments (including open-loop control and closed-loop control) in quantum control theory are reviewed. In the area of open-loop quantum control, the paper surveys the notion of controllability for quantum systems and presents several control design ...

The optimal control of problem is about finding a control law for a given system such that a certain optimality criterion is achieved. Methods of solving the optimal control problems are divided into direct methods and mediated methods (through other equations). In this paper, the PSO- SVM indirect method is used to solve a class of optimal control problems. In this paper, we try to determine t...

This new platform too requires a strong and substantial research effort to take vision into reality. This research program can build on the activities from the 1960s onwards which laid the foundations of an ambitious system theory encompassing linear and nonlinear systems, stability theory, robust control, estimation, optimal control, decentralized control, adaptive control, identification, dis...

in this paper we first describe the stochastic optimal control algorithm called ((optcon)). the algorithm minimizes an intertemporal objective loss function subject to a nonlinear dynamic system in order to achieve optimal value of control (or instrument) variables. second as an application, we implemented the algorithm by the statistical programming system ((gauss)) to determine the optimal fi...