- Los Angeles, California, United States
Research Interests:
In this paper, we provide a simple novel approach to decentralised control design. Each subsystem of an interconnected interacting system is controlled in a decentralised manner using locally available information related only to the... more
In this paper, we provide a simple novel approach to decentralised control design. Each subsystem of an interconnected interacting system is controlled in a decentralised manner using locally available information related only to the state ofthat particular subsystem. The method is developed in two steps. In the first step, we define 'w'hat we call a 'nominal system', which consists of 'nominal subsystems'. The nominal subsystems are assumed to be acted upon by forces that can be computed using only locally available information. We obtain an asymptotically stable control for each nominal subsystem which minimises a suitable, desired norm of the control effort at each instant of time. In the second step, we determine the control force that needs to be applied to the actual (interconnected) subsystem in addition to the control force calculated for the nominal subsystem, so each actual subsystem tracks the state ofthe controlled nominal subsystem as closely as desired. This additional compensating controller is obtained using the concept of a generalised sliding surface control. The design of this additional controller needs as its input an estimate of the bound on the mismatch belween the nominal and the actual subsystems. Exatnples ofnon-autonotnous, nonlinear, distributed systelns are provided that delnonstrate the efficacy and ease of implementation of the control method.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
In this paper, we provide a simple novel approach to decentralised control design. Each subsystem of an interconnected interacting system is controlled in a decentralised manner using locally available information related only to the... more
In this paper, we provide a simple novel approach to decentralised control design. Each subsystem of an interconnected interacting system is controlled in a decentralised manner using locally available information related only to the state ofthat particular subsystem. The method is developed in two steps. In the first step, we define 'w'hat we call a 'nominal system', which consists of 'nominal subsystems'. The nominal subsystems are assumed to be acted upon by forces that can be computed using only locally available information. We obtain an asymptotically stable control for each nominal subsystem which minimises a suitable, desired norm of the control effort at each instant of time. In the second step, we determine the control force that needs to be applied to the actual (interconnected) subsystem in addition to the control force calculated for the nominal subsystem, so each actual subsystem tracks the state ofthe controlled nominal subsystem as closely as desired. This additional compensating controller is obtained using the concept of a generalised sliding surface control. The design of this additional controller needs as its input an estimate of the bound on the mismatch belween the nominal and the actual subsystems. Exatnples ofnon-autonotnous, nonlinear, distributed systelns are provided that delnonstrate the efficacy and ease of implementation of the control method.
Research Interests:
Research Interests:
ABSTRACT This paper presents a simple approach to synthesize optimal controls from user prescribed positive definite functions. The synthesized controls minimize a user specified objective function which is a quadratic function of the... more
ABSTRACT This paper presents a simple approach to synthesize optimal controls from user prescribed positive definite functions. The synthesized controls minimize a user specified objective function which is a quadratic function of the control variables. The approach followed in this paper is inspired by recent developments in analytical dynamics and the observation that the Lyapunov criterion for stability of dynamical systems can be recast as a constraint to be imposed on the system. The approach used to obtain the fundamental equation of motion for constrained mechanical systems is extended to find control forces that minimize any user-specified quadratic function of the control forces while simultaneously enforcing the stability requirement as an additional constraint. This method can also be generalized to nonautonomous dynamical system described by first order nonlinear differential equations. We further explore the possibility of extending the approach to systems in which we do not have full state control.