Abstract-A Computer aided implementation of an estimator based inverse dynamics controller (EBIDC) algorithm for the efficient control of the states, especially the non-measurable states of an autonomous hybrid system (AHS) is proposed in this paper. Case of a cylindrical three-tank hybrid system is demonstrated. The studies combining behaviors of both discrete event and continuous systems are of utmost importance nowadays and thus study of dynamics of hybrid systems and control strategies for performance improvement is very important in the present scenario. This algorithm makes use of a state estimator for estimating all the states of the system which uses a generic nonlinear model of the actual system. The efficacy of the developed EBIDC is demonstrated by conducting simulation studies using Matlab under different operating modes of the system. Both set point tracking and disturbance rejection capabilities of the proposed controller are also confirmed in this work. The robustness of EBIDC in controlling the non-measurable states is also analyzed under different uncertainties.Index Terms-Autonomous hybrid systems, derivative-free state estimator, estimator based inverse dynamics controller, unscented kalman filter (UKF) in state estimation.
I. INTRODUCTIONHybrid system is a very dynamic branch of engineering which deals with the systems of continuous, discrete time and discrete event behavior. In some of the earlier works reported, theories behind hybrid automata and the discrete control of continuous plant were considered [1], [2]. Later many approaches were reported in the literature in which the systems were considered to contain both continuous and discrete behavior and control of such systems were accomplished [3]- [16]. Subsequently studies like Lyapunov technique, applied for continuous nonlinear systems were extended to hybrid systems in [4]. Linear approximations of nonlinear systems were carried out in most of such studies as in [4] and [5]. In [6], with the help of constraint logic programming with interval arithmetic, a rigorous modeling, simulation and analysis approach for hybrid systems were proposed. A collection of modeling and classification of different benchmark hybrid systems are presented in [7]. However, direct use of nonlinear models for analysis and control of hybrid systems were reported in very few works and still it is a challenging area of research.The potential of dynamic models of hybrid systems developed in state estimation along with the modeling was investigated in [10]-[14] and [16]. Recently, using Bayesian approach, a nonlinear model of hybrid system was proposed by combining multiple local linear models in [11].Using such model a novel state identification method and predictive control of the system were proposed for a class of hybrid systems.[12], [13] had recommended an ensemble Kalman filter (EnKF) based nonlinear model predictive control (NMPC) and UKF based fault tolerant control schemes for controlling the output variables of the AHS. In addition to UKF and EnKF bas...
In recent years researches in hybrid system dynamics and control strategies have become very prominent because most of the systems show hybrid behavior (continuous and discrete) in their dynamics. In this work authors have considered a threetank autonomous hybrid system for the investigation. Implementation aspects of the model based control scheme and a derivative-free state estimator for three-tank hybrid system are simulated in MATLAB platform. In the simulation studies on benchmark three tank hybrid systems, the efficacy of the proposed controller and estimator under various real time operating conditions is demonstrated.
In this paper authors propose a distributed state estimation scheme for the hybrid system with interconnected subsystems to estimate the states. The system considered in this work has different subsystems which can interact with each other via their states over a communication network. The objective is to implement the distributed state estimation scheme for interconnected subsystems in which each subsystem sensors are connected to the communication network, the estimator has been used for each subsystem to estimate the current states by utilizing the states of the neighboring subsystems over the communication network. The proposed state estimation framework utilizes unscented Kalman filter algorithm. Unscented Kalman filter has been designed for each subsystem to estimate the current state estimates which corrupted by state and measurement noise. The benchmark system taken to implement distributed state estimation is continuous stirred tank reactor units which are strongly interconnected via their neighboring states. The reactors temperature is maintained at unstable operating point by a decentralized proportional integral controller for each subsystem by utilizing the measurements of the sensors from the network. The estimation framework has been verified in the absence of the network failure to stabilize the plant at unstable operating point. The estimate of the corresponding subsystems is used to compute the controller output in the absence of the network failure with minimal sharing over the network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.