Abstract
This study actualized a new hybrid adaptive controller design to increase the control performance of a variable loaded time-varying system. A structure in which LQR and adaptive control work together is proposed. At first, a Kalman filter was designed to estimate the states of the system and used with the LQR control method which is one of the optimal control servo system techniques in constant initial load. Then, for the variable loaded servo (VLS) system, the Lyapunov based adaptive control was added to the LQR control method which was inadequate due to the constant gain parameters. Thus, it was aimed to eliminate the variable load effects and increase the stability of the system. In order to show the effectiveness of the proposed method, a Quanser servo module was used in Matlab-Simulink environment. It is seen from the experimental results and performance measurements that the proposed method increases the system performance and stability by minimizing noise, variable load effect and steady-state error.
Highlights
Estimating the state variables in state feedback control systems at trust values is very important in terms of system performance and efficiently working of the system
Linear quadratic regulator (LQR) and adaptive controllers are designed for initial load (Jl_in, Bl_in) in the experimental system
The load was kept constant at the first experiment, and the system output responses were obtained separately for LQR and proposed LQR assisted adaptive control
Summary
Estimating the state variables in state feedback control systems at trust values is very important in terms of system performance and efficiently working of the system. LQR that aims to minimize the errors that occur in state output value can be called as linear optimal state feedback control in time-invariant systems. This is a technique that increases system performance and stability [6]. Lyapunov stability criteria and MIT rule are frequently used methods in designing traditional adaptive control systems to increase the system stability in time varying systems This method organizes the parameter values based on a reference model output value and aims to increase the system performance against destructive effects [11]. Lyapunov based adaptive control method is generally more effective on system performance and is preferred in various fields and control mechanisms, e.g. position control of permanent magnet synchronous motor [12], X-Y table experimental platforms control [13, 14], and DC motor speed control [15]
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