Open-loop System Identification Research Articles

Model predictive control of non-domestic heating using genetic programming dynamic models

We present a novel approach to obtaining dynamic nonlinear models using genetic programming (GP) for the model predictive control (MPC) of the indoor temperatures of buildings. Currently, the large-scale adoption of MPC in buildings is economically unviable due to the time and cost involved in the design and tuning of predictive models by expert control engineers. We show that GP is able to automate this process, and have performed open-loop system identification over the data produced by an industry grade building simulator. The simulated building was subject to an amplitude modulated pseudo-random binary sequence (APRBS), which allows the collected data to be sufficiently informative to capture the underlying system dynamics under relevant operating conditions.In this initial report, we detail how we employed GP to construct the predictive model for MPC for heating a single-zone building in simulation, and report results of using this model for controlling the internal environmental conditions of the simulated single-zone building. We conclude that GP shows great promise for producing models that allow the MPC of building to achieve the desired temperature band in a single zone space.

Fixed-order data-driven H∞ controller synthesis for flexible mechanical systems: Two-stage approach

In this paper, a two-stage method is introduced to design fixed-order data-driven [Formula: see text] controller for flexible mechanical systems. In the first stage of the proposed method, unknown parameters of anti-resonance filter that is added to the forward path of the control loop of the system to minimize resonant peaks, are calculated using frequency domain data obtained from open-loop system identification tests. In the second stage, a fixed-order data-driven [Formula: see text] controller is calculated by solving an optimization problem under convex [Formula: see text] constraints obtained based on the Nyquist diagram. With the proposed method, lower order controllers that meets the performance constraints of classical model-based [Formula: see text] problems can be synthesized without need of a parametric plant model. The method developed in this study is tested experimentally on a military stabilized platform and its performance is compared with a model-based [Formula: see text] controller design method.

Open-Loop System Identification of MIMO Integrator Model

This paper considers the open-loop system identification of a multi-input multi-output (MIMO) integrator model which is a multiplication of a constant matrix, called the action matrix, and the inte...

System identification of a hot cathode electron source: Time domain approach

Electron sources with a hot cathode operating in consumption or generation modes are widely used in many vacuum devices as gas ion sources, thermionic energy converters. The main aim of this work is to get information how dynamic properties of the electron source changes within full range of work, therefore the identification of a hot cathode electron source using the step signal and the time domain approach to know dynamic parameters (DC incremental transconductance, time constant, delay time) of the electron source in full range of its operation is made. In the first part, an open-loop system identification using step response method was conducted. For the electron source with a thoriated tungsten cathode (d=0.1 mm, l=45 mm) operating in the range 1 μA to 1 mA, the time constant T varies from 0.71 s to 0.35 s, the delay time T0 from 0.04 s to 0.01 s and the DC incremental transconductance g0 from 0 to 0.0056 S, respectively. In the next step, an approximation of obtained characteristics is made and ultimate gains of thermionic emission current automatic control system for each fixed operating point are estimated. The results of similar investigations for electron sources with an yttrium oxide coated iridium cathode and a tungsten cathode have also been shown. Presented system identification approach can be successfully applied to other types of the hot cathode electron sources.

Gain-Scheduled Autopilot Design and Validation for an Experimental Guided Projectile Prototype

This paper investigates the design and validation of a gain-scheduled skid-to-turn autopilot for an experimental canard-guided, fin-stabilized 80-mm-guided projectile prototype in a hardware-in-the-loop (HIL) wind tunnel-based setup. The projectile dynamics are a priori unknown and are determined from open-loop system identification experiments conducted on the test setup. To this end, a nonlinear airframe model is discussed and considered for linearization around equilibrium operating points. The linear model parameters are estimated from several data collection experiments, resulting in a family of linear models. This knowledge is leveraged in a second step to compute a family of robustly stable multiobjective disturbance-rejection and reference-tracking controllers, which are implemented on the HIL test setup using a zero-pole gain interpolation scheme. The time-domain performance of the autopilot is finally assessed by the means of numerical simulations and experimental results gathered from the test setup, demonstrating the excellent suitability of the proposed approach.

LQ decomposition based subspace identification under deterministic type disturbance

ABSTRACTTo overcome the influence from deterministic type load disturbance with unknown dynamics, a bias-eliminated subspace identification method is proposed for consistent estimation. By decomposing the output response into three parts, deterministic, disturbed and stochastic components, in terms of the linear superposition principle, an LQ decomposition approach is developed to eliminate the disturbance and noise effect for unbiased estimation of the deterministic system state. Subsequently, a shift-invariant approach is given to retrieve the state matrices. Consistent estimation on the state matrices is analyzed with a proof. Illustrative example of open-loop system identification is shown to demonstrate the effectiveness and merit of the proposed method.

An extended AUDI algorithm for simultaneous identification of forward and backward paths in closed-loop systems

In closed-loop system identification, most of the existing methods only focus on the forward path, yet few on simultaneous identification of the forward and backward paths. Meanwhile, an augmented UD identification (AUDI) algorithm has been proved effective in open-loop system identification, but it only extracts the forward path information, while not including the backward path information provided in an augmented information matrix, which is helpful for the closed-loop system identification. In this paper, an extended AUDI (EAUDI) is proposed to simultaneously identify the model orders and parameters of both forward and backward paths of a closed-loop system. The conditions of identifiability and uniform convergence for closed-loop systems using the EAUDI algorithm are also given. The effectiveness of this algorithm is demonstrated by a numerical example.

Novel Plant Test for MPC

The present work is a method of plant testing for the purpose of open-loop system identification and model-based control of chemical processes, in particular, model predictive control (MPC). It is a multivariable test technique using plant-friendly and optimal amplitude binary multi-frequency signals, in conjunction with multivariable parametric modeling techniques, to achieve significant time savings in plant testing by comparison with traditional step testing and even other multivariable testing methods in the literature.

閉ループ系のインパルス応答列による開ループ系の同定とその宇宙構造物への応用

閉ループ系のインパルス応答列による開ループ系の同定とその宇宙構造物への応用

Active identification of dynamic systems in face of ‘ coloured ’ disturbances

An algorithm is developed for identification of open-loop systems in the presence of ‘ coloured ’ noises. The algorithms are proved to converge almost exactly and in the mean square. Estimates of the rate of convergence are obtained and other asymptotic properties of resultant estimates studied.