Data compression for estimation of the physical parameters of stable and unstable linear systems

A two-stage method for the identification of physical system parameters from experimental data is presented. The first stage compresses the data as an empirical model which encapsulates the data content at frequencies of interest. The second stage then uses data extracted from the empirical model of the first stage within a nonlinear estimation scheme to estimate the unknown physical parameters. Furthermore, the paper proposes use of exponential data weighting in the identification of partially unknown, unstable systems so that they can be treated in the same framework as stable systems. Experimental data are used to demonstrate the efficacy of the proposed approach

Feedback control of unsupported standing in paraplegia. Part I: optimal control approach

This is the first of a pair of papers which describe an investigation into the feasibility of providing artificial balance to paraplegics using electrical stimulation of the paralyzed muscles. By bracing the body above the shanks, only stimulation of the plantarflexors is necessary. This arrangement prevents any influence from the intact neuromuscular system above the spinal cord lesion. Here, the authors extend the design of the controllers to a nested-loop LQG (linear quadratic Gaussian) stimulation controller which has ankle moment feedback (inner loops) and inverted pendulum angle feedback (outer loop). Each control loop is tuned by two parameters, the control weighting and an observer rise-time, which together determine the behavior. The nested structure was chosen because it is robust, despite changes in the muscle properties (fatigue) and interference from spasticity

Robust adaptive regulation without persistent excitation

A globally convergent adaptive regulator for minimum or nonminimum phase systems subject to bounded distrubances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the new representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least Squares identification algorithm with a dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given

Signal Reconstruction via H-infinity Sampled-Data Control Theory: Beyond the Shannon Paradigm

This paper presents a new method for signal reconstruction by leveraging sampled-data control theory. We formulate the signal reconstruction problem in terms of an analog performance optimization problem using a stable discrete-time filter. The proposed H-infinity performance criterion naturally takes intersample behavior into account, reflecting the energy distributions of the signal. We present methods for computing optimal solutions which are guaranteed to be stable and causal. Detailed comparisons to alternative methods are provided. We discuss some applications in sound and image reconstruction

Yet Another Tutorial of Disturbance Observer: Robust Stabilization and Recovery of Nominal Performance

This paper presents a tutorial-style review on the recent results about the disturbance observer (DOB) in view of robust stabilization and recovery of the nominal performance. The analysis is based on the case when the bandwidth of Q-filter is large, and it is explained in a pedagogical manner that, even in the presence of plant uncertainties and disturbances, the behavior of real uncertain plant can be made almost similar to that of disturbance-free nominal system both in the transient and in the steady-state. The conventional DOB is interpreted in a new perspective, and its restrictions and extensions are discussed

Синтез системы управления неминимально-фазовыми объектами на основе искусственной нейронной сети

Рассматривается задача управления неминимально-фазовой системой. Предложенный регулятор состоит из многослойной нейронной сети и ПИД-регулятора. Нейроконтроллер адаптивно изменяет управляющие воздействия, вырабатываемые ПИД-регулятором, так, чтобы выходы объекта с неминимально-фазовой характеристикой следовали за выходами минимально-фазовой эталонной модели в каждый момент времени. Результаты моделирования доказывают эффективность предложенного метода для управления неминимально-фазовым объектом с запаздыванием.The problem of control of a nonminimum phase system is considered. The proposed controller has a hybrid architecture of a multilayer neural network and the PID controller. The neurocontroller adaptively transforms a control action of the PID controller to follow the system outputs with the nonminimum phase characteristic to those of a reference model with a minimum phase characteristic in each sampling instant. Computer simulation results show that the proposed method effectively controls the nonminimum phase systems with time delay properties

Optimal Energy Regulation Performance of Delay-time Systems

This paper studies the regulation performance limi- tation of delay-time systems. The performance is measured by the energy of the control input with respect to an impulse dis- turbance function. We first provide the analytical closed-form expression of the optimal performance for minimum phase case by reviewing the existing result. We then extend the problem to non-minimum phase case by exploiting the results of linear time- invariant discrete-time and delta domain cases

Asymptotic Hyperstability and Input–Output Energy Positivity of a Single-Input Single-Output System Which Incorporates a Memoryless Non-Linear Device in the Feed-Forward Loop

This paper visualizes the role of hyperstable controllers in the closed-loop asymptotic stability of a single-input single-output system subject to any nonlinear and eventually time-varying controller within the hyperstable class. The feed-forward controlled loop (or controlled plant) contains a strongly strictly positive real transfer function in parallel with a non-linear and memory-free device. The properties of positivity and boundedness of the input–output energy are examined based on the “ad hoc” use of the Rayleigh energy theorem on the truncated relevant signals for finite time intervals. The cases of minimal and non-minimal state-space realizations of the linear part are characterized from a global asymptotic stability (asymptotic hyperstability) point of view. Some related extended results are obtained for the case when the linear part is both positive real and externally positive and for the case of incorporation of other linear components which are stable but not necessarily positive real.This research was funded by the Spanish Government and the European Commission, grant number RTI2018-094336-B-I00 (MCIU/AEI/FEDER, UE) and by the Basque Government, grant number IT1207-19. The APC was funded by grant RTI2018-094336-B-I00 (MCIU/AEI/FEDER, UE)

Indirect parameter estimation of continuous-time systems using discrete time data

This paper addresses the problem of parameter estimation of continuous-time systems using samples of its input-output data. We propose a method based on the bilinear transformation to obtain an equivalent discrete-time model. Introducing a new polynomial pre-filter it .is possible to compute the physical parameters via inverse mapping between the discrete-time and the continuous-time models. A simulation example is given to illustrate the noise effects in the parameter estimation results. Using experimental results, we demonstrate the ability of the estimator. to handle real measurement problems

Virtual Holonomic Constraints for Euler-Lagrange systems under sampling

In this paper, we consider the problem of imposing Virtual Holonomic Constraints to mechanical systems in Euler-Lagrangian form under sampling. An exact solution based on multi-rate sampling of order two over each input channel is described. The results are applied to orbital stabilization of the pendubot with illustrative simulations