Output Feedback Regulation of a Class of Lower Triangular Nonlinear Systems with Arbitrary Unknown Measurement Sensitivity

International Journal of Control, Automation and Systems - In this paper, a regulation problem for a class of lower triangular nonlinear systems under unknown measurement sensitivity by output...     

On Robust Approximate Feedback Linearization: Control with Two Gain-scaling Factors

In this paper, we consider a problem of global stabilization for a class of approximately feedback linearized nonlinear systems. In order to handle more nonlinearity over the existing results, we provide a new feedback controller with two gain-scaling factors and we show that more nonlinearity can be treated by our control scheme. Moreover, we analytically show that the considered nonlinear systems can be stabilized by the proposed controller. Through comparison practical examples, we illustrate the improved features of our proposed control method.

     

Improved Controller Design with Two Gain-scaling Factors for Global Asymptotic Stabilization of Nonlinear Systems via Matrix Inequality Approach

In this paper, we consider a problem of global asymptotic stabilization for nonlinear systems with the perturbed nonlinearity. We provide a stabilizing controller with two gain-scaling factors and a new controller design method with matrix inequality approach. In particular, we provide a new procedure for selecting gain-scaling factors which are associated with stabilizing the closed-loop system. As a result, our proposed control method widens the class of considered nonlinear systems and yields better control performance over the existing methods. Via several comparison examples, we illustrate the improved features of the proposed control method over the existing ones.

     

Fastest recovery after feedback disruption: nonlinear delay-differential systems

The problem of reducing operating errors after a feedback disruption is considered for a class of nonlinear delay-differential systems. It is shown that there are optimal controllers that reduce such errors in minimal time, once feedback has been restored. It is further shown that optimal performance can be approximated by bang-bang controllers – controllers that are easy to design and implement.     

Stabilisation of non-linear systems with unknown growth rate by adaptive output feedback

In recent years, several results have been proposed on the global stabilisation of non-linear systems with unknown linear growth rate. However, these works are limited in the sense that they consider only one particular form of non-linear systems–mostly either triangular or feedforward form. We propose an adaptive output feedback control scheme which can deal with both triangular or feedforward non-linear systems with unknown linear growth rate in a unified framework. Thus, our result broadens the class of non-linear systems under consideration over the existing results.     

On pattern classification of EMG signals for walking motions

We present a method to calssify electromyogram (EMG) signals which are utilized as control signals for a patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for different walking motions are classified via adequate filtering, real EMG signal extraction, AR-modeling, and a modified self-organizing feature map (MSOFM). In particular, a data-reducing extraction algorithm is employed for real EMG signals. Moreover, MSOFM classifies and determines the results automatically using a fixed map. Finally, the experimental results are presented for validation.     

Global regulation of a class of nonlinear systems with high-order triangular type nonlinearity

The problem of global regulation is investigated for a class of nonlinear systems which contain some high-order terms. We propose a high-order scaling state-feedback controller with appropriate dynamic gains. Compared to existing results, the condition on the nonlinearity is flexible due to the freedom of choosing the bounding positive function of the nonlinearity. Thus, the nonlinear systems with some high-order nonlinearities which do not belong to existing conditions can be globally regulated.     

Periodic sampling: maximising the sampling period

The process of periodic sampling is investigated for a class of nonlinear systems. The objective is to achieve the longest sampling period that is compatible with a specified error bound. It is shown that there are robust optimal controllers that achieve this objective. It is also shown that the performance of such optimal controllers can be approximated by bang-bang controllers – controllers that are relatively easy to design and implement.     

Fast Regulation Control of a Class of Input-delayed Linear Systems with Pre-feedback

A control problem of a class of input-delayed linear systems is considered in this paper. Due to the delay τ in the input, any designed feedback controller can only be engaged after t ≥ τ. Then, this can become the cause of slow regulation since any feedback information cannot be available during the delay. So, the initial function defined for -τ ≤ t ≤ 0 is engaged as an ‘initial non-feedback input’ for 0 ≤ t ≤ τ, which governs the system behavior during this initial time period. There have been numerous research results on the control of input-delayed linear systems by far. Yet, there have been no results on the examination and design of this initial function. Utilizing a time optimal control in the existing results, we show that if some pre-feedback as the initial function is engaged, the system response of the input-delayed linear system can be much improved, and a bang-bang input function is a good candidate as a pre-feedback which can provide better starting state values for the state feedback controller in order to perform the fast regulation. Two examples are given for the illustration of our results.     

Global regulation of almost feedforward nonlinear systems by an adaptive event-triggered controller with multi-triggering conditions

We consider a global regulation problem for almost feedforward nonlinear systems with uncertain time-varying parameters using an adaptive event-triggered controller. The systems we consider are called “almost” feedforward systems because, in addition to the feedforward nonlinearity with the unknown linear growth rate, there is a non-zero input-matching term. Notably, this input-matching term is a non-feedforward term and it cannot be directly canceled due to the presence of input uncertainty and the use of event-triggered control. To solve our considered problem, we propose an adaptive event-triggered controller with multi-triggering conditions and dynamic gain. We show that the closed-loop system is globally regulated and the times between executions are positively lower bounded. Moreover, we show that the positive lower bounds of interexecution times can be enlarged by a control parameter. For a clear illustration, a practical example is given.