Design of multi‐input multi‐output minimum‐phase state control system with decoupling and feedforward compensation

This paper discusses the design of decoupling control for a multi‐input multi‐output (MIMO) linear system. A new configuration of the prepositional tandem matrix is presented as a decoupling compensator, and minimum‐phase state control is applied to the resulting decoupled system. In general, non‐minimum‐phase characteristics often accompany decoupled systems. Feedforward compensation makes the non‐minimum‐phase effect of each decoupled scalar system change to the delay time. A numerical example is given for the MIMO linear system, which conventionally results in non‐minimum‐phase systems. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(2): 53–61, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21117     

Experimentally verified point‐to‐point iterative learning control for highly coupled systems

Iterative learning control (ILC) is a well‐established approach for precision tracking control of systems, which perform a repeated tracking task defined over a fixed time interval. Despite a rich theoretical framework accompanied by a wide array of application studies, comparatively little attention has been paid to the case of multiple input, multiple output (MIMO) systems. Here, the presence of interacting dynamics often correlates with reduced performance. This article focuses on a general class of linear ILC algorithms and establishes links between interaction dynamics and reduced robustness to modeling uncertainty, and slower convergence. It then shows how these and other limitations can be addressed by relaxing the tracking requirement to include only a subset of time points along the time duration. This is the first analysis to show how so‐called ‘point‐to‐point’ ILC can address performance limitations associated with highly coupled systems. Theoretical observations are tested using a novel MIMO experimental test facility, which permits both exogenous disturbance injection and a variable level of coupling between input and output pairs. Results compare experimental observations with theoretical predictions over a wide range of interaction levels and with varying levels of injected noise. Copyright © 2014 John Wiley & Sons, Ltd.     

Passivity‐based control for stabilization,regulation and tracking purposes of a class of nonlinear systems

In this paper, a new passivity‐based control (PBC) scheme based on state feedback is proposed in order to solve tracking, regulation and stabilization problems for a class of multi‐input multi‐output (MIMO) nonlinear systems expressed in the normal form, with time‐invariant parameters and locally bounded reference weakly minimum phase. For the proposed control scheme two new different state feedbacks, one non‐adaptive for the case when the system parameters are assumed to be known and the other adaptive for the case of unknown parameters, are developed. For the adaptive case it is assumed that the unknown parameters appear linearly in the equations. Analysis of the transient behaviour of the proposed control schemes is presented through the simulation of two examples. Copyright © 2006 John Wiley & Sons, Ltd.     

Adaptive neural dynamic surface control of MIMO stochastic nonlinear systems with unknown control directions

In this paper, an adaptive neural output‐feedback control approach is considered for a class of uncertain multi‐input and multi‐output (MIMO) stochastic nonlinear systems with unknown control directions. Neural networks (NNs) are applied to approximate unknown nonlinearities, and K‐filter observer is designed to estimate unavailable system's states. Due to utilization of Nussbaum gain function technique in the proposed approach, the singularity problem and requirement to prior knowledge about signs of high‐frequency gains are removed, simultaneously. Razumikhin functional method is employed to deal with unknown state time‐varying delays, so that the offered control approach is free of common assumptions on derivative of time‐varying delays. Also, an adaptive neural dynamic surface control is developed; hence, explosion of complexity in conventional backstepping method is eliminated, effectively. The boundedness of all the resulting closed‐loop signals is guaranteed in probability; meanwhile, convergence of the tracking errors to adjustable compact set in the sense of mean quartic value is also proved. Finally, simulation results are shown to verify and clarify efficiency of the offered approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive neural dynamic surface control of MIMO nonlinear time delay systems with time‐varying actuator failures

In this paper, an adaptive dynamic surface control approach is developed for a class of multi‐input multi‐output nonlinear systems with unknown nonlinearities, bounded time‐varying state delays, and in the presence of time‐varying actuator failures. The type of the considered actuator failure is that some unknown inputs may be stuck at some time‐varying values where the values, times, and patterns of the failures are unknown. The considered actuator failure can cover most failures that may occur in actuators of the systems. With the help of neural networks to approximate the unknown nonlinear functions and combining the dynamic surface control approach with the backstepping design method, a novel control approach is constructed. The proposed design method does not require a priori knowledge of the bounds of the unknown time delays and actuator failures. The boundedness of all the closed‐loop signals is guaranteed, and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark as well as a chemical reactor system. The simulation results show the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.     

Order and parameter estimation of time‐varying system by subspace method

This paper proposes an identification algorithm for time‐varying systems. We apply subspace method for estimation, since it is known to be useful when the input–output (I/O) data are observed by multi‐input multi‐output (MIMO) systems. Among many proposed techniques of subspace methods, we use MOESP (MIMO Output‐Error State Space model identification) in this paper, which assures arithmetic stability by RQ factorization and singular value decomposition (SVD). Generally, subspace methods can be applied after I/O data collection, so that we introduce updated steps of matrices for PI‐MOESP, which uses past inputs for instrumental variables. We propose a recursive update algorithm of PI‐MOESP, including estimation step of the system order, and consider some parameters inherent to the algorithm, namely, initial number of data, estimation step of the order, and forgetting factor. A numerical example shows the usefulness of the proposed method. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 157(2): 57–64, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20169     

Neutralizing interferences in two‐hop amplify‐and‐forward MIMO relay systems

In this paper, we present the interference neutralization technique for two‐hop multiple‐input multiple‐output (MIMO) relay systems. It enables multiple MIMO transmitters (sources) to simultaneously transmit independent data streams to their MIMO receivers (destinations) without mutual interferences, thereby improving spectral efficiency of the systems. To neutralize the mutual interferences using multiple amplify‐and‐forward (AF) MIMO relays, we establish the sufficient condition for the antenna configuration in the MIMO relay networks, and provide a filter design technique for the AF MIMO relays. The proposed method increases sum rates of the systems linearly with the number of transmitters participating in simultaneous transmission. To improve the sum rates further, this method is combined with transmit power allocation using the water‐filling algorithm. In addition, it is shown that by employing the minimum number of relays required to meet the sufficient condition, the system cost for the proposed method can be reduced without compromising the sum rate performance severely. Finally, simulation results successfully demonstrate that by exploiting radio resources such as frequency and time efficiently, the proposed method achieves a higher sum rate than the existing techniques based on interference avoidance. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A high‐speed MIMO FFT processor with full hardware utilization

The conventional way to design multi‐input‐multi‐output (MIMO) fast Fourier transform (FFT) processors for MIMO‐orthogonal frequency division multiplexing systems is to adopt a parallel architecture which uses as many single‐input‐single‐output FFT processors as the number of transmit/receive antennas. These MIMO FFT processors can provide high throughput, but they perform with low hardware utilization when there are not all input sequences available. In this paper, we propose a high‐speed MIMO FFT processor which can work efficiently with high throughput and full hardware utilization for variable 1 to 4 input sequences. Our MIMO FFT processor is designed by reordering and distributing data sequences to all data paths and is constructed by some novel modules. Being synthesized by using UMC 0.18‐μm process demonstrates that our 64‐point 4 × 4 FFT can achieve high throughput with full hardware utilization and perform correctly up to 62.25 MHz with low power consumption for variable 1 to 4 input sequences.     

Sliding mode disturbance observer‐based adaptive control for uncertain MIMO nonlinear systems with dead‐zone

In this paper, an adaptive integral sliding mode control (ISMC) scheme is developed for a class of uncertain multi‐input and multi‐output nonlinear systems with unknown external disturbance, system uncertainty, and dead‐zone. The research is motivated by the fact that the ISMC scheme against unknown external disturbance and system uncertainty is very important for multi‐input and multi‐output nonlinear systems. The system uncertainty, the unknown external disturbance, and the effect of dead‐zone are integrated as a compounded disturbance, which is well estimated using a sliding mode disturbance observer (SMDO). Then, the adaptive ISMC based on the designed SMDO is presented to guarantee the satisfactory tracking performance in the presence of system uncertainty, external disturbance, and dead‐zone. Finally, the designed adaptive ISMC strategy based on SMDO is applied to the attitude control of the near space vehicle, and simulation results are presented to illustrate the effectiveness of the proposed adaptive ISMC scheme using the SMDO. Copyright © 2016 John Wiley & Sons, Ltd.     

Stabilization analysis and implementation for MIMO NCS with time‐varying delays

This paper is concerned with the design of output feedback controllers for a class of maximum input maximum output networked control systems (NCSs). In view of NCSs with many independent sensors and actuators, a discrete‐time model with multiple time‐varying delays is proposed. By constructing a novel Lyapunov–Krasovskii functional, a new less conservative stability criterion is developed in terms of linear matrix inequality. On the basis of the obtained stability condition, a static output feedback controller can be designed by applying an iterative algorithm. Both simulation and practical experiment results are given to show the effectiveness of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.