Changyun Wen

Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance

In this technical note, we consider adaptive control of single input uncertain nonlinear systems in the presence of input saturation and unknown external disturbance. By using backstepping approaches, two new robust adaptive control algorithms are developed by introducing a well defined smooth function and using a Nussbaum function. The Nussbaum function is introduced to compensate for the nonlinear term arising from the input saturation. Unlike some existing control schemes for systems with input saturation, the developed controllers do not require assumptions on the uncertain parameters within a known compact set and a priori knowledge on the bound of the external disturbance. Besides showing global stability, transient performance is also established and can be adjusted by tuning certain design parameters.

Adaptive output control of nonlinear systems with uncertain dead-zone nonlinearity

In this note, we present a new scheme to design adaptive controllers for uncertain systems preceded by unknown dead-zone nonlinearity. The control design is achieved by introducing a smooth inverse function of the dead-zone and using it in the controller design with backstepping technique. For the design and implementation of the controller, no knowledge is assumed on the unknown system parameters. It is shown that the proposed controller not only can guarantee stability, but also transient performance.

Brief paper: Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance

In order to accommodate actuator failures which are uncertain in time, pattern and value, we propose two adaptive backstepping control schemes for parametric strict feedback systems. Firstly a basic design scheme on the basis of existing approaches is considered. It is analyzed that, when actuator failures occur, transient performance of the adaptive system cannot be adjusted through changing controller design parameters. Then we propose a new controller design scheme based on a prescribed performance bound (PPB) which characterizes the convergence rate and maximum overshoot of the tracking error. It is shown that the tracking error satisfies the prescribed performance bound all the time. Simulation studies also verify the established theoretical results that the PPB based scheme can improve transient performance compared with the basic scheme, while both ensure stability and asymptotic tracking with zero steady state error in the presence of uncertain actuator failures.

Analysis and design of impulsive control systems

Some sufficient conditions for asymptotic stability of impulsive control systems with impulses at fixed times have recently been presented. In this paper, we derive some less conservative conditions for asymptotic stability of such impulsive control systems and the results are used to design impulsive control for a class of nonlinear systems. The class of nonlinear systems considered is also extended.

Analysis of a high-order iterative learning control algorithm for uncertain nonlinear systems with state delays

Key Words—Iterative learning control; nonlinear systems; convergence analysis; high-order scheme; delay; tracking. Abstract—For a better learning transient along the iteration number direction, a PID-type iterative learning control algo- rithm is proposed for a class of delayed uncertain nonlinear systems which perform a given task repeatedly. The convergence conditions for the proposed high-order learning control have been established. The tracking error bound is proven to be a class-K function of the bounds of reinitialization errors, uncer- tainties and disturbances to the systems. It is also indicated that the time delays in the system states do not play a significant role in the ILC convergence property. The e⁄ectiveness of the high- order ILC algorithm is demonstrated by simulation examples. ( 1998 Elsevier Science Ltd. All rights reserved.

An iterative learning controller with initial state learning

In iterative learning control (ILC), a common assumption is that the initial states in each repetitive operation should be inside a given ball centred at the desired initial states which may be unknown. This assumption is critical to the stability analysis, and the size of the ball will directly affect the final output trajectory tracking errors. In this paper, this assumption is removed by using an initial state learning scheme together with the traditional D-type ILC updating law. Both linear and nonlinear time-varying uncertain systems are investigated. Uniform bounds for the final tracking errors are obtained and these bounds are only dependent on the system uncertainties and disturbances, yet independent of the initial errors. Furthermore, the desired initial states can be identified through learning iterations.

Robust Adaptive Output Control of Uncertain Nonlinear Plants With Unknown Backlash Nonlinearity

In this note, we consider a class of uncertain dynamic nonlinear systems preceded by unknown backlash nonlinearity. The control design is achieved by introducing a smooth inverse function of the backlash and using it in the controller design with backstepping technique. For the design and implementation of the controller, no knowledge is assumed on the unknown system parameters. It is shown that the proposed controller not only can guarantee stability, but also transient performance

Decentralized adaptive regulation

A new adaptive control scheme developed by Krstic et al. (1992) is employed to design decentralized adaptive regulators. The interconnected system to be regulated consists of N coupled subsystems having arbitrarily relative degrees. Global stability is established for the closed-loop system and perfect regulation is ensured. >

Fast Mode Decision Algorithm for Inter-Frame Coding in Fully Scalable Video Coding

Scalable video coding is an ongoing standard, and the current working draft (WD) is an extension of H.264/AVC. In the WD, an exhaustive search technique is employed to select the best coding mode for each macroblock. This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. This paper proposes a fast mode decision algorithm for inter-frame coding for spatial, coarse grain signal-to-noise ratio, and temporal scalability. It makes use of the mode-distribution correlation between the base layer and enhancement layers. Specifically, after the exhaustive search technique is performed at the base layer, the candidate modes for enhancement layers can be reduced to a small number based on the correlation. Experimental results show that the fast mode decision scheme reduces the computational complexity significantly with negligible coding loss and bit-rate increases

Distributed Secondary Voltage and Frequency Restoration Control of Droop-Controlled Inverter-Based Microgrids

In this paper, restorations for both voltage and frequency in the droop-controlled inverter-based islanded microgrid (MG) are addressed. A distributed finite-time control approach is used in the voltage restoration which enables the voltages at all the distributed generations (DGs) to converge to the reference value in finite time, and thus, the voltage and frequency control design can be separated. Then, a consensus-based distributed frequency control is proposed for frequency restoration, subject to certain control input constraints. Our control strategies are implemented on the local DGs, and thus, no central controller is required in contrast to existing control schemes proposed so far. By allowing these controllers to communicate with their neighboring controllers, the proposed control strategy can restore both voltage and frequency to their respective reference values while having accurate real power sharing, under a sufficient local stability condition established. An islanded MG test system consisting of four DGs is built in MATLAB to illustrate our design approach, and the results validate our proposed control strategy.