Adaptive speed control for induction motors based on a semi-current-fed model

This paper presents a semi-current-fed concept and a virtual desired variable synthesis for induction motor control. First, the traditional ideal current-loop assumption is relaxed. The relaxed assumption, considering more practical situations, allows a bounded stator voltage and a finite absolute-integral of current tracking error. From this novel concept, a semi-current-fed model for induction motors is used for the design. Both unknown rotor resistance and torque load are considered along with immeasurable rotor flux. To cope with the problems, we use a virtual desired variable approach to synthesize the control law. In the absence of a flux sensor and not using a flux observer, the asymptotic speed tracking is ensured without needing the persistent excitation condition. However, if the controlled system is persistently excited, an optimal torque control is additionally achieved. In addition to the theoretical proof, experimental results show the expected tracking performance.     

Robust Adaptive Control of Linear Induction Motors With Unknown End-Effect and Secondary Resistance

This paper proposes a novel robust adaptive speed/ position tracking control for a linear induction motor (LIM) with both end-effect and secondary resistance unknown. The practical current-fed controlled LIM, with residual current error, is considered, i.e., the traditional ideal current-loop assumption is relaxed. More practical conditions, such as bounded primary voltage and a finite absolute-integral of current tracking error is considered. To overcome the high nonlinearity and nonzero current error, a backstepping method, combining virtual desired variable synthesis, is developed for the speed and position tracking. Then, the controller achieves asymptotic speed and position tracking even with unknown parameters and immeasurable secondary flux. Furthermore, the effect of the residual current error is attenuated in an L₂ -gain sense. The experiments for several scenarios are carried out to verify the theoretical result.     

Semi-decentralized adaptive fuzzy control for cooperativemultirobot systems with H∞ motion/internal forcetracking performance

We present a semi-decentralized adaptive fuzzy control scheme for cooperative multirobot systems to achieve H(infinity) performance in motion and internal force tracking. First, we reformulate the overall system dynamics into a fully actuated system with constraints. To cope with both parametric and nonparametric uncertainties, the controller for each robot consists of two parts: 1) model-based adaptive controller; and 2) adaptive fuzzy logic controller (FLC). The model-based adaptive controller handles the nominal dynamics which results in both zero motion and internal force errors for a pure parametric uncertain system. The FLC part handles the unstructured dynamics and external disturbances. An H(infinity) tracking problem defined by a novel performance criterion is given and solved in the sequel. Hence, a robust controller satisfying the disturbance attenuation is derived being simple and singularity-free. Asymptotic convergence is obtained when the fuzzy approximation error is bounded with finite energy. Maintaining the same results, the proposed controller is further simplified for easier implementation. Finally, the numerical simulation results for two cooperative planar robots transporting an object illustrate the expected performance.     

Induction motor control with friction compensation: an approach of virtual-desired-variable synthesis

In this paper, the speed control problem of induction motors suffering from substantial friction force is considered. Here, a semi-current-fed model for induction motors and LuGre's dynamic model for friction force are used. To reflect practical situations, rotor resistance, torque load, and friction parameters are assumed to be unknown. In the design methodology, a double-observer structure is applied to estimate the immeasurable friction states. On the other hand, in light of the principles of vector control and field orientation, a set of virtual desired variables (VDVs) are introduced to synthesize the control law. Therefore, using only measurable signals of rotor speed, stator voltage and current, an asymptotic adaptive tracking controller is designed. Numerical simulations and experiments are carried out to verify the theoretical results and show satisfactory performance.     

Hybrid Fuzzy Model-Based Control of Nonholonomic Systems: A Unified Viewpoint

This paper proposes a unified hybrid fuzzy model-based control scheme for uncertain nonholonomic systems. Compared with typical hybrid fuzzy control, the stability analysis is performed based on a new concept of constructing a semicommon Lyapunov function and a new definition called as exponential-like model following. This advancement provides a strict stability analysis but results in relaxed gain conditions. In detail, a unified hybrid Takagi-Sugeno fuzzy model is first introduced for representing well-known nonholonomic systems with a momentum conservation constraint or a no-slip constraint. Then, the hybrid fuzzy controller is derived to ensure robust nonlinear model following control, i.e., an asymptotic convergence with adjustable ultimate bound and arbitrary disturbance attenuation in an -gain sense. Furthermore, an iterative linear matrix inequality technique is proposed to guarantee the stability and avoid the need of a common positive-definite matrix. Finally, the applications are carried out on a hopping robot and a car-like mobile robot. Numerical simulations and experiment results show the expected performances.     

Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Secure communications of chaotic systems with robust performancevia fuzzy observer-based design

This paper presents a systematic design methodology for fuzzy observer-based secure communications of chaotic systems with guaranteed robust performance. The Takagi-Sugeno fuzzy models are given to exactly represent chaotic systems. Then, the general fuzzy model of many well-known chaotic systems is constructed with only one premise variable in fuzzy rules and the same premise variable in the system output. Based on this general model, the fuzzy observer of chaotic system is given and leads the stability condition of a linear-matrix inequality problem. When taking the fuzzy observer-based design to applications on secure communications, the robust performance is presented by simultaneously considering the effects of parameter mismatch and external disturbances. Then, the error of the recovered message is stated in an H^∞ criterion. In addition, if the communication system is free of external disturbances, the asymptotic recovering of the message is obtained in the same framework. The main results also hold for applications on chaotic synchronization. Numerical simulations illustrate that this proposed scheme yields robust performance     

LMI-based fuzzy chaotic synchronization and communications

Addresses synthesis approaches for signal synchronization and secure communications of chaotic systems by using fuzzy system design methods based on linear matrix inequalities (LMIs). By introducing a fuzzy modeling methodology, many well-known continuous and discrete chaotic systems can be exactly represented by Takagi-Sugeno (T-S) fuzzy models with only one premise variable. Following the general form of fuzzy chaotic models, the structure of the response system is first proposed. Then, according to the applications of synchronization to the fuzzy models that have common bias terms or the same premise variable of drive and response systems, the driving signals are developed with four different types: fuzzy, character, crisp, and predictive driving signals. Synthesizing from the observer and controller points of view, all types of drive-response systems achieve asymptotic synchronization. For chaotic communications, the asymptotical recovering of messages is ensured by the same framework. It is found that many well-known chaotic systems can achieve their applications on asymptotical synchronization and recovering messages in secure communication by using either one type of driving signals or all. Several numerical simulations are shown with expected satisfactory performance     

Finite-time control of DC–DC buck converters via integral terminal sliding modes

This article presents novel terminal sliding modes for finite-time output tracking control of DC–DC buck converters. Instead of using traditional singular terminal sliding mode, two integral terminal sliding modes are introduced for robust output voltage tracking of uncertain buck converters. Different from traditional sliding mode control (SMC), the proposed controller assures finite convergence time for the tracking error and integral tracking error. Furthermore, the singular problem in traditional terminal SMC is removed from this article. When considering worse modelling, adaptive integral terminal SMC is derived to guarantee finite-time convergence under more relaxed stability conditions. In addition, several experiments show better start-up performance and robustness.     

Terminal sliding mode control for maximum power point tracking of photovoltaic power generation systems

This paper presents a novel terminal sliding mode control (TSMC) method for maximum power tracking of photovoltaic (PV) power systems. First, an incremental conductance method is used for maximum power point (MPP) searching. It provides good efficiency under rapidly changing atmospheric conditions, but the accuracy for finding the MPP is highly related to the MPP tracking control. Therefore, a TSMC-based controller is developed to regulate the system to the searched reference MPP. Different from traditional sliding mode control, the developed TSMC assures finite convergence time for the MPP tracking. Furthermore, a common singularity problem that exists in traditional TSMC is removed in this paper. Even if considering uncertainty in the PV power system, the TSMC guarantees high robustness. Finally, several simulations and experiments show the expected control performance.