Inversion-free force tracking control of piezoelectric actuators using fast finite-time integral terminal sliding-mode

The major hurdles to control the force created by piezoelectric actuators (PEAs) are originated from its strong nonlinear behaviors which include hysteresis, creep, and vibration dynamics. To achieve an accurate, fast and robust force tracking performance without using complicated modeling and parameter identification of PEAs, this paper presents a practical direct force control scheme. The proposed controller is based on two core approaches: 1) fast finite-time integral terminal sliding mode (FFI-TSM) which allows fast convergence and high accuracy to the closed-loop system without control chattering; and 2) an inverse-model-free compensation, named force-based time-delayed estimation (FBTDE) which offers significant robustness with minimum use of plant dynamics information. The finite-time stability of the overall closed-loop system is proven through the Lyapunov’s method. The proposed force tracking controller is implemented on the PEA system driving a variable physical damping actuator mechanism. The overall accuracy, convergence speed, and robustness of the proposed controller are validated under various experimental scenarios. Comparative experimental results are particularly presented to verify the effectiveness of the FFI-TSM term and the FBTDE term.     

A neural-network-based controller for a single-link flexiblemanipulator using the inverse dynamics approach

This paper presents an intelligent-based control strategy for tip position tracking control of a single-link flexible manipulator. Motivated by the well-known inverse dynamics control strategy for rigid-link manipulators, two feedforward neural networks (NNs) are proposed to learn the nonlinearities of the flexible arm associated with the inverse dynamics controller. The redefined output approach is used by feeding back this output to guarantee the minimum phase behavior of the resulting closed-loop system. No a priori knowledge about the nonlinearities of the system is needed and the payload mass is also assumed to be unknown. The network weights are adjusted using a modified online error backpropagation algorithm that is based on the propagation of output tracking error, derivative of that error and the tip deflection of the manipulator. The real-time controller is implemented on an experimental test bed. The results achieved by the proposed NN-based controller are compared experimentally with conventional proportional-plus-derivative-type and standard inverse dynamics controls to substantiate and verify the advantages of our proposed scheme and its promising potential in identification and control of nonlinear systems     

Fuzzy error governor: A practical approach to counter actuator saturation on flexible joint robots

In this paper, a practical method to counter actuator saturation based on a fuzzy error governor is developed and a complete case study is considered. In addition to good performance, the method has two attracting properties: It does not change the structure of the main controller, and therefore, the theoretically proven characteristics of the system are untouched, and it is simply implementable in practice. The proposed controller structure is applied on a flexible joint robot (FJR). The robust stability of the closed loop system for an n-DOF FJR is thoroughly analyzed and the proposed controller is implemented on a laboratory setup to show the ease of implementation and the resulting closed-loop performance. The main controller used for the n-DOF FJR consists of a composite structure, with a PD controller on the fast dynamics and a PID controller on the slow dynamics. The bandwidth of the fast controller is decreased during critical occasions with the fuzzy logic supervisor, which adjusts the loop gain to a proper level. Using Lyapunov direct method, the robust stability of the overall system is analyzed in presence of modeling uncertainties, and it is shown that if the PD and the PID gains are tuned to satisfy certain conditions, the closed loop system becomes UUB stable.     

A Control Scheme for PWM Voltage-Source Distributed-Generation Inverters for Fast Load-Voltage Regulation and Effective Mitigation of Unbalanced Voltage Disturbances

This paper presents a control scheme for grid-connected pulsewidth-modulated voltage-source inverters (VSIs) featuring fast load-voltage regulation and effective mitigation of unbalanced voltage disturbances. To ensure perfect regulation of the voltage at the point of common coupling (PCC) and provide means for rejecting fast and dynamic voltage disturbances, the frequency modes of the disturbances to be eliminated should be included in the stable closed-loop system. Toward this, a hybrid voltage controller combining a linear with variable-structure control element is proposed for an inverter-based distributed-generation interface to regulate the voltage at the PCC. The proposed voltage controller can embed a wide band of frequency modes through an equivalent internal model. Subsequently, a wide range of voltage perturbations, including capacitor-switching disturbances, can be rejected. To account for unbalanced voltage disturbances, a dual-sequence voltage controller is proposed. To provide accurate and robust tracking of the generated active and reactive current trajectories, a newly designed deadbeat current control algorithm is proposed. The controller is designed under the practical considerations of inherent plant delays, which are associated with the digital implementation of the control algorithm, and the uncertain nature of the current dynamics. Theoretical analysis and comparative evaluation tests are presented to demonstrate the effectiveness of the proposed control scheme.     

A nonlinear state observer for the sensorless control of apermanent-magnet AC machine

This paper presents a sensorless speed regulation scheme for a permanent-magnet synchronous motor (PMSM) based solely on the motor line currents measurements. The proposed scheme combines an exact linearization-based controller with a nonlinear state observer which estimates the rotor position and speed. Moreover, the stability of the closed-loop system, including the observer, is demonstrated through Lyapunov stability theory. The proposed observer has the advantage of being insensitive to rotation direction. It is shown how a singularity at zero velocity appears in the scheme and how it can be avoided by switching smoothly from the observer-based closed-loop control to an open-loop control at low velocity. The system performance is tested with an experimental setup consisting of a PMSM servo drive and a digital-signal-processor-based controller for both unidirectional and bidirectional speed regulation     

Robust PID control of fully-constrained cable driven parallel robots

In this paper dynamic analysis and robust PID control of fully-constrained cable driven parallel manipulators are studied in detail. Since in this class of manipulators cables should remain in tension for all maneuvers in their workspace, feedback control of such robots becomes more challenging than that of conventional parallel robots. In this paper, structured and unstructured uncertainties in dynamics of the robot are considered and a robust PID controller is proposed for the cable robot. To ensure that all cables remain in tension internal force concept is used in the proposed PID control algorithm. Then, robust stability of the closed-loop system with proposed control algorithm is analyzed through Lyapunov direct method and it is shown that by suitable selection of the PID controller gains, the closed-loop system would be robustly stable. Finally, the effectiveness of the proposed PID algorithm is examined through experiments on a planar cable driven robot and it is shown that the proposed control structure is able to provide suitable performance in practice.     

Model reference adaptive control of a soft bending actuator with input constraints and parametric uncertainties

In this article, model reference adaptive control of a pneumatically actuated soft robot has been studied in detail. To deal with the effects of system uncertainties, in the proposed control scheme, parametric uncertainties and input constraints are taken into account. To design such a controller, based on experimental analysis, the robot has been modeled as a second-order Linear Parameter Varying (LPV) system. Then, the dominant dynamics are presented as a Linear Time-Invariant (LTI) system, while uni-directional input constraint has been considered as a critical issue in the control scheme design. Furthermore, to compensate parametric uncertainties as well as unmodeled dynamics, adaptive laws are modified. Finally, the effectiveness is studied in different scenarios on an experimental platform to validate our claims. Moreover, to show the proposed approach capabilities and performance, the proposed controller has been compared with a PID and a recent sophisticated robust-adaptive controller, which presented a new formulation to achieve a better tracking performance with guaranteed stability in the presence of different constraints and unmodeled dynamics.     

New fractional-order LADRC scheme based on a novel filtered-Bode’s ideal transfer function for integer-order systems

In this paper, a new Fractional-Order Linear Active Disturbance Rejection Control scheme (FO-LADRC) is proposed to enhance the robustness against loop gain variations of the standard Active Disturbance Rejection Control (ADRC) in the case of uncertain integer-order systems. A new filtered Bode’s ideal transfer function (F-BITF) is proposed to be used as a reference model in the design approach of the proposed control scheme to ensure the dynamic behavior of the closed-loop BITF to the controlled system. A Fractional-order Extended State Observer (F-ESO) is used in the proposed FO-LADRC structure to approximate the system to be controlled by a filtered fractional-order integrator. The fractional order of the F-ESO is a design parameter to tune to achieve the desired overshoot of the closed-loop step response. For the tuning of FO-LADRC structure, an analytical method is proposed. The performance of the proposed FO-LADRC and the Chen’s et al. FO-ADRC structures are evaluated thorough numerical simulation, and then validated in practice in the case of a Cart-Pendulum. Both the simulation and the experimental results show that the proposed FO-LADRC is able to achieve the desired dynamics of the F-BITF and guarantee the robustness with respect to the controller gain variation and the system parameter uncertainties. The comparative study conducted also reveals that the proposed control scheme is more robust than that of Chen.     

Nonlinear control of a dynamic model of HIV-1

Highly active antiretroviral therapy (HAART) reduces the viral burden in human immunodeficiency virus type 1 (HIV-1) infected patients. The paper addresses the problem of controlling the predator-prey like model of the interaction among CD4+ T-cell, CD8+ T-cell, and HIV-1 by an external drug agency. By exploring the dynamic properties of the system, the original system is first regrouped into two subsystems, then a nonlinear global controller is presented by designing two controllers over two complementary zones: a local controller on a finite region and a global controller over its complement. The local controller is designed to guarantee nonnegativty, and avoids the problem of control singularity within the neighborhood of the origin omega. The complementary controller is designed via backstepping for both subsystems over the complementary region. The closed-loop system is globally stable at nominal values through the introduction of a novel bridging virtual control, and the resulting controller is singularity free and guarantees nonnegativity. In this paper, simulations are conducted in discrete-time with sampling time Ts to show the effectiveness of the proposed method.     

Torque-maximizing field-weakening control: design, analysis, andparameter selection

The torque-maximizing field-weakening control scheme proposed by Kim and Sul is developed further. The performance under imperfect field orientation conditions is investigated, and it is shown that an overestimated-rather than an underestimated-model leakage inductance should be used. A slightly modified algorithm, which offers better robustness and reduced computational complexity, is presented. The importance, for good performance, of combining the scheme with current and speed controllers featuring antiwindup and improved disturbance rejection is emphasized. The dynamics of the resulting closed-loop system are analyzed. Obtained in the process, are rules for selection of all controller parameters, allowing tuning without trial-and error steps. Good performance of the resulting system is verified experimentally     

An approach to inverse nonlinear control using neural networks

In this paper, we present a strategy for controlling a class of nonlinear dynamical systems using techniques based on neural networks. The proposed strategy essentially exploits the property of neural networks in being able to approximate arbitrary nonlinear maps when suitable learning strategies are applied. For the closed-loop control, such a network is used in conjunction with a technique of inverse nonlinear control to form what we call an inverse nonlinear controller using neural networks, abbreviated as the INC/NN controller. Properties of the controller are discussed, and it is shown that the proposed INC/NN controller allows the closed-loop error dynamics to be specified directly through a set of controller gains. Extensions of the basic INC/NN controller to incorporate integral control action, to higher order systems, and to a class of nonlinear multi-input multi-output dynamical systems are also indicated. Finally, results of some real-time experiments in applying the INC/NN controller to a position control system which has inherent nonlinearities are presented.     

Decentralized nonlinear adaptive control of an HVAC system

This paper presents a new decentralized nonlinear adaptive controller (DNAC) for a heating, ventilating, and air conditioning (HVAC) system capable of maintaining comfortable conditions under varying thermal loads. In this scheme, an HVAC system is considered to be two subsystems and controlled independently. The interactions between the two subsystems are treated as deterministic types of uncertain disturbances and their magnitudes are supposed to be bounded by absolute value. The decentralized nonlinear adaptive controller (DNAC) consists of an inner loop and an outer loop. The inner loop is a single-input fuzzy logic controller (FLC), which is used as the feedback controller to overcome random instant disturbances. The outer loop is a Fourier integral-based control, which is used as the frequency-domain adaptive compensator to overcome steady, lasting uncertain disturbances. The global DNAC controller ensures that the system output vector tracks a desired trajectory vector within the system bandwidth and that the tracking error vector converges uniformly to a zero vector. The simulated experimental results on the HVAC system show that the performance is dramatically improved.     

Adaptive coupling control for overhead crane systems

Due to the requirements of high positioning accuracy, small swing angle, short transportation time, and high safety, both motion and stabilization control for an overhead crane system becomes an interesting issue in the field of control technology development. Since the overhead crane system is subject to underactuation with respect to the load sway dynamics, it is very hard to manipulate the crane system in a desired manner, namely, gantry position tracking and sway angle stabilization. Hence, in this paper, a nonlinear control scheme incorporating parameter adaptive mechanism is devised to ensure the overall closed-loop system stability. By applying the designed controller, the position error will be driven to zero while the sway angle is rapidly damped to achieve swing stabilization. Stability proof of the overall system is given in terms of Lyapunov concept. To demonstrate the effectiveness of the proposed controller, results for both computer simulation and experiments are also shown.     

An Improved Deadbeat Current Control Scheme With a Novel Adaptive Self-Tuning Load Model for a Three-Phase PWM Voltage-Source Inverter

In this paper, an improved deadbeat current control scheme with a novel adaptive self-tuning load model for a three-phase pulsewidth-modulated (PWM) voltage-source inverter is proposed. First, to achieve high-bandwidth current control characteristics, an improved deadbeat current controller with delay compensation is adopted. The compensation method forces the delay elements, which are caused by voltage calculation, PWM, and synchronous frame rotation, to be equivalently placed outside the closed-loop control system. Hence, their effect on the closed-loop stability is eliminated, and the current controller can be designed with a higher bandwidth. Second, to relax the parameter sensitivity issue of the deadbeat controller and to realize a control scheme with reduced sensors, a novel adaptive self-tuning load model is emerged in the control structure. The adaptive model is designed with low computational demand to estimate in real time the load parameters (R,L) and the back-electromotive-force voltage simultaneously. A unified solution to the present nonlinear estimation problem is presented by adopting a parallel observer structure. Furthermore, the adaptive model has the necessary phase advance of the estimated quantities, which compensates for the total system's delay. Comparative evaluation results are presented to demonstrate the validity and effectiveness of the proposed control scheme     

Adaptive Fuzzy Output-Feedback Control for Switched Nonlinear Systems with Arbitrary Switchings

This paper investigates the adaptive fuzzy output-feedback control problem for single-input and single-output switched uncertain nonlinear systems. The addressed systems in this paper have the characteristics of arbitrary switchings, unknown nonlinear dynamics and immeasurable states. A common state observer is designed independent of switching signals. Fuzzy logic systems are utilized to approximate unknown lumped nonlinear dynamics. Based on the framework of backstepping design technique, an adaptive fuzzy output-feedback control scheme is developed. By using the common Lyapunov function theory, the stability of the closed-loop system is proved. The proposed control scheme does not need the assumptions that the states of the controlled system are available for measurement and that the switching signals satisfy the average dwell time. Moreover, it can guarantee that all the closed-loop signals are bounded, and the system output eventually converges to a small neighborhood of the origin. Finally, simulation studies are provided to further check the effectiveness of the proposed control scheme.     

Integrated design of mechanical structure and control algorithm fora programmable four-bar linkage

As the demand increases for machines of high accuracy, high speed, and high stiffness, programmable closed-loop linkages emerge in the development of modern machinery. A mechatronic design methodology is proposed for the integrated design of mechanical structure and control algorithm for a programmable closed-loop mechanism system. This design methodology suggests a negative mass-redistribution scheme, which follows the principle of a shaking force/shaking moment balancing scheme, for the modification of an existing four-bar mechanism, with the aim to obtain a simple system dynamic model and, thus, to facilitate controller design. In consequence, motion tracking performance and vibration behavior of the linkage system are significantly improved by simply applying a conventional PD control algorithm. The effectiveness of the proposed methodology has been verified by simulation studies     

Sliding-mode motion controller with adaptive fuzzy disturbance estimation

This paper proposes a motion control scheme which belongs to the class of the control schemes known as sliding-mode control with disturbance estimation. A novel adaptive fuzzy disturbance estimator works as an estimator of a major part of robot dynamics. The adaptation algorithm is derived by using the Lyapunov stability theory and provides global asymptotic stability of the state errors, resulting in the sliding-mode regime. The structure of the disturbance estimator is optimized by the introduction of three fuzzy logic subsystems, based on the physical properties of the robot mechanism. This also significantly lowers the computational burden and enables real-time implementation. Performance of the proposed controller scheme, as well as some practical design aspects, are demonstrated by the control of a direct-drive robot.     

A Hybrid-Type Variable-Structure Instantaneous Torque Control With a Robust Adaptive Torque Observer for a High-Performance Direct-Drive PMSM

This paper describes a novel instantaneous torque control scheme for a high-performance direct-drive permanent-magnet synchronous motor. The scheme consists of a robust adaptive instantaneous torque observer and a hybrid-type variable-structure instantaneous torque controller. First, to robustly obtain the instantaneous electromagnetic torque information, a robust adaptive torque observer is designed by considering all possible current model uncertainties. The observation gains and uncertainties prediction rules are derived in the sense of Lyapunov theory so that the stability of the proposed estimation scheme is fulfilled. Second, to ensure perfect tracking of the output torque and providing means in eliminating torque ripples, the frequency modes of the disturbances to be eliminated should be included in the stable closed-loop system. To achieve this objective, a hybrid-type variable-structure controller with internal model, for the flux harmonics and system uncertainties, is adopted. The hybrid controller shows better disturbance rejection without control chattering. Comparative evaluation results are presented to demonstrate the validity and effectiveness of the proposed instantaneous torque control scheme.     

Lyapunov-function-based design of fuzzy logic controllers and itsapplication on combining controllers

This paper presents the design of fuzzy logic controllers (FLCs) for nonlinear systems with guaranteed closed-loop stability and its application on combining controllers. The design is based on heuristic fuzzy rules. Although each rule in the FLC refers to a stable closed-loop subsystem, the overall system stability cannot be guaranteed when all these rules are applied together. In this paper, it is proved that if each subsystem is stable in the sense of Lyapunov (ISL) under a common Lyapunov function, the overall system is also stable ISL. Since no fuzzy plant model is involved, the number of subsystems generated is relatively small, and the common Lyapunov function can be found more easily. To probe further, an application of this design approach to an inverted pendulum system that combines a sliding-mode controller (SMC) and a state feedback controller (SFC) is reported. Each rule in this FLC has an SMC or an SFC in the consequent part. The role of the FLC is to schedule the final control under different antecedents. The stability of the whole system is guaranteed by the proposed design approach. More importantly, the controller thus designed can keep the advantages and remove the disadvantages of the two conventional controllers