Showing papers on "Feedback linearization published in 2015"

Modeling, control and design optimization for a fully-actuated hexarotor aerial vehicle with tilted propellers

Abstract: Mobility of a hexarotor UAV in its standard configuration is limited, since all the propeller force vectors are parallel and they achieve only 4-DoF actuation, similar, e.g., to quadrotors. As a consequence, the hexarotor pose cannot track an arbitrary trajectory while the center of mass is tracking a position trajectory. In this paper, we consider a different hexarotor architecture where propellers are tilted, without the need of any additional hardware. In this way, the hexarotor gains a 6-DoF actuation which allows to independently reach positions and orientations in free space and to be able to exert forces on the environment to resist any wrench for aerial manipulation tasks. After deriving the dynamical model of the proposed hexarotor, we discuss the controllability and the tilt angle optimization to reduce the control effort for the specific task. An exact feedback linearization and decoupling control law is proposed based on the input-output mapping, considering the Jacobian and task acceleration, for non-linear trajectory tracking. The capabilities of our approach are shown by simulation results.

Nonlinear Control of Quadrotor for Point Tracking: Actual Implementation and Experimental Tests

Abstract: In this paper, a nonlinear control scheme along with its simulation and experimental results for a quadrotor are presented. It is not easy to control the quadrotor because the dynamics of quadrotor, which is obtained via the Euler–Lagrangian approach, has the features of underactuated, strongly coupled terms, uncertainty, and multiinput/multioutput. We propose a new nonlinear controller by using a backstepping-like feedback linearization method to control and stabilize the quadrotor. The designed controller is divided into three subcontrollers which are called attitude controller, altitude controller, and position controller. Stability of the designed controller is verified by the Lyapunov stability theorem. Detailed hardware parameters and experimental setups to implement the proposed nonlinear control algorithms are presented. The validity of proposed control scheme is demonstrated by simulations under different simulation scenarios. Experimental results show that the proposed controller is able to carry out the tasks of taking off, hovering, and positioning.

Robust Control for a Class of Nonaffine Nonlinear Systems Based on the Uncertainty and Disturbance Estimator

Abstract: In this paper, the uncertainty and disturbance estimator (UDE)-based robust control is applied to the control of a class of nonaffine nonlinear systems. This class of systems is very general and covers a large range of nonlinear systems. However, the control of such systems is very challenging because the input variables are not expressed in an affine form, which leads to the failure of using feedback linearization. The proposed UDE-based control method avoids the inverse operator construction, which might result in the control singularity problem. Moreover, the general assumption on the uncertainty and disturbance term is relaxed, and only its bandwidth information is required for the control design. The asymptotic stability of the closed-loop system is established. The proposed approach is easy to be implemented and tuned while bringing very good robust performance. The important features and performance of the proposed approach are demonstrated through both simulation studies and experimental validation on a servo system with nonaffine uncertainties.

Back-stepping active disturbance rejection control design for integrated missile guidance and control system via reduced-order ESO.

Abstract: This paper proposes a novel composite integrated guidance and control (IGC) law for missile intercepting against unknown maneuvering target with multiple uncertainties and control constraint. First, by using back-stepping technique, the proposed IGC law design is separated into guidance loop and control loop. The unknown target maneuvers and variations of aerodynamics parameters in guidance and control loop are viewed as uncertainties, which are estimated and compensated by designed model-assisted reduced-order extended state observer (ESO). Second, based on the principle of active disturbance rejection control (ADRC), enhanced feedback linearization (FL) based control law is implemented for the IGC model using the estimates generated by reduced-order ESO. In addition, performance analysis and comparisons between ESO and reduced-order ESO are examined. Nonlinear tracking differentiator is employed to construct the derivative of virtual control command in the control loop. Third, the closed-loop stability for the considered system is established. Finally, the effectiveness of the proposed IGC law in enhanced interception performance such as smooth interception course, improved robustness against multiple uncertainties as well as reduced control consumption during initial phase are demonstrated through simulations.

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties.

Abstract: This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.

An Observer-Based Optimal Voltage Control Scheme for Three-Phase UPS Systems

Abstract: This paper proposes a simple optimal voltage control method for three-phase uninterruptible-power-supply systems. The proposed voltage controller is composed of a feedback control term and a compensating control term. The former term is designed to make the system errors converge to zero, whereas the latter term is applied to compensate for the system uncertainties. Moreover, the optimal load current observer is used to optimize system cost and reliability. Particularly, the closed-loop stability of an observer-based optimal voltage control law is mathematically proven by showing that the whole states of the augmented observer-based control system errors exponentially converge to zero. Unlike previous algorithms, the proposed method can make a tradeoff between control input magnitude and tracking error by simply choosing proper performance indexes. The effectiveness of the proposed controller is validated through simulations on MATLAB/Simulink and experiments on a prototype 600-VA testbed with a TMS320LF28335 DSP. Finally, the comparative results for the proposed scheme and the conventional feedback linearization control scheme are presented to demonstrate that the proposed algorithm achieves an excellent performance such as fast transient response, small steady-state error, and low total harmonic distortion under load step change, unbalanced load, and nonlinear load with the parameter variations.

Adaptive output feedback fault-tolerant control design for hypersonic flight vehicles

Abstract: In this paper, an adaptive output feedback fault-tolerant controller is developed for the longitudinal dynamics of a generic hypersonic flight vehicle in the presence of parameter uncertainties, actuator faults and external disturbances. Firstly, the derivatives of the output are calculated repeatedly so that the relative degree of the system is obtained. Then feedback linearization is used to design the nominal controller. Considering the occurrence of actuator faults, a fault-tolerant controller is developed based on the nominal feedback linearization controller to accommodate the effect of actuator fault, ensure system stability and recover desirable tracking performance. Since some of the states are difficult to measure during actual hypersonic flight, the high-gain observer technique is adopted to achieve output feedback fault-tolerant control. Adaptive laws are designed for updating the controller parameters when both the plant parameters and actuator fault parameters are unknown. Closed-loop stability and output tracking performance are analyzed rigorously. Simulation results verify the effectiveness of the proposed adaptive fault-tolerant control scheme.

Solving Multi-UAV Dynamic Encirclement via Model Predictive Control

Abstract: In order for teams of unmanned aerial vehicles (UAVs) to collaborate and cooperate to perform challenging group tasks, intelligent and flexible control strategies are required. One of the complex behaviors required of a team of UAVs is dynamic encirclement, which is a tactic that can be employed for persistent surveillance and/or to neutralize a target by restricting its movement. This tactic requires a high level of cooperation such that the UAVs maintain a desired and proper encirclement radius and angular velocity around the target. In this paper, model predictive control (MPC) is used to model and implement controllers for the problem of dynamic encirclement. The linear and nonlinear control policies proposed in this paper are applied as a high-level controller to control multiple UAVs to encircle a desired target in simulations and real-time experiments with quadrotors. The nonlinear solution provides a theoretical analysis of the problem, while the linear control policy is used for real-time operation via a combination of MPC and feedback linearization applied to the nonlinear UAV system. The contributions of this paper lie in the implementation of MPC to solve the problem of dynamic encirclement of a team of UAVs in real time and the application of theoretical stability analysis to the problem.

Nonlinear Control of a Buck Converter Which Feeds a Constant Power Load

Abstract: In this paper, a nonlinear control strategy for controlling a dc/dc buck converter feeding a constant power load is proposed. The main objective of the proposed controller is to improve the transient performance when in presence of unknown power disturbances. A feedback controller is combined with a feedforward strategy. A nonlinear reduced order observer is used for estimating the value of the power load and its time derivative. These estimated values are fed forward to the nonlinear feedback controller whose design is based on feedback linearization method. The proposed controller is tested via simulation and experimental results.

Quadrotor control: modeling, nonlinear control design, and simulation

Abstract: In this work, a mathematical model of a quadrotor’s dynamics is derived, using Newton’s and Euler’s laws. A linearized version of the model is obtained, and therefore a linear controller, the Linear Quadratic Regulator, is derived. After that, two feedback linearization control schemes are designed. The first one is the dynamic inversion with zero dynamics stabilization, based on Static Feedback Linearization obtaining a partial linearization of the mathematical model. The second one is the exact linearization and non-interacting control via dynamic feedback, based on Dynamic Feedback Linearization obtaining a total linearization of the mathematical model. Moreover, these nonlinear control strategies are compared with the Linear Quadratic Regulator in terms of performances. Finally, the behavior of the quadrotor under the proposed control strategies is observed in virtual reality by using the Simulink 3D Animation toolbox.

Deadbeat Control for Electrical Drives: A Robust and Performant Design Based on Differential Flatness

Abstract: The present contribution introduces a new deadbeat controller design that increases robustness without compromising performance. In conventional deadbeat control, feedback linearization is applied, and the feedback gains are set very high to obtain the minimum-step reference response. This makes the control method highly sensitive to parametric uncertainties. To date, the only remedies have been to tune the deadbeat controller settling time higher and the according disturbance estimator more slowly. Recently proposed remedies based on online parameter estimators show either moderate performance or higher demands on hardware. Therefore, first a feedforward linearization-based controller is introduced to obtain the desired reference response via open-loop control. Thereby, the parametric sensitivity is considerably improved. Then, the new generalized flatness-based controller, a mix between feedback and feedforward linearization, is proposed. The result is a deadbeat controller with high dynamic performance and high robustness with respect to both parameter uncertainties and disturbances. The experimental results on an induction machine demonstrate very fast reference tracking, high robustness to typical parameter uncertainties, and active compensation of time-varying disturbances. The results on a synchronous reluctance machine show that even very large inductance uncertainties can be handled.

Model-based feedforward position control of constant curvature continuum robots using feedback linearization

Abstract: Fast and exact motions of continuum robots are hardly seen so far. Partly this is caused by physical constraints, e.g. small available actuation forces. Another reason is the dynamic coupling between the actuators that cannot be neglected during fast motions. Therefore, a model-based MIMO controller in actuator space was developed, that is based on a spatial dynamic model with one mass point per section. Using feedback linearization, the actuators can be decoupled and feedforward control in combination with linear controllers can be applied. Measurements of an example manipulator show the good tracking result of pure feedforward action with feedback linearization. Adding a linear PD-controller increases the robustness against disturbances without reducing the possibility of fast motions.

Nonlinear attitude control scheme with disturbance observer for flexible spacecrafts

Abstract: To attenuate the effects of parameter variations and disturbances of flexible spacecrafts on attitude control accuracy and stability, a composite control approach by combining nonlinear disturbance observer (NDO) and feedback linearization (FBL) control is proposed. In this paper, the multiple disturbances that act on spacecrafts from flexible appendages, space environment, and unmodelled dynamics are considered as an ‘equivalent’ disturbance. The proposed NDO is used to estimate and compensate for the disturbances through feedforward. Stability and tracking performance of the NDO are then analyzed. Moreover, the stability of the FBL + NDO composite control approach is established through the Lyapunov method. Simulation results show that the NDO can estimate disturbances and reduce the effect of disturbances on spacecrafts through feedforward compensation. Robust dynamic performance and attitude control accuracy are effectively improved.

Cooperative manipulation exploiting only implicit communication

Abstract: This paper addresses the problem of cooperative object manipulation with the coordination relying solely on implicit communication. We consider a decentralized leader-follower architecture where the leading robot, that has exclusive knowledge of the object's desired trajectory, tries to achieve the desired tracking behavior via an impedance control law. On the other hand, the follower estimates the leader's desired motion via a novel prescribed performance estimation law, that drives the estimation error to an arbitrarily small residual set, and implements a similar impedance control law. Both control schemes adopt feedback linearization as well as load sharing among the robots according to their specific payload capabilities. The feedback relies exclusively on each robot's force/torque, position as well as velocity measurements and apart from a few commonly predetermined constant parameters, no explicit data is exchanged on-line among the robots, thus reducing the required communication bandwidth and increasing robustness. Finally, a comparative simulation study clarifies the proposed

Path Following Using Dynamic Transverse Feedback Linearization for Car-Like Robots

Abstract: This paper presents an approach for designing path-following controllers for the kinematic model of car-like mobile robots using transverse feedback linearization with dynamic extension. This approach is applicable to a large class of paths and its effectiveness is experimentally demonstrated on a Chameleon R100 Ackermann steering robot. Transverse feedback linearization makes the desired path attractive and invariant, while the dynamic extension allows the closed-loop system to achieve the desired motion along the path.

Variation-Based Linearization of Nonlinear Systems Evolving on $SO(3)$ and $\mathbb S^{2}$

Abstract: In this paper, we propose a variation-based method to linearize the nonlinear dynamics of robotic systems, whose configuration spaces contain the manifolds $\mathbb S^{2}$ and $SO(3)$ , along dynamically feasible reference trajectories. The proposed variation-based linearization results in an implicitly time-varying linear system, representing the error dynamics, that is globally valid. We illustrate this method through three different systems: 1) a 3-D pendulum: 2) a spherical pendulum; and 3) a quadrotor with a suspended load, whose dynamics evolve on $SO(3)$ , $\mathbb S^{2}$ , and $SE(3) \times \mathbb S^{2}$ , respectively. We show that for these systems, the resulting time-varying linear system obtained as the linearization about a reference trajectory is controllable for all possible reference trajectories. Finally, a linear quadratic regulator-based controller is designed to attenuate the error so as to locally exponentially stabilize tracking of a reference trajectory for the nonlinear system. Several simulations results are provided to validate the effectiveness of this method.

A Maximum Power Tracking Technique for Grid-Connected DFIG-Based Wind Turbines

Abstract: In this paper, a maximum power tracking technique is presented for doubly fed induction generator-based wind turbines. The presented technique is a novel version of the conventional method, i.e., the electrical torque is proportional to the square of the rotor speed, in which the proportional coefficient is adaptively adjusted in real-time through three control laws. The first control law calculates the desired electrical torque using feedback linearization, assuming that the power capture coefficient and the desired rotor speed are instantaneously identified. The second control law estimates the real-time values of the power capture coefficient from a Lyapunov-based analysis, and the third control law provides the desired rotor speed. These control laws cause the turbine to adaptively adjust the rotor speed toward a desired speed in which the operating point moves in the direction of increasing the power capture coefficient. The proposed maximum power tracking method differs distinctly from the perturb-and-observe scheme by eliminating a need for adding a dither or perturbation signal, and robustly tracks the trajectory of maximum power points even in the event of a sudden wind speed change that can cause the perturb-and-observe technique to fail. In this paper, the National Renewal Energy Laboratory 5-MW reference wind turbine model is used to demonstrate the validity and robustness of the proposed method.

Relative Degrees and Adaptive Feedback Linearization Control of T–S Fuzzy Systems

Abstract: This paper presents a new study on the relative degrees of single-input and single-output T–S fuzzy systems in general noncanonical forms, and proposes a feedback linearization-based control design method for such systems. The study extends the system relative degree concepts, commonly used for the control of nonlinear systems, to general T–S fuzzy systems, derives various relative degree conditions for general T–S fuzzy systems, and establishes the relative degree dependent normal forms. A feedback linearization-based control design framework is developed for general T–S fuzzy systems using its normal form, to achieve closed-loop stability and asymptotic output tracking under relaxed design conditions. A new adaptive feedback linearization-based control scheme for T–S fuzzy systems in general noncanonical forms with parameter uncertainties is designed and analyzed. Some extensions of relative degrees and their possible application to robust adaptive control for noncanonical form T–S fuzzy systems are also demonstrated. An illustrative example is presented with simulation results to demonstrate the control system design procedure and to show the effectiveness of the proposed control scheme.

A novel self-adaptive modified bat fuzzy sliding mode control of robot manipulator in presence of uncertainties in task space

Abstract: In this paper, an optimal fuzzy sliding mode controller has been designed for controlling the end-effector position in the task space. In the proposed control, feedback linearization method, sliding mode control, first-order fuzzy TSK system and optimization algorithm are utilized. In the proposed controller, a novel heuristic algorithm namely self-adaptive modified bat algorithm (SAMBA) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input membership functions are optimized by SAMBA simultaneously. In this method, the bounds of structural and non-structural uncertainties are reduced by using feedback linearization method, and to overcome the remaining uncertainties, sliding mode control is employed. Mathematical proof demonstrates that the closed loop system with the proposed control has global asymptotic stability. The presence of sliding mode control gives rise to the adverse phenomenon of chattering in the end-effector position tracking in the task space. Subsequently, to prevent the occurrence of chattering in control input, a first-order TSK fuzzy approximator is utilized. Finally, to determine the fuzzy sliding mode controller coefficients, the optimization algorithm of Self-Adaptive Modified Bat is employed. To investigate the performance of the proposed control, a two-degree-of-freedom manipulator is used as a case study. The simulation results indicate the favorable performance of the proposed method.

Adaptive Control for Aircraft Longitudinal Dynamics with Thrust Saturation

Abstract: An output-feedback control law is designed for the longitudinal flight dynamics of an aircraft. The proposed control law is designed using the adaptive backstepping method and does not require any knowledge of aircraft aerodynamics beyond well-known qualitative physical properties. The resulting feedback controller is able to follow given references in both airspeed and flight-path angle by actuating elevator deflections and aircraft engine thrust. Engine physical limits are incorporated into the design by using a Lyapunov function analysis that includes saturation, obtaining a novel hybrid adaptation law that guarantees closed-loop system stability. Simulation results show good performance of the feedback law and, in particular, demonstrate that the hybrid adaptation law improves the behavior of the closed-loop system when saturations are present. A degraded scenario (a sudden cargo displacement that renders the aircraft statically unstable) is also considered to show the adaptation capabilities of the c...

A recursive Newton-Euler algorithm for robots with elastic joints and its application to control

Abstract: We consider the problem of computing the inverse dynamics of a serial robot manipulator with N elastic joints in a recursive numerical way. The solution algorithm is a generalized version of the standard Newton-Euler approach, running still with linear complexity O(N) but requiring to set up recursions that involve higher order derivatives of motion and force variables. Mimicking the case of rigid robots, we use this algorithm and a numerical factorization of the link inertia matrix (which needs to be inverted in the elastic joint case) for implementing on-line a feedback linearization control law for trajectory tracking purposes. The complete method has a complexity that grows as O(N3). The developed tools are generic, easy to use, and do not require symbolic Lagrangian modeling and customization, thus being of particular interest when the number N of elastic joints becomes large.

Experimental Validation of a Fuzzy Adaptive Voltage Controller for Three-Phase PWM Inverter of a Standalone DG Unit

Abstract: This paper investigates a disturbance observer-based fuzzy adaptive voltage controller for three-phase pulse width modulation (PWM) inverter of a standalone distributed generation (DG) unit in the existence of system uncertainties. The proposed control law includes only a voltage control loop, which has advantages such as a simple control structure and a fast transient response due to the direct control of the output voltage. Next, a disturbance observer is presented to reduce the number of the sensors and improve the control performance. Besides, the proposed strategy is insensitive to any system uncertainties, because it does not require any accurate knowledge about system parameter and load current information. Experimental results on a prototype DG unit with a TMS320F28335 DSP are demonstrated to validate the superior performance of the proposed control scheme over the conventional proportional-derivative (PD) control method and feedback linearization control (FLC) method under sudden load disturbances, system uncertainties, and nonlinear load.

Survey of advances in control algorithms of quadrotor unmanned aerial vehicle

Abstract: First, the basic structure and principle of quadrotor UAV and its practical applications are introduced. Then, some control algorithms are also presented, such as, PID, LQR/LQG, H∞, sliding mode, feedback linearization, back stepping, model predictive, robust, adaptive, nested saturation, fuzzy logic, neural network, reinforcement learning, iterative learning, memory and brain emotional learning-based intelligent controllers, and the merits and drawbacks of them are analyzed. At last, we predict the main research direction on the future researches of quadrotor UAV.