Design Of Trajectory Tracking Controller Research Articles

Robust Trajectory Tracking for an Uncertain UAV Based on Active Disturbance Rejection

This note addresses the design of a robust trajectory tracking controller based on active disturbance rejection for a quadrotor Unmanned Aircraft Vehicle (UAV). A standard state-feedback linearizing controller, designed using a nominal model, is applied for tracking reference signals. An active disturbance rejection technique based on high-order sliding modes compensates for the uncertainties and nonlinearities. Furthermore, this rejection technique provides robustness against uncertainties and external disturbances after a finite transient time. Outdoors experimental results in a prototype illustrate the workability of the proposed methodology.

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

Robot manipulators have complex dynamics and are affected by significant uncertainties and external disturbances (perturbations). Consequently, determining the exact mathematical model of a robot manipulator is a tedious task. Accordingly, accurate trajectory tracking is a dominant feature in the design of position control for robot manipulators. The main objective of this research is to design a robust and accurate position control for a robot manipulator despite the absence of an exact model. For this purpose, an extended state observer (ESO)-based sliding mode control (SMC) is proposed. The main concept in the ESO is to define and estimate the assumed perturbation, which includes known and unknown system dynamics, uncertainties, and external disturbances. Additionally, the ESO estimates the system states. This estimated perturbation information, which is combined with the SMC input, is utilized as a feedback term to compensate for the effect of the actual perturbation. The perturbation compensation improves the controller performance, resulting in a slight position error, less sensitivity to perturbation, and a small switching gain required for the SMC. The advantage of the proposed algorithm is that it only requires partial state information and position feedback. Thus, identifying the system parameters for the nominal model before designing the controller is unnecessary. The proposed algorithm is implemented and compared with the conventional SMC and the SMC with a sliding perturbation observer (SMCSPO) in a virtual environment based on MATLAB SimMechanics. The comparison results validate the robustness of the proposed technique in the presence of perturbation and show that the technique has a significantly reduced trajectory tracking error than the conventional SMC and SMCSPO.

Tracking control for a flat system under disturbances: a fixed-wing UAV example

This paper considers a class of systems admitting several flat representations and proposes a trajectory tracking controller design which accounts for disturbance rejection. Set invariance is used for characterizing the tracking and estimation error dynamics. Furthermore, some insights on the disturbance propagation in case of different flat representations for a fixed-wing Unmanned Aerial Vehicle (UAV) system are highlighted via simulations and comparisons.

Asymptotic Trajectory Tracking of Autonomous Bicycles via Backstepping and Optimal Control

This letter studies the trajectory tracking problem for an autonomous bicycle that is a non-minimum phase, strongly nonlinear system. As compared with most existing methods dealing only with approximate trajectory tracking, this letter proposes a constructive design to achieve asymptotic trajectory tracking. More specifically, under the assumption that the desired trajectory is generated by a virtual bicycle, a novel asymptotic trajectory tracking controller design scheme is presented. Firstly, the nonlinear dynamics of the autonomous bicycle is established. Secondly, it is decomposed into two interconnected subsystems: a tracking subsystem and a balancing subsystem. For the tracking subsystem, the popular backstepping approach is applied to determine the propulsive force of the bicycle. For the balancing subsystem, optimal control is applied to determine the steering angular velocity of the handlebar in order to balance the bicycle and align the bicycle with the desired yaw angle. Thirdly, to tackle the strong coupling between the tracking and the balancing systems, the small-gain technique is applied for the first time to prove the asymptotic stability of the closed-loop bicycle system. Finally, the efficacy of the proposed exact trajectory tracking control methodology is validated by numerical simulations.

Trajectory tracking control of underactuated tendon‐driven truss‐like manipulator based on type‐1 and interval type‐2 fuzzy logic approach

This paper deals with the trajectory tracking control problem of a planar underactuated tendon-driven truss-like manipulator (UTTM) by using fuzzy logic control methods, including type-1 fuzzy and interval type-2 fuzzy approaches. The UTTM is a novel designed underactuated robot that excels in manipulating in harsh environments due to its tendon-driven parallelogram structure. This unique structure, however, poses challenges for UTTM's trajectory tracking controller design, including underactuation, excessive nonlinearity, parameter uncertainty, and so on. To solve these problems, a fuzzy logic-based approach is proposed. First, the dynamic model of UTTM is transformed into a partially linearized form. Then a type-1 fuzzy controller is designed according to a linear quadratic regulator controller for the linearized system. Then by blurring the membership functions of type-1 fuzzy controllers, an interval type-2 fuzzy logic controller is designed, aiming at dealing with uncertainties. The proposed type-1 and interval type-2 fuzzy logic controllers are validated through simulations, and made comparisons with each other, especially when the system is involved with uncertainties. Simulation results show that the interval type-2 fuzzy-based trajectory tracking controller provides better performance than the type-1 counterpart in terms of tracking accuracy and capacity against uncertainties.

Trajectory-Tracking Controller Design of Rotorcraft Using an Adaptive Incremental-Backstepping Approach

This paper treats a robust adaptive trajectory-tracking control design for a rotorcraft using a high-fidelity math model subject to model uncertainties. In order to control the nonlinear rotorcraft model which shows strong inter-axis coupling and high nonlinearity, incremental backstepping approach with state-dependent control effectiveness matrix is utilized. Since the incremental backstepping control suffers from performance degradation in the presence of control matrix uncertainties due to change of flight conditions, control system robustness is improved by combining the least squares parameter estimator to estimate time varying uncertainties contained in the control effectiveness matrix. Also, by selecting a suitable gain set by investigating the error dynamics, a uniform trajectory-tracking performance over operational flight envelope of the rotorcraft is ensured without resorting to the conventional gain scheduling method. To evaluate the proposed controller, comparative results between IBSC and Adaptive IBSC are provided in this paper with sequential maneuvers from the ADS-33E-PRF. The proposed method shows improved tracking performance under variations in control effective matrix in the flight simulation. Robust and stable parameter estimation is also guaranteed due to the implementation of the DF-RLS algorithm for the least squares estimator.

A new approach for three-dimensional trajectory tracking control of under-actuated AUVs with model uncertainties

This paper presents a study of precisely three-dimensional (3-D) trajectory tracking controller design for AUV vehicles regarding to highly uncertain nonlinear model features, internal/external disturbances, and roll motion's effect. Firstly, the six degrees of freedom (6-DOF) nonlinear equations of motion are described. Subsequently, a novel control scheme is proposed based on cascade structure, which divides the control problem into dual-coupled problems, called kinematic control and dynamic control. Furthermore, four nonlinear disturbance observers (NDOs) are innovatively constructed to handle the errors in the linearization process and the uncertainties in the 6-DOF AUV model as well. In the kinematic control, Lyapunov's direct method is adopted to compute the desired values for surge velocity, pitch angle, and heading angle to force the trajectory tracking error to an arbitrarily small neighborhood of zero. In the dynamic control, back-stepping sliding mode control is applied in designing attitude and velocity controllers. Finally, strict inspection added with benchmark tests are specific evidence showing the feasibility, effectiveness, disturbances rejection ability, and robustness of the proposed control scheme.

Design of a Model Predictive Trajectory Tracking Controller for Mobile Robot Based on the Event-Triggering Mechanism

A novel model predictive control- (MPC-) based trajectory tracking controller for mobile robot is proposed using the event-triggering mechanism, and the aim is to solve the problem that the MPC optimization problem requires a large amount of online computation and communication resources. This method includes two different event-triggering strategies, namely, the event-triggering based on threshold curve and the event-triggering based on threshold band. The selection of the triggering threshold is achieved by applying the statistical method to the historical data of the trajectory tracking of the mobile robot under the classic MPC method. Simulation and experimental tests illustrate that the proposed approach is able to significantly reduce the computation and communication burdens without affecting the control performance. Furthermore, the experimental results show that compared with the classic MPC-based tracking method, the proposed two event-triggering strategies can reduce 28.1% and 75.7% of the computation load and 0.886 s and 2.385 s communication time.

Adaptive Robust Tracking Control for Hybrid Models of Three-Dimensional Bipedal Robotic Walking Under Uncertainties

Abstract This paper introduces an adaptive robust trajectory tracking controller design to provably realize stable bipedal robotic walking under parametric and unmodeled uncertainties. Deriving such a controller is challenging mainly because of the highly complex bipedal walking dynamics that are hybrid and involve nonlinear, uncontrolled state-triggered jumps. The main contribution of the study is the synthesis of a continuous-phase adaptive robust tracking control law for hybrid models of bipedal robotic walking by incorporating the construction of multiple Lyapunov functions into the control Lyapunov function. The evolution of the Lyapunov function across the state-triggered jumps is explicitly analyzed to construct sufficient conditions that guide the proposed control design for provably guaranteeing the stability and tracking the performance of the hybrid system in the presence of uncertainties. Simulation results on fully actuated bipedal robotic walking validate the effectiveness of the proposed approach in walking stabilization under uncertainties.

Trajectory Tracking Control Design for Nonholonomic Systems with Full-state Constraints

A systematic control design strategy of the trajectory tracking controller is proposed for a class of chained nonholonomic systems with full-state constraints. The barrier Lyapunov function (BLF) with finite-time convergence, the technique of relay switching and the integral backstepping are applied to the development of the controller. The designed control law guarantees that the reference trajectory can be tracked by the system state asymptotically and the state constraints are not violated. The physical models of two mobile robots and simulation results are provided to demonstrate the effectiveness of the proposed control scheme.

Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

This paper deals with the simulation, and design of a trajectory-tracking control law for a physical system under parameter uncertainty modeled by a bond graph. This control strategy is based on the inversion of the system through their causal Input/Output (I/O) path using the principle of bicausality to track the desired trajectory. The proposed control strategy is validated with the use of a simple mechanical mass-spring-damper system. The results show that the bond graph is a very helpful methodology for the design of control laws in the presence of uncertainties. This proposed control can be applied in several applications and can be improved to ensure robust control.

Adaptive finite-time sliding mode control design for finite-time fault-tolerant trajectory tracking of marine vehicles with input saturation

The increasing interest in marine mechatronic systems and their applications has promoted the development of advanced control algorithms for the trajectory control of marine vehicles including ships, surface vehicles, and underwater vehicles. In this paper, the finite-time fault-tolerant trajectory tracking of fully actuated marine vehicles is investigated in the presence of parametric uncertainties, external disturbances, actuator faults, and input saturation. A novel adaptive finite-time sliding mode control scheme is proposed by combining the homogeneous integral sliding mode manifold, the fast terminal sliding mode control, and the adaptation technique. Rigorous theoretical analysis for the practical finite-time stability of the whole closed-loop system is provided. The proposed control scheme can guarantee the position and velocity tracking errors converge to the small region about zero in finite time even in the presence of actuator faults. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance in the same conditions. In addition, the proposed control scheme is structurally simple, model-independent, and continuous with chattering free, which makes it affordable for practical applications. Numerical simulations illustrate the effectiveness and superiority of the proposed control scheme.

Adaptive Kalman Filtering Model Predictive Controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulum

The goal of this manuscript is to formulate a Kalman Filtering Model Predictive Controller (KFMPC) for control of cart position, cart velocity, angular position, and angular velocity of pendulum within a stable range under model uncertainties and disturbances. For designing of the KFMPC, a 4th-order linearized structure of the inverted pendulum system is taken. In this strategy, the conventional model predictive controller is re-formulated with a state estimator based on the Kalman filtering strategy to update the control actions. The approval of the updated control execution of KFMPC is built up by comparative outcome examination with other well-known control techniques. The comparative results obviously expose the better action of the proposed strategy to monitor the system outcomes inside the steady range as far as accuracy, robustness, and stability.

Trajectory tracking controller for unmanned helicopter under environmental disturbances

This paper develops a trajectory tracking control design algorithm to be applied in unmanned aerial vehicles (UAVs). The strategy is simple but effective and it is based on linear algebra theory. The proposed approach reforms the column space of a system of linear equations at each sampling time to ensure the tracking objective when environmental disturbances appear. This new formulation ensures a uniform signal without affecting the error convergence to zero (demonstration available), which is one of the main contributions of this work. A statistical method is used to tune the system control minimizing a pre-defined cost function. In addition, the convergence to zero of the tracking errors is demonstrated in this work. Finally, the controller’s effectiveness is tested through several simulations in realistic test scenarios in the presence of disturbances.

Global Saturated Tracking Control of a Quadcopter With Experimental Validation

This letter addresses the design of a global saturated trajectory tracking controller for a quadcopter in the presence of external disturbances. The proposed control law guarantees that (i) the thrust force generated by the propellers is bounded with respect to the position and linear velocity errors; (ii) the quadcopter globally converges to a neighborhood of a desired smooth trajectory, achieving global practical stability. Disturbance observers are employed to estimate and compensate for external constant and slowly time-varying disturbances, improving the robustness performance of the controller. A projection operator ensures that the estimates do not wind-up and that they remain within a prescribed bound. To validate the efficiency and robustness of the proposed controller, we present and analyze both simulation and experimental results. The proposed global saturated controller is also compared with a standard backstepping-based trajectory tracking controller to demonstrate the merits and improvements of the proposed controller.

Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system.

The state-of-charge (SoC) of an energy storage system (ESS) should be kept in a certain safe range for ensuring its state-of-health (SoH) as well as higher efficiency. This procedure maximizes the power capacity of the ESSs all the times. Furthermore, economic load dispatch (ELD) is implemented to allocate power among various ESSs, with the aim of fully meeting the load demand and reducing the total operating cost. In this research article, a distributed multi-agent consensus based control algorithm is proposed for multiple battery energy storage systems (BESSs), operating in a microgrid (MG), for fulfilling several objectives, including: SoC trajectories tracking control, economic load dispatch, active and reactive power sharing control, and voltage and frequency regulation (using the leader-follower consensus approach). The proposed algorithm considers the hierarchical control structure of the BESSs and the frequency/voltage droop controllers with limited information exchange among the BESSs. It embodies both self and communication time-delays, and achieves its objectives along with offering plug-and-play capability and robustness against communication link failure. Matlab/Simulink platform is used to test and validate the performance of the proposed algorithm under load disturbances through extensive simulations carried out on a modified IEEE 57-bus system. A detailed comparative analysis of the proposed distributed control strategy is carried out with the distributed PI-based conventional control strategy for demonstrating its superior performance.

Trajectory Tracking Control of Robot Manipulators Based on U-Model

A new trajectory tracking control method based on the U-model is proposed to improve the trajectory tacking speed of robot manipulators. The U-model method is introduced to relieve the requirement of the dynamic mathematical model and make the design of trajectory tracking controller of robot manipulators simpler. To further improve the trajectory tacking speed, an improved iterative learning control algorithm is used to suppress the influence of the initial state error with less computation time. Experimental results show that the proposed control method is effective and practical for the trajectory tracking control of robot manipulators, especially with a high real-time requirement.

A Novel Fuzzy Trajectory Tracking Control Design for Wheeled Mobile Robot

In the past decades, wheeled mobile robots (WMRs) are widely applied in various industrial and service fields which include...

Robust controller design for trajectory tracking of autonomous vehicle

In order to improve the stability and fault tolerance of the control system of the autonomous vehicle in the middle and low speed lane changing, a dual loop weighted trajectory tracking robust control system is designed. Firstly, the lateral displacement transfer function and yaw angle transfer function are derived by combining the mathematical model of trajectory planning and vehicle motion, and the proportion integral differential (PID) control parameters are calculated by mathematical derivation and transfer function reduction. Then, the influence of weighting coefficient on system stability and its determination method are studied by simulation. The results show that the dual-loop weighted control is feasible and effective, and it could provide a good fault tolerance, good control ability, good tracking effect, and small lateral displacement error and yaw angular velocity error for lane changing conditions in the medium and low speed.

Robust controller design for trajectory tracking of autonomous vehicle

In order to improve the stability and fault tolerance of the control system of the autonomous vehicle in the middle and low speed lane changing, a dual loop weighted trajectory tracking robust control system is designed. Firstly, the lateral displacement transfer function and yaw angle transfer function are derived by combining the mathematical model of trajectory planning and vehicle motion, and the proportion integral differential (PID) control parameters are calculated by mathematical derivation and transfer function reduction. Then, the influence of weighting coefficient on system stability and its determination method are studied by simulation. The results show that the dual-loop weighted control is feasible and effective, and it could provide a good fault tolerance, good control ability, good tracking effect, and small lateral displacement error and yaw angular velocity error for lane changing conditions in the medium and low speed.