Explore the vast range of titles available.

The design of output constrained control system for unmanned aerial vehicles deployed in confined areas is an important issue in practice and not taken into account in many autopilot systems. In this study, the authors address a neural networks-based adaptive trajectory tracking control algorithm for multi-rotors systems in the presence of various uncertainties in their dynamics. Given any sufficient smooth and bounded reference trajectory input, the proposed algorithm achieves that (i) the system output (Euclidean position) tracking error converges to a neighbourhood of zero and furthermore (ii) the system output remains uniformly in a prescribed set. Instead of element-wise estimation, a norm estimation approach of unknown weight vectors is incorporated into the control system design to relieve the onboard computation burden. The convergence property of the closed-loop system subject to output constraint is analysed via a symmetric barrier Lyapunov function augmented with several quadratic terms. Simulation results are demonstrated on a quadrotor model to validate the effectiveness of the proposed algorithm.

In this paper we study the convergence of an adaptive finite element method for optimal control problems with integral control constraint. For discretization, we use piecewise constant discretization for the control and continuous piecewise linear discretization for the state and the co-state. The contraction, between two consecutive loops, is proved. Additionally, we find the adaptive finite element method has the optimal convergence rate. In the end, we give some examples to support our theoretical analysis.

Cable-driven parallel robots (CDPRs) are a class of parallel robots where the cables are used as the arms of the robot in a redundant kinematic architecture. Such an architecture allows manipulation in a considerably large working area and also operation at high speed and acceleration. However, as cables only support tensile force, the controller should generate positive control effort, which leads to a complex constrained control problem. The positive tension distribution in redundant CDPR is generally maintained via redundancy resolution (RR) methods, which are originally optimization-based. The RR methods are prone to kinematic uncertainty, which brings complexity to the control apart from the original effects of kinematic uncertainty. The constrained control of CDPRs gets more complex in the faulty mode of the actuators. The combined effects of faulty actuators along with the kinematic uncertainty limit the application of RR in practice. To address this, a robust fault-tolerant constrained control scheme is proposed to generate an unidirectional control signal for maintaining positive tension in cables in the presence of actuator fault and model uncertainties, taking advantage of an adaptive finite-time sliding mode control along with a nonlinear adaptive observer. The proposed observer estimates the model uncertainties and the actuator fault, while the controller ensures the convergence of the state variables and compensates for the observer estimation error. The H ∞ asymptotic stability of the proposed observer is ensured through sufficient conditions using linear matrix inequality. Furthermore, Lyapunov’s second method is employed to prove the finite-time stability of the system. The performance of the proposed scheme is experimentally validated using a planar CDPR in the presence of actuator fault and model uncertainties.

Three decades have passed since milestone publications by several industrialists spawned a flurry of research and industrial / commercial activities on model predictive control (MPC). This article reviews major developments and achievements during the three decades and attempts to put a perspective on them. The first decade is characterized by the fast-growing industrial adoption of the technology, primarily in the refining and petrochemical sectors, which sparked much interest and also confusion among the academicians. The second decade saw a number of significant advances in understanding the MPC from a control theoretician’s viewpoint, which included state-space interpretations / formulations and stability proofs. These theoretical triumphs contributed to the makings of the second generation of commercial software, which was significantly enhanced in generality and rigor. The third decade’s main focus has been on the development of “fast MPC,” a term chosen to collectively describe the various efforts to bring orders-of-magnitude improvement in the efficiency of the on-line computation so that the technology can be applied to systems requiring very fast sampling rates. Throughout the three decades of the development, theory and practice supported each other quite effectively, a primary reason for the fast and steady rise of the technology.

Since many practical systems can be modeled as nonlinear systems with time-varying powers, its control problem is a new issue in control theory research. In this paper the output-constrained control problem for a class of nonlinear systems with time-varying power is studied. Firstly, due to the constraint on system output, we construct not a quadratic Lyapunov function, but a log -type barrier Lyapunov function (BLF). Secondly, by skillfully combining the adding a power integrator technique with the log -type BLF, we can develop an output-constrained controller to ensure the boundedness of closed-loop system signals and the convergence of system states. Finally, by a simulation verify the effectiveness of the controller.

In this paper, a novel robust fractional-order sliding mode (FOSM)-based state constrained control scheme is designed for uncertain quadrotor UAVs (QUAVs). Model uncertainties and wind gust disturbances are taken into consideration. Under the presented framework, the overall QUAV system is decoupled into translational subsystem and rotational subsystem. These two subsystems are connected to each other through common attitude extraction algorithms. For translational subsystem, the robust state variables constrained controller is designed to ensure the position state variables within the given time-varying constraints. For the rotational subsystem, a new robust FOSM controller is constructed to track the desired attitudes with better performances. Finally, the system is proved to be asymptotically stable, and both simulation and experiment results are conducted to validate the feasibility and effectiveness of the proposed control scheme.

The problem of designing a nonlinear control such that the control magnitude and settling time of the closed-loop system regionally satisfy prescribed bounds is considered. Such a control is termed a regional, magnitude constrained, time constrained control. Using common Lyapunov functions, sufficient conditions are derived to solve the design problem and a control synthesis procedure involving a sequence of linear matrix inequalities is presented. The conditions and procedure are applied to three examples including single-input and two-input relative orbital motion control.

In this paper, we propose a distributed prescribed performance formation tracking control method for unknown Euler–Lagrange systems subject to input amplitude constraints. We address the challenge of maintaining formation tracking within predefined performance bounds when the agents’ inputs are subject to saturation. This is achieved by designing a distributed virtual velocity reference modification mechanism, which modifies the desired velocity reference of each agent whenever saturation occurs. We establish sufficient feasibility conditions for the input constraints that ensure prescribed performance formation tracking of the desired trajectory and guarantee the boundedness of all closed-loop signals. Simulations on a team of underwater vehicles validate the method’s effectiveness.

The paper extends the earlier work entitled “Making the PI and PID Controller Tuning Inspired by Ziegler and Nichols Precise and Reliable”, to higher-order controllers and a broader range of experiments. The original series PI and PID controllers, based on automatic reset calculated by filtered controller outputs, are now augmented by higher-order output derivatives. This increases the number of degrees of freedom that can be used to modify the resulting dynamics, accelerates transient responses, and increases robustness to unmodeled dynamics and uncertainties. The fourth order noise attenuation filter used in the original work allows for the addition of an acceleration feedback signal, thus resulting in a series PIDA controller or even a jerk feedback that leads to a PIDAJ series controller. Such a design can further use the original process and filter approximation of the step responses through the integral-plus-dead-time (IPDT) model, while allowing experimentation with disturbance and setpoint step responses of the series PI, PID, PIDA and PIDAJ controllers, and thus, evaluating the role of output derivatives and noise attenuation from a broader perspective. All controllers considered are tuned using the Multiple Real Dominant Pole (MRDP) method, which is complemented by a factorization of the controller transfer functions to achieve the smallest possible time constant for automatic reset. The smallest time constant is chosen to improve the constrained transient response of the considered controller types. The obtained excellent performance and robustness allow the proposed controllers to be applied to a wider range of systems with dominant first-order dynamics. The proposed design is illustrated on a real-time speed control of a stable direct-current (DC) motor, which is approximated (together with a noise attenuation filter) by an IPDT model. The transient responses obtained are nearly time-optimal, with control signal limitations active for most setpoint step responses. Four controllers with different degrees of derivative with generalized automatic reset were used for comparison. It was found that controllers with higher-order derivatives may significantly improve the disturbance performance and virtually eliminate overshoots in the setpoint step responses in constrained velocity control.