Narrow Results

In the past decade, there has been much interest in operating quadrotors in uncertain and cluttered environments due to their simplicity. Executing precise agile quadrotor flight maneuvers is an important open research problem for navigating in such environment. Collisions can occur if actuator constraints are not considered in the trajectory tracker design. This paper presents a cascade nonlinear constrained control approach (CNCCA) for trajectory tracking with explicit consideration of actuator constraints, where the output signal of the position controller is converted into the desired command of the attitude controller. The proposed position control loop is shown to be stable and bounded, satisfying the total thrust limits. The proposed attitude tracking control loop is designed as a saturated control law based on a modified geometric controller in SO(3) space. A proof of its stability is provided. The simulation results also show good tracking performance of the proposed approach.

The theory of synergetic control was introduced in a power electronics context in a previous paper. In this paper we review the theory, then we focus on a comparison with the sliding mode approach. Common elements and main differences are underlined and illustrated through a comparative simulation example. The main advantages of synergetic control are that it is well-suited for digital implementation, it gives constant switching frequency operation, and it gives better control of the off-manifold dynamics. Finally, simulation and experimental results under transient conditions are compared. Advanced control laws with adaptation are presented and discussed to show how to better exploit the features of the synergetic control. The example used throughout the paper is the control of a boost converter operating in continuous conduction mode.

Beam halo-chaos in high-current accelerators has become a key concerned issue because it can cause excessive radioactivity from the accelerators therefore significantly limits their applications in industry, medicine, and national defense. This article reviews the complexity of accelerator driven clean nuclear power system (ADS) as well as the associate physical mechanism for beam halo-chaos formation in high-intensity proton linear accelerator. Notably, some general engineering methods for chaos control have been developed in recent years, but they are generally unsuccessful for beam halo-chaos suppression due to many technical constraints. In this article, some of these technical problems are addressed. Particles-in-Cell (PIC) simulations are described, for exploring the nature of beam halo-chaos formation. Some efficient nonlinear control methods, including wavelet function feedback control, are reported for beam halo-chaos suppression. PIC simulations show that after control is applied to the initial proton beam with water bag or full Gauss distributions, the beam halo strength factor is quickly reduced to zero, and other statistical physical quantities of beam halo-chaos are also doubly reduced. These performed PIC simulation results demonstrate that the developed methods are very effective for halo-chaos suppression. Potential applications of the beam halo-chaos control methods are finally discussed.

This paper describes some numerical techniques to control unstable periodic orbits embedded in chaotic attractors of a particular discontinuous mechanical system. The control method is a continuous time delayed feedback that modifies the stability of the orbit but does not affect the orbit itself.

This paper presents a neural network-based digital redesign approach for digital control of continuous-time chaotic systems with unknown structures and parameters. Important features of the method are that: (i) it generalizes the existing optimal linearization approach for the class of state-space models which are nonlinear in the state but linear in the input, to models which are nonlinear in both the state and the input; (ii) it develops a neural network-based universal optimal linear state-space model for unknown chaotic systems; (iii) it develops an anti-digital redesign approach for indirectly estimating an analog control law from a fast-rate digital control law without utilizing the analog models. The estimated analog control law is then converted to a slow-rate digital control law via the prediction-based digital redesign method; (iv) it develops a linear time-varying piecewise-constant low-gain tracker which can be implemented using microprocessors. Illustrative examples are presented to demonstrate the effectiveness of the proposed methodology.

We present an application of equation-free computation to the coarse-grained feedback linearization problem of nonlinear systems described by microscopic/stochastic simulators. Feedback linearization with pole placement requires the solution of a functional equation involving the macroscopic (coarse-grained) system model. In the absence of such a closed-form model, short, appropriately initialized bursts of microscopic simulation are designed and performed, and their results used to estimate on demand the quantities required for the numerical solution of the (explicitly unavailable) functional equation. Our illustrative example is a kinetic Monte Carlo realization of a simplified heterogeneous catalytic reaction scheme.

In this paper, a scalar sign function-based digital design methodology is presented to develop a digital tracking controller for the continuous-time chaotic systems with absolute value state constraints. A scalar sign function, which is the counterpart of the well-known matrix sign function, is utilized to approximately represent the absolute value state term by a rational function. As a result, the original state constrained nonsmooth nonlinear system becomes a smooth nonlinear system having rational nonlinear terms. Then, an optimal linearization technique is applied to the afore-mentioned nonlinear system for finding an optimal linearization model, which has the exact dynamics of the original nonlinear system at any operating point of interest with minimal modeling error in the vicinity of the operating point on the trajectory. To overcome the effect of modeling errors and to quickly track the desired reference signals, a high-gain optimal analog tracker is designed for the obtained linear model. For practical implementation of the high-gain analog tracker, the prediction-based digital redesign technique is utilized to obtain a low-gain digital tracker for digital control of the sampled-data nonlinear system with constrained states. Chua's chaotic circuits are used to demonstrate the effectiveness of the proposed approach.

In this paper, a class of fuzzy controllers is considered. The controllers are constructed by applying product-max-COA(Center Of Area) inference method. The membership functions of the antecedence and the consequence are triangular and singelton in shape, respectively. The class of fuzzy controllers can be expressed by an explicit form, i.e. the sum of a linear function and some nonlinear terms. The explicit form of the class of controllers is generalized for multiple inputs. Therefore, by the use of the explicit form, the analysis of the fuzzy control system can be performed with the use of nonlinear control theory.

The effective force testing is a promising seismic testing method for evaluating the structural dynamic response to earthquakes for conciseness and efficiency. However, two challenging loading issues are associated with this method, i.e. the natural velocity feedback (NVF) and nonlinearities related to the interaction between the loading system and specimen, thereby hindering its development and extensive applications. To address these issues, this study proposes a dynamic force loading strategy using a hybrid algorithm with linear compensation for NVF and model reference adaptive control via the minimal control synthesis (MCS) method. Online identification of linear compensation gain in preliminary tests is conceived based on the gradient descent method. A series of numerical simulations on a nonlinear loading system model with linear/trilinear single/two degree(s)-of-freedom specimens are conducted using five loading strategies, including linear and nonlinear compensations and MCS method. Comparative studies show that the proposed method and nonlinear compensation strategy outperform the other three methods, and sometimes the proposed method performs best. In summary, the proposed method is promising because of its accuracy and robustness as well as its ease of implementation and cost-effectiveness.

The trajectory linearization control (TLC) was applied to design an autonomous nonlinear trajectory tracking controller for a novel rehabilitation exoskeleton shoulder joint in this paper. TLC is a relatively new control method which was applied in aircraft and mobile robot, which had good performance on real-time trajectory tracking, anti-jamming and universality. As a new application in the exoskeleton shoulder joint controller design, the controller in this research contained two loops that separately based on the inverse kinematics and pseudo-inverse dynamics models of the exoskeleton shoulder. Two PI controllers as the error regulator can reduce the tracking error. The position and angular velocity error feedback were employed to constitute the closed-loops. Since the controller was based on model and linearization, it can adapt to both linear and nonlinear control processes. The simulation of three different trajectories for single degree of freedom movement of shoulder joint (shoulder flexion and extension, abduction and extension), and the movement of both the two degrees were given. The simulation results showed that the TLC controller can follow the exoskeleton shoulder trajectory steadily and accurately.

A proportional controller is compared to a nonlinear backstepping controller with four different grasps for a dexterous anthropomorphic hand. A bioinspired grasp-dependent control scheme which autonomously modulates the grip force using wrist velocity feedback to prevent grasped object slip is also introduced. Four different grasp types are evaluated to illustrate how the wrist velocity feedback architecture must differ depending upon the manner in which objects are grasped. The backstepping controller can successfully increase grip force with wrist velocity in a robustly stable bioinspired fashion. Experimental results show that the developed backstepping controller improves the position tracking abilities for multiple periodic inputs, as well as reduces step input overshoot. The slip prevention capabilities of the backstepping controller are also demonstrated and compared to the proportional control scheme. Results of the slip prevention experiments show that both the grasp type and manipulator orientation with respect to gravity are significant factors in the performance of the controllers. The backstepping control scheme significantly improves slip prevention of grasped objects for multiple grasps and in two different orientations with respect to gravity.

Owing to their nonlinear structures and dynamics, bipedal walking robots are commonly used as appropriate case studies for nonlinear modeling and control. In this study, the dynamics of a point-feet 4-link biped robot having asymmetric structure is studied. This asymmetry appears on the robot’s legs such that one leg of the robot does have an active knee while the other is knee-less. In this way, the style and analysis of each step depends on which leg is the stance leg. Although the stable steady state behavior of the system is purely periodic, the gait cycle does consist of two sequential steps. Since each step includes a continuous phase followed by an impact phase, hence, we need to model the system as a multiphase (4-phase) hybrid system. The main purpose of this research is to find stable gating pattern and employ appropriate controller to make sure that the gating is accomplished in an asymptotically stable manner. A combination of feedback linearization and finite-time controllers is used to control the walking posture, and the stability of the whole behavior is investigated by analysis of a one-dimensional Poincaré map. Simulation results successfully support the modeling and control approach.

Proper functioning of the shoulder, elbow, and wrist movements play a vital role in the performance of essential daily activities. To assist physically disabled people with impaired upper-limb function, we have been developing an exoskeleton robot (ExoRob) to rehabilitate and to ease upper limb motion. The proposed ExoRob will be comprised of seven degrees of freedom (DOFs) to enable natural movements of the human upper-limb. This paper focuses on the kinematic and dynamic modeling of the proposed ExoRob that corresponds to human upper-limbs. For this purpose, a nonlinear computed torque control technique was employed. In simulations, trajectory tracking corresponding to typical rehabilitation exercises were carried out to evaluate the performances of the developed model and controller. For the experimental part, only 3DOFs (elbow, wrist flexion/extension, wrist abduction/adduction) were considered. Simulated and experimental results show that the controller was able to maneuver the proposed ExoRob efficiently in order to track the desired trajectories, which in this case consisted in passive arm movements. Such movements are widely used in therapy and were performed efficiently with the developed ExoRob and the controller.

Recently, applying control theory to regulate the intracellular mRNA level was introduced as a new direction for gene regulation. However, the high nonlinearity in the gene regulatory networks imposes significant challenges in control design. As a well understood benchmark example, the GAL regulatory network in S. cerevisiae was recently proposed as a test-bed system for validating theoretical control algorithms in cellular systems. A simple proportional feedback control approach was previously proposed for regulating the intracellular mRNA level in the GAL network, however, there were still limitations with its use to control the nonlinear GAL network. To improve the performance and effectiveness, this paper proposes an advanced nonlinear control strategy. The reduced mathematical model for the GAL network is reorganized into a nonlinear affine system. Then, a partial feedback linearization control approach was employed to regulate the concentration of a protein at a desired level. For validating the control approach in experimental studies, we choose Gal1p as a measurable output, instead of GAL1 mRNA used in the previous study. Simulation results demonstrate that this control approach can shorten the convergence time between states comparing with the proportional feedback control.

An optimal control problem for a drift-free controllable system on the Lie group SO(4) is discussed and some of its dynamical and geometrical properties are pointed out.

Nonlinear behavior is present in the operating conditions of many mechanical systems, especially if nonsmall oscillations are considered. In these cases, in order to improve vibration control performance, a common engineering practice is to design the control system on a set of linearized models, for given operating conditions. The well-known gain-scheduling technique allows the parameters of the control law to be changed according to the current working condition, also increasing system stability. However, more recently new control logics directly applicable to the systems in nonlinear form have been developed. The aim of this paper is to study, both numerically and experimentally, the dynamic of a mechanical system (a 3-link flexible manipulator) comparing the performance of a fully nonlinear control (the sliding-mode control) and a standard linearized approach.

This paper presents a dynamic image-based visual servoing (IBVS) control law for a quadrotor unmanned aerial vehicle (UAV) equipped with a single fixed on-board camera. The motion control problem is to regulate the relative position and yaw of the vehicle to a moving planar target located within the camera’s field of view. The control law is termed dynamic as it’s based on the dynamics of the vehicle. To simplify the kinematics and dynamics, the control law relies on the notion of a virtual camera and image moments as visual features. The convergence of the closed-loop is proven to be globally asymptotically stable for a horizontal target. In the case of nonhorizontal targets, we modify the control using a homography decomposition. Experimental and simulation results demonstrate the control law’s performance.

This paper proposes a novel nonlinear feedback control strategy for velocity and attitude control of fixed wing aircrafts. The key feature of the control design strategy is the introduction of a virtual control input in order to deal with the underactuation property of such vehicles and to indirectly control the orientation of the aircraft. As such, the proposed strategy consists of three control loops each realizing a specific task. Simulations are carried out by using the jetstream-3102 aircraft in a real-time virtual Simulation Platform for the development of Aircraft Control Systems (SP-ACS). The proposed approach of control is model-based for which we have introduces an identification part before test and validation. We use the Total Least Squares Estimation (TLSE) technique to identify the aerodynamic parameters, which are unknown, variable and classified. Each aerodynamic coefficient is defined as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting law. Simulation results on Jetstream-3102 aircraft show very good performance in terms of convergence towards the desired reference trajectories and in terms of robustness with respect to modeling uncertainties.

For aerial manipulators, a steady flight must be guaranteed to perform safe interaction with the surrounding environment. This paper focuses on the development of a position control algorithm for an aerial manipulator system (AMS). The position control algorithm is based on the Immersion and Invariance (I&I) theory. The proposed controller maintains the position of the aerial manipulator at the desired point under external and internal disturbances. The control architecture uses a Visual-SLAM technique using on-board sensors for AMS positioning. A series of outdoor experimental tests are performed to demonstrate the effectiveness of the proposed control strategy.

In this paper, a novel robust backstepping-based fault-tolerant control is designed, implemented and validated experimentally on a quadrotor unmanned aerial vehicle testbed under actuator fault conditions for tracking control. Backstepping is known as a robust method to maintain system performance and keep it insensitive to disturbances. The proposed nonlinear controller is mainly based on the advanced robust backstepping method to solve the system uncertainties caused by disturbances and actuator faults, which appear in the motor part of the system and are compensated without diagnostics or fault identification. The various parameters of the proposed approach are optimized using the particle swarm optimization (PSO) method. Owing to the minimized control effort to accommodate uncertainties compared to the conventional backstepping, the proposed approach can still maintain the system performance when severer faults occur. The proposed approach is validated, first, in a simulation using the nonlinear model of the quadrotor, then experimentally, using the Quanser 3DOF Hover quadrotor. Both theoretical and experimental analyses have demonstrated that the effectiveness of the proposed improved backstepping fault-tolerant control strategies faces significant loss of actuator efficiency.