Narrow Results

This paper focuses on trajectory tracking, robustness and stabilization of a golf swing robot which has been recently developed to simulate the ultra-high-speed swing motions of a golfer. The proposed control strategies are based on the Lyapunov stability theory and include Backstepping and Sliding-Mode Control based techniques. To attenuate the chattering phenomena caused by a discontinuous switching function and improve the dynamic response of the manipulator, a fuzzy system is used in this research; a Backstepping Sliding-Mode Controller (BSMC), a Backstepping Fuzzy Sliding-Mode Controller (BFSMC) and a Super-twisting Backstepping Sliding-Mode Controller (STBSMC) are used to evaluate the proposed hybrid controller’s BFSMC performance. The Lyapunov stability theory is used to guarantee the stability of the proposed closed-loop robot technique. Numerical simulations show the effectiveness of the proposed strategy based on the fuzzy logic mechanism under different disturbances and uncertainties.

The last decades proved that policymaking without considering uncertainty is impracticable. In an environment of uncertainty, policymakers have doubts about the policy models they routinely use. This paper focuses specifically on the situation where uncertainty on the financial side of the economy leads to misspecification in the policy model. We describe a coherent strategy for policymakers who are averse to model misspecification and analyze optimal policy design in the face of Knightian uncertainty. To do so, we augment a financial dynamic stochastic general equilibrium model with model misspecification in a simple minimax framework where the central bank plays a zero-sum game versus a hypothetical evil agent. The policy is tailored to insure against the worst-case outcomes. We show that model ambiguity on the financial side requires a passive monetary policy stance. However, if the uncertainty originates from the supply side of the economy, an aggressive response of interest rate is required. We also show the impact of an additional macroprudential tool on the dynamics of the economy.

This paper studies a problem of dynamic pricing faced by a retailer with limited inventory, uncertain about the demand rate model, aiming to maximize expected discounted revenue over an infinite time horizon. The retailer doubts his demand model which is generated by historical data and views it as an approximation. Uncertainty in the demand rate model is represented by a notion of generalized relative entropy process, and the robust pricing problem is formulated as a two-player zero-sum stochastic differential game. The pricing policy is obtained through the Hamilton-Jacobi-Isaacs (HJI) equation. The existence and uniqueness of the solution of the HJI equation is shown and a verification theorem is proved to show that the solution of the HJI equation is indeed the value function of the pricing problem. The results are illustrated by an example with exponential nominal demand rate.

Autonomous helicopter stabilization in the presence of a wind disturbance is presented. A controller is designed based on the nonlinear adaptive output regulation and robust stabilization of a chain of integrators by a saturated feedback to stabilize the position and velocity of a helicopter. The controller is able to adaptively estimate the wind disturbance whose measurements are not made available. In addition to robustness against the external disturbance input the control design is carried out to handle helicopter parameter uncertainties. The cost of the robustly stabilizing control strategy is the challenge to tune 13 controller parameters for a desired output response. Particle swarm optimization (PSO), a metaheuristic optimization algorithm is applied to automate the tuning process. Simulation results demonstrate the effectiveness of the proposed control and tuning methods in the robust stabilization of the helicopter motion.

In this paper the regulation problem of linear discrete-time systems with uncertain parameters under state and control constraints is studied. In the first part of the paper, two theorems concerning necessary and sufficient conditions for the existence of a solution to this problem are presented. Due to the constructive form of the proof of these theorems, these results can be used to the development of techniques for the derivation of a control law transferring to the origin any state belonging to a given set of initial states while respecting the state and control constraints.

A two-loop control has been designed for a boost converter. An internal sliding-mode control loop forces the converter inductor current to track the reference established by H_∞ control of the output voltage in an outer loop. The outer H_∞ controller is designed through loop shaping concepts. A practical design approach that aims at systematizing the procedure for the selection of inner sliding mode control parameters is also presented. The closed loop characteristics of a typical low-power boost converter with the proposed dual loop controller implemented in the actual switched model is validated through computer simulation. The proposed controller is found to be superior due to its low distortion property, good regulating performance and insensitivity to load variations. Finally, the validity and effectiveness of the control schemes are verified through hardware experiments.

This paper investigates the synchronization of coupled chaotic systems using techniques from the theory of robust control based on Linear Matrix Inequalities. To deal with the synchronization of a class of Lur'e discrete time systems, a project methodology is proposed. A laboratory setup based on Chua's oscillator circuit is used to demonstrate the main ideas of the paper in the context of the problem of information transmission.

This paper deals with the problems of stability analysis and control synthesis with performance for the master-slave synchronization of Lur'e systems using a time-delay feedback control. The proposed approach consists in obtaining a new improved robust stability criteria as well as a control law based on linear matrix inequalities (LMIs) via discretized Lyapunov–Krasovskii functional combined with an alternative strategy based on the introduction of slack variables to allow the decoupling of the system matrices from the Lyapunov matrices. Using the problem of synchronizing coupled Chua's circuits, two examples are presented to illustrate the effectiveness of the proposed methodology.

The stabilization of nonlinear systems that exhibit chaotic behavior is presented using notch-filter output feedback control. The effect of constant disturbance input and/or parametric uncertainty on the systems' performance is studied for a class of nonlinear systems where bifurcation analysis is used to illustrate the period-doubling route to chaos. The motivation for using the notch-filter in the feedback is to selectively damp-out portions of the closed-loop power spectrum, thus truncating period-doubling. Double-notch-filter feedback is introduced as a regulation scheme to bring the chaotic system to a steady state. The effect of using the fixed-parameters feedback on the equilibrium points is carefully studied, and a robust numerical parameter-tuning method is presented. The efficiency of this method is verified via simulations applied to a third-order uncertain nonlinear system that has typical applications in power generation and voltage control. A comparative study with a model-based recursive backstepping controller is carried out to highlight the advantages and limitations of the proposed control system.

A method for finding reduced-order approximations of turbulent flow models is presented. The method preserves bounds on the production of turbulent energy in the sense of the norm of perturbations from a notional laminar profile. This is achieved by decomposing the Navier–Stokes system into a feedback arrangement between the linearized system and the remaining, normally neglected, nonlinear part. The linear system is reduced using a method similar to balanced truncation, but preserving bounds on the supply rate. The method involves balancing two algebraic Riccati equations. The bounds are then used to derive bounds on the turbulent energy production. An example of the application of the procedure to flow through a long straight pipe is presented. Comparison shows that the new method approximates the supply rate at least as well as, or better than, canonical balanced truncation.

Robust control of chaotic vibration in composite plate in the presence of noise using sliding mode control methodology is considered in this paper. The composite plate system has a combination of linear, quadratic and cubic stiffness terms. Robustness of the controller is analyzed with reference to the parametric variations of the system and external disturbances due to noise and compared with Pyragas control method. The composite plate considered is a six-layered rectangular antisymmetric cross-ply plate with immovable edges. The plate is assumed to be viscously damped and harmonically excited.

We first investigate the fundamental properties of the mechanical system as related to the control design. Then a new robust control is proposed for mechanical systems with fuzzy uncertainty. Fuzzy set theory is used to describe the uncertainty in the mechanical system. The desirable system performance is deterministic. The proposed control is deterministic and is not the usual if-then rules-based. The resulting controlled system is uniformly bounded and uniformly ultimately bounded proved via the Lyapunov minimax approach. The resulting control design is systematic and is able to render the deterministic performance. A mechanical system is chosen for demonstration.

A robust global fuzzy sliding mode controller is designed in this paper for the synchronization of non-linear systems with control input non-linearities (CIN) and uncertainties. A consistent global fuzzy sliding mode control (GFSMC) law is developed, which guarantees the suppression of the reaching phase and the presence of the sliding phase from the initial time. Chattering phenomenon, which is characteristic of customary sliding mode control (SMC), avoided by the on-line fuzzy regulation of the sliding surface in the controller, when the system is subject to disturbances and CIN. Finite-time boundedness (FTB) properties are designed with adequate conditions, which are entrenched in terms of linear matrix inequalities (LMIs) with the help of cost and Lyapunov functions. Numerical simulations for the synchronization problem of the chaotic modified Colpitt’s system and Duffing system clearly show the good performance of the proposed control scheme. The present work provides a regular procedure to design GFSMC for a class of non-linear systems with CIN.

In this paper, we deal with the problem of how to achieve stability for a complex system in which the subsystems are stable, but the non-linear interaction between the subsystems may cause instability. We assume that the uncertainties with which we know the parameters of the system are bounded, but that these bounds are not known. For such systems, we propose a new control method: a decentralized robust control with fuzzy estimation of the bounds of uncertainties, implemented as a combination of conventional and fuzzy controllers. The use of fuzzy control is motivated by the equivalent dynamic fuzzy state-space model of the system consisting of interconnected uncertain subsystems.

We formulate the portfolio choice problem as a robust control problem under uncertainty or ambiguity aversion. By considering a stochastic investment opportunity set, we derive optimal robust portfolio rules in the cases of one and two risky assets. With two risky assets and ambiguity structure determined by economy-wide factors, we show that the robust portfolio rule could lead to an increase in the total holdings of risky assets as compared to the holdings under the Merton rule, which is the standard risk aversion case. This result goes against the general belief that uncertainty aversion and robust control methods lead to conservative behavior. We also show that the investor is more likely to increase the holdings of the asset for which there is no ambiguity, and reduce the holdings of the asset for which there is ambiguity, a result that might provide an explanation for the home bias puzzle.

We investigate an impulse control differential game arising in a problem of option pricing in mathematical finance. In a previous paper, it was shown that its Value function in ℝ³ could be described as a pair of functions affine in one of the variables, joined on a 2D manifold. Depending on the regions of the state space, this manifold is either a dispersal one, an equivocal one or a 2D focal manifold. A pair of PDE's were derived for the focal part. Here we show that irrespective of the nature of this manifold, it has to satisfy this same set of PDE's.

Lunar-based equipment undertakes the task of movement and transportation in the construction of unmanned lunar base. In the process of moving, the mechanical legs of the equipment are influenced by the lunar soil with special mechanical properties. In order to avoid these uncertainties caused by the lunar soil and other lunar environmental conditions affecting the safety during the mission, a new robust control method with the form of sectionalized expression is proposed based on the dynamic model of the leg-soil system. Lyapunov second method is introduced to demonstrate that the proposed control method can maintain the stability of the leg-soil system successfully. In order to clarify the contact force in the dynamics model, CAS-1 lunar soil simulant that can accurately simulate real lunar soil is used in the calibration test to obtain the precise mechanical parameters. Simulation and experiment are also carried out to verify the proposed control method and the traditional control methods are introduced to make a comparison. Both the simulation and experiment results show that the proposed control method has a better control effect than traditional methods. The proposed method improves the accuracy by an average of 75.7% and 55.9% compared to the traditional methods and the error is limited to 0.2%. By maintaining the stability and accuracy of the leg-soil system, the stability of the lunar-based equipment is improved when performing construction tasks. This study lays the foundation for the construction of unmanned lunar base in advance.

Stability analysis is one of the main issues in the research area of biped robots with point feet. This article develops stability analysis and robust control of a planar biped robot with point feet with one degree of underactuation. A stability analysis is presented for the bipedal motion comprising single support and impact phases by using Poincaré map for nonlinear systems. Then, the stability conditions of periodic orbits are derived and stable gait pattern is determined using an optimization process. Thereafter, a robust sliding mode control with a time-invariant feedback is proposed to track stable gait in the presence of parameter uncertainties of the biped. Proposed approach is carried out for two types of bipeds, namely, a normal model and a balanced model in which the biped center of mass located at the hip using a novel model. Energy efficiency of biped is investigated for both models. Moreover, the stability of biped motion is studied in the presence of an unexpected stair. Simulation results show the biped motion quickly converges to cyclic motion during the first gait in both models.

This paper presents a control scheme for the humanoid robot TEO’s elbow joint based on a novel tuning method for fractional-order PD and PI controllers. Due to the graphical nature of the proposed method, a few basic operations are enough to tune the controllers, offering very competitive results compared to classic methods. The experiments show a robust performance of the system to mass changes at the tip of the humanoid arm.

This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-space model, as well as because of underactuation, the control problem of these robots is nontrivial. The dynamic model of the brachiation robots undergoes first approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the Jacobian matrices of the brachiation robots’ state-space model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the brachiation robots, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the brachiation robots, under moderate variations of the control inputs.