Hongzhe Jin

Adaptive Control of a Gyroscopically Stabilized Pendulum and Its Application to a Single-Wheel Pendulum Robot

This paper presents an adaptive decoupling control strategy for a gyroscopically stabilized pendulum. In the proposed model, the gyro moment acts directly on the pivot of the pendulum, the magnitude of which is restricted by gyroscopic precession. A decoupling algorithm based on virtual control is proposed to regulate the upright posture of the pendulum through gyroscopic precession. Virtual control is considered a control torque that acts on the pivot of the pendulum; it forms nonlinear mapping along with the precession command. Consequently, gyroscopic precession matches the stability condition of the pendulum well. In the control design, an adaptive disturbance estimation method based on a smooth saturation function is proposed to avoid the adverse effects of parametric uncertainties, mechanical vibrations, and system nonlinearities. Accurate estimation of unstructured disturbances is easily achieved by adaptively tuning the weight coefficient of the saturation function. The results of stability analysis, simulations, and experiments show the validity of the proposed pendulum model and adaptive decoupling control scheme.

Design and evaluation of a parallel-series elastic actuator for lower limb exoskeletons

This paper presented a novel compliant actuator used for lower limb exoskeletons. The compliant joint consists of a series elastic actuator (SEA) and parallel elastic (PE) unit. SEA has various advantages as the actuator of assistive exoskeletons, such as low output impedance, impact absorption, precise force control and high stability. We designed and fabricated a novel SEA as the primary joint actuator which is compact, adjustable and low-cost. Meanwhile an additional elastic unit is installed in parallel with the SEA to improve energy utilization by storing and releasing energy during motion cycles. An adaptive stable controller is designed to realize the joint following motion to a virtual limb. The algorithm can identify and compensate the undetermined contact stiffness between the joint output and the virtual limb. Finally, the performance of the actuator is evaluated through motion tracking and energy-conservation experiments. Preliminary results indicate the validity of the design and imply its potential usage in lower limb exoskeletons.

Chaotic CPG Based Locomotion Control for Modular Self-reconfigurable Robot

The most important feature of Modular Self-reconfigurable Robot (MSRR) is the adaption to complex environments and changeable tasks. A critical difficulty is that the operator should regulate a large number of control parameters of modules. In this paper, a novel locomotion control model based on chaotic Central Pattern Generator (CPG) is proposed. The chaotic CPG could produce various rhythm signals or chaotic signal only by changing one parameter. Utilizing this characteristic, a unified control model capable of switching variable locomotion patterns or generating chaotic motion for modular self-reconfigurable robot is presented. This model makes MSRR exhibit environmental adaptability. The efficiency of the control model is verified through simulation and experiment of UBot MSRR platform.

Automatic Locomotion Generation for a UBot Modular Robot - Towards Both High-speed and Multiple Patterns

Modular self-reconfigurable robots (SRRs) have redundant degrees of freedom and various configurations. There are two hard problems imposed by SRR features: locomotion planning and the discovery of multiple locomotion patterns. Most of the current research focuses on solving the first problem, using evolutionary algorithms based on the philosophy of searching-for-the-best. The main problem is that the search can fall into a local optimum in the case of a complex non-linear problem. Another drawback is that the searched result lacks diversity in the behaviour space, which is inappropriate in addressing the problem of discovering multiple locomotion patterns. In this paper, we present a new strategy that evolves an SRRs controller by searching for behavioural diversity. Instead of converging on a single optimal solution, this strategy discovers a vast variety of different ways to realize robot locomotion. Optimal motion is sparse in the behaviour space, and this method can find it as a by-product through a diversity-keeping mechanism. A revised particle swarm optimization (PSO) algorithm, driven by behaviour sparseness, is implemented to evolve locomotion for a variety of configurations whose efficiency and flexibility is validated. The results show that this method can not only obtain an optimized robot controller, but also find various locomotion patterns.

CFD analysis of ducted-fan UAV based on Magnus effect

Uninhabited Aerial Vehicle(UAV) has been developed quickly for decades and a new kind of VTOL(Vertical Take-Off and Landing)UAV which is called Ducted-Fan Uninhabited Aerial Vehicle attracts more and more attention. This paper presents a new structure of the ducted-fan UAV. In this vehicle, the actuator system consists of four rotary cylinders which are symmetrically installed at bottom of inside duct. The force used for attitude stabilization is generated by the interaction between the surface of cylinder and the downwash, which is known as Magnus effect. In this paper, the aerodynamic characteristics of propeller-wing interaction for the ducted fan UAV were simulated numerically based on the Computational Fluid Dynamics (CFD) by means of sliding mesh technology.

Double closed-loop cascade control for lower limb exoskeleton with elastic actuation.

Unlike traditional rigid actuators, the significant features of Series Elastic Actuator (SEA) are stable torque control, lower output impedance, impact resistance and energy storage. Recently, SEA has been applied in many exoskeletons. In such applications, a key issue is how to realize the human-exoskeleton movement coordination. In this paper, double closed-loop cascade control for lower limb exoskeleton with SEA is proposed. This control method consists of inner SEA torque loop and outer contact force loop. Utilizing the SEA torque control with a motor velocity loop, actuation performances of SEA are analyzed. An integrated exoskeleton control system is designed, in which joint angles are calculated by internal encoders and resolvers and contact forces are gathered by external pressure sensors. The double closed-loop cascade control model is established based on the feedback signals of internal and external sensor. Movement experiments are accomplished in our prototype of lower limb exoskeleton. Preliminary results indicate the exoskeleton movements with pilot can be realized stably by utilizing this double closed-loop cascade control method. Feasibility of the SEA in our exoskeleton robot and effectiveness of the control method are verified.

A Multi-sensory Autonomous Docking Approach for a Self-reconfigurable Robot without Mechanical Guidance

The most important feature of a Self-Reconfigurable Robot (SRR) is that it is reconfigurable and self-repairing. At the centre of these capabilities is autonomous docking. One difficulty for docking is the alignment between two robots. Current strategies overcome this by integrating a mechanical guiding device within the connecting mechanism. This increases the robustness of docking but compromises the flexibility of reconfiguration. In this paper, we present a new autonomous docking strategy that can overcome the drawbacks of current approaches. The new strategy uses a novel hook-type connecting mechanism and multi-sensory guidance. The hook-type connecting mechanism is strong and rigid for reliable physical connection between the modules. The multi-sensory docking strategy, which includes visual-sensor-guided rough positioning, Hall-sensor-guided fine positioning, and the locking between moving and target modules, guarantees robust docking without sacrificing reconfigurability. The proposed strategy is verified by docking between a worm-shaped robot and one target module, and docking among three moving robots to form a T-shaped configuration. The experimental results showed that the strategy is very effective.

Gain-scheduling control of a 6-DOF single-wheeled pendulum robot based on DIT parameterization

This article presents the nonlinear dynamics and the posture stabilization control scheme for the single-wheeled pendulum robot (SWPR). Considering the maneuverability of SWPR, the steering is realized through the control for the inertia pendulum (IP) installed horizontally on the middle part of robot body. The feature of the control system modeling consists in a technique for which the posture stabilization control design is based on the parameterization of the dynamic interactions (DIT) between the lateral dynamics, the longitudinal dynamics, and the rotational dynamics. Simulation results showed the feasibility of the SWPR model and the control algorithm.

A distributed and parallel control mechanism for self-reconfiguration of modular robots using L-systems and cellular automata

For distributed self-reconfiguration of Modular Self-Reconfigurable (MSR) robots, one of the main difficulties is the contradiction between limited information of decentralized modules and well-organized global structure. This paper presents a distributed and parallel mechanism for decentralized self-reconfiguration of MSR robots. This mechanism is hybrid by combining Lindenmayer systems (L-systems) describing the topological structure as configuration target and Cellular Automata (CA) for local motion planning of individual modules. Turtle interpretations are extended to modular robotics for generating module-level predictions from global description. According to local information, independent modules make motion planning by Cellular Automata in parallel. This distributed mechanism is robust to failure of modules, scalable to varying module numbers, and convergent to predefined reconfiguration targets. Simulations and statistical results are provided for validating the proposed algorithm. We propose a distributed and parallel mechanism for self-reconfiguration of modular robots.L-systems are introduced to the distributed self-reconfiguration for a parallel system.The Cellular Automata are simplified with only two rules.This approach is convergent to target structure, robust to failure of modules and scalable to module numbers.

Unicycle Robot Stabilized by the Effect of Gyroscopic Precession and Its Control Realization Based on Centrifugal Force Compensation

This study presents a new control algorithm based on centrifugal force compensation for balancing unicycle robots, as well as for improving the systems robustness. First, the mechanical structure of the unicycle robot based on gyroscopic precession is built. Second, a new control algorithm based on centrifugal force compensation is developed, whose basic method is to adopt centrifugal force to compensate gyroscopic torque for lateral balance. Third, the effectiveness of the proposed algorithm is further simulated in the automatic dynamic analysis of mechanical systems environment. Finally, balancing and interference experiments are performed on the prototype machine to demonstrate the high effectiveness of the structure and the new control algorithm. Compared with the traditional control algorithm, the simulation and experimental results have shown that the overshoot of the system and the recovery time after interference are reduced, thereby presenting the validity of the proposed structure and control algorithm based on centrifugal force compensation.