Variable-Time-Domain Online Neighboring Optimal Trajectory Modification for Hypersonic Interceptors

The predicted impact point (PIP) of hypersonic interception changes continually; therefore the midcourse guidance law must have the ability of online trajectory optimization. In this paper, an online trajectory generation algorithm is designed based on neighboring optimal control (NOC) theory and improved indirect Radau pseudospectral method (IRPM). A trajectory optimization model is designed according to the features of operations in near space. Two-point boundary value problems (TPBVPs) are obtained based on NOC theory. The second-order linear form of transversality conditions is deduced backward to express the modifications of terminal states, costates, and flight time in terms of current state errors and terminal constraints modifications. By treating the current states and the optimal costates modifications as initial constraints and perturbations, the feedback control variables are obtained based on improved IRPM and nominal trajectory information. The simulation results show that when the changes of terminal constraints are not relatively large, this method can generate a modified trajectory effectively with high precision of terminal modifications. The design concept can provide a reference for the design of the online trajectory generation system of hypersonic vehicles

Real-Time Trajectory Generation and Control of a Semi-Omnidirectional Mobile Robot

When controlling a wheeled mobile robot with four independently steerable driving wheels, the control of the wheel coordination must be handled. Both the direction and velocity of the wheels must be coordinated to allow for proper operation of the robot. The focus of this work is on the coordination of the wheel directions. Such coordination is mostly done by solving constraint equations of the system kinematics, but when the demands on the coordination are high, it is sometimes necessary to include the steering dynamics in the coordination control. With dynamics included the complexity of the wheel coordination increases, since constraints dependent on required angle changes and current velocities must be fulfilled. By calculating the dynamic limitations in each control cycle, the steering limit for the whole wheel base within the current control cycle can be found. With use of such wheel base limit, followable and coordinated wheel trajectories can be generated online. This thesis includes the construction of a dynamic model for inclusion of the steering dynamic limitations affecting the performance the most, the construction of the online trajectory generation idea, as well as implementation and validation on the real target wheeled mobile robot platform

Online trajectory generation in an amphibious snake robot using a lamprey-like central pattern generator model

This article presents a control architecture for controlling the locomotion of an amphibious snake/lamprey robot capable of swimming and serpentine locomotion. The control architecture is based on a central pattern generator (CPG) model inspired from the neural circuits controlling locomotion in the lamprey's spinal cord. The CPG model is implemented as a system of coupled nonlinear oscillators on board of the robot. The CPG generates coordinated travelling waves in real time while being interactively modulated by a human-operator. Interesting aspects of the CPG model include (1) that it exhibits limit cycle behavior (i.e. it produces stable rhythmic patterns that are robust against perturbations), (2) that the limit cycle behavior has a closed-form solution which provides explicit control over relevant characteristics such as frequency, amplitude and wavelength of the travelling waves, and (3) that the control parameters of the CPG can be continuously and interactively modulated by a human operator to offer high maneuverability. We demonstrate how the CPG allows one to easily adjust the speed and direction of locomotion both in water and on ground while ensuring that continuous and smooth setpoints; are sent to the robot's actuated joints

Damped Harmonic Smoother for Trajectory Planning and Vibration Suppression

In this brief, a novel filter for online trajectory generation is presented. The filter can be categorized as an input smoother since it acts on the input signal by increasing its continuity level. When fed with simple signals, as, e.g., a step input, it behaves like a trajectory generator that produces harmonic motions. Moreover, it can be combined with other filters, and in particular, with smoothers having a rectangular impulse response, in order to generate (online) more complex trajectories compliant with several kinematic constraints. On the other hand, being a filter, it possesses the capability of shaping the frequency spectrum of the output signal. This possibility can be profitably exploited to suppress residual vibration by imposing that the zeros of the filter cancel the oscillatory dynamics of the plant. For this purpose, the standard harmonic filter has been generalized in order to consider not only the natural frequency but also the damping coefficient of the plant. In this manner, the so-called ``damped harmonic filter" and the related ``damped harmonic trajectory" have been defined. By means of theoretical considerations, supported by experimental tests, the novel approach has been compared with the existing methods, and the advantages of its use have been proved

Estimation and Control of Robotic Radiation-Based Processes

This dissertation presents a closed-loop control and state estimation framework for a class of distributed-parameter processes employing a moving radiant actuator. These radiation-based processes have the potential to significantly reduce the energy consumption and environmental impact of traditional industrial processes. Successful implementation of these approaches in large-scale applications requires precise control systems. This dissertation provides a comprehensive framework for: 1) integration of trajectory generation and feedback control, 2) online distributed state and parameter estimation, and 3) optimal coordination of multiple manipulated variables, so as to achieve elaborate control of these radiation-based processes for improved process quality and energy efficiency. The developed framework addresses important issues for estimation and control of processes employing a moving radiant actuator from both practical and theoretical aspects. For practical systems, an integrated motion and process control approach is first developed to compensate for disturbances by adjusting either the radiant power of the actuator or the speed of the robot end effector based on available process measurements, such as temperature distribution. The control problem is then generalized by using a 1D scanning formulation that describes common characteristics of typical radiant source actuated processes. Based on this 1D scanning formulation, a distributed state and parameter estimation scheme that incorporates a dual extended Kalman filter (DEKF) approach is developed to provide real-time process estimation. In this estimation scheme, an activating policy accompanying the moving actuator is applied in order to reduce the computational cost and compensate for observability changes caused by the actuator\u27s movement. To achieve further improvements in process quality, a static optimization and a rule-based feedback control strategy are used to coordinate multiple manipulated variables in open-loop and closed-loop manners. Finally, a distributed model predictive control (MPC) framework is developed to integrate process optimization and closed-loop coordination of manipulated variables. Simulation studies conducted on a robotic ultraviolet (UV) paint curing process show that the developed estimation and control framework for radiant source actuated processes provide improved process quality and energy efficiency by adaptively compensating for disturbances and optimally coordinating multiple manipulated variables