Research on Nonlinear Coupled Tracking Controller for Double Pendulum Gantry Cranes With Load Hoisting/lowering

Gantry cranes, which have attracted extensive attention, are mostly simplified as nonlinear single pendulum systems without load hoisting/lowering. However, in fact, due to the existence of the hook, gantry cranes produce double pendulum swing. With an extra underactuated degree of freedom, the anti-swing control of the double pendulum gantry cranes becomes more difficult than that of single pendulum gantry cranes, especially when load hoisting/lowering is considered simultaneously. Moreover, large swings, which lead to problems such as inaccurate positioning and low transportation efficiency, may be caused by double pendulum gantry cranes with load hoisting/lowering. In this paper, a nonlinear coupled tracking anti-swing controller is proposed to solve these problems. In this controller, a smooth tracking trajectory is introduced to ensure the stable start and run of the trolley, and a coupled signal is constructed to eliminate the residual swing angles of gantry crane system. The system stability is analyzed by using Lyapunov method and Barbarat theorem. Theoretical derivation, simulation and experimental results show that the proposed controller has excellent control performance, specifically, not only does it ensure accurate positioning of the load, but also it suppresses and eliminates the hook/load swing angle effectively. The proposed controller can still achieve good control effects and has strong robustness under the condition of changing the load mass, trolley target displacement, system initial swing angles and adding external disturbance.

The Right to Silence and the Pendulum Swing: Variations in Canadian and Scottish Criminal Law

The right to silence is afforded to suspects in criminal cases as part of a number constitutional protections contained within Canadian law through the Charter of Rights and Freedoms. It is closely linked to other such rights, including the right to counsel, the right against self-incrimination and the presumption of innocence. Moreover, in some cases, the denial of this right has resulted in convictions in error through false confessions and wrongful convictions. Decisions by the Supreme Court in Canada in recent times can be viewed as a slow encroachment onto individual Charter rights in favour of the needs of law enforcement. In Scotland, until recently, while afforded a right to silence suspects could still be questioned for up to six hours without a lawyer present. While other measures existed to protect an individual’s right to a fair trial, such practices were out of step with the European Convention on Human Rights Article 6(1) right to a fair trial. In the decision in Cadder v HMA, greater protections to suspects were introduced regarding the right to silence and the right to counsel, and the Criminal Justice (Scotland) Act 2016 later consolidated the relevant law on this matter. The focus of this paper will be to examine how the right to silence in both Canadian and Scottish law has evolved through statute and case law and the implications of this for law enforcement practices, the protection of rights and the safety of convictions.

Determining the degree of pulse absorption of air blast wave by spaced material systems

The paper presents the results of a study to determine the degree of attenuation of a detonation wave pulse generated by a spherical ceresin-phlegmatized hexogen charge, by spaced material systems. The systems were mounted on a ballistic pendulum and the amount of energy absorbed was determined based on the change in pendulum swing. The spaced panels with absorbing elements, simulated the flat bottom of a vehicle exposed to a single blast.

Comparing Action Aggregation Strategies in Deep Reinforcement Learning with Continuous Action

Deep Reinforcement Learning has been very promising in learning continuous control policies. For complex tasks, Reinforcement Learning with minimal human intervention is still a challenge. This article proposes a study to improve performance and to stabilize the learning curve using the ensemble learning methods. Learning a combined parameterized action function using multiple agents in a single environment, while searching for a better way to learn, regardless of the quality of the parametrization. The action ensemble methods were applied in three environments: pendulum swing-up, cart pole and half cheetah. Their results demonstrated that action ensemble can improve performance with respect to the grid search technique. This article also presents as contribution the comparison of the effectiveness of the aggregation techniques, the analysis considers the use of the separate or the combined policies during training. The latter presents better learning results when used with the data center aggregation strategy.