A control device includes a first controller configured to generate a first operation amount for the device on the basis of an output fed back from the device and a target value, a predicted output generator including a learned model which is machine learned so as to generate a predicted output from the device on the basis of the output fed back from the device and the first operation amount, a second controller configured to generate a second operation amount for the device on the basis of the predicted output and the target value, an integrated operation amount generator configured to generate an integrated operation amount which is an operation amount for the device on the basis of the first operation amount and the second operation amount.

A control device includes a first controller configured to generate a first operation amount for the device on the basis of an output fed back from the device and a target value, a predicted output generator including a learned model which is machine learned so as to generate a predicted output from the device on the basis of the output fed back from the device and the first operation amount, a second controller configured to generate a second operation amount for the device on the basis of the predicted output and the target value, an integrated operation amount generator configured to generate an integrated operation amount which is an operation amount for the device on the basis of the first operation amount and the second operation amount.

A smart electronic power steering system and method for a retrofitted electric vehicle are provided. In one embodiment, an electronic power steering system of an electric vehicle is provided. The electronic power steering system comprises one or more computer-readable storage media, a processing system operatively coupled with the one or more computer-readable storage media, and program instructions stored on the one or more computer-readable storage media that, based on being read and executed by the processing system, direct the electronic power steering system to receive a maximum pressure value and a flow rate from the electric vehicle; convert the maximum pressure value and the flow rate into one or more power steering component settings; and send the one or more power steering component settings to one or more power steering components of the electric vehicle.

A smart electronic power steering system and method for a retrofitted electric vehicle are provided. In one embodiment, an electronic power steering system of an electric vehicle is provided. The electronic power steering system comprises one or more computer-readable storage media, a processing system operatively coupled with the one or more computer-readable storage media, and program instructions stored on the one or more computer-readable storage media that, based on being read and executed by the processing system, direct the electronic power steering system to receive a maximum pressure value and a flow rate from the electric vehicle; convert the maximum pressure value and the flow rate into one or more power steering component settings; and send the one or more power steering component settings to one or more power steering components of the electric vehicle.

A method for identifying underperforming agents in a multi-agent cooperative system includes receiving information relating to the performance of each agent in the multi-agent system, calculating an estimated extracted resource value of each agent based on the received information, comparing the estimated extracted resource value of each agent to a threshold value, calculating a performance index based on the comparison and identifying an agent as an under-performing agent based on the performance index. A system for identifying under-performing agents in a plurality of agents in a multi-agent cooperative system includes a performance analyzing processor, a communications port for receiving state information for each agent and control information for each agent, a classifier for identifying a subset of agents in the plurality of agents that are performance comparable and an optimizer configured to identify an under-performing agent of performance comparable agents and generate updated control information for the identified under-performing agent.

A method for identifying underperforming agents in a multi-agent cooperative system includes receiving information relating to the performance of each agent in the multi-agent system, calculating an estimated extracted resource value of each agent based on the received information, comparing the estimated extracted resource value of each agent to a threshold value, calculating a performance index based on the comparison and identifying an agent as an under-performing agent based on the performance index. A system for identifying under-performing agents in a plurality of agents in a multi-agent cooperative system includes a performance analyzing processor, a communications port for receiving state information for each agent and control information for each agent, a classifier for identifying a subset of agents in the plurality of agents that are performance comparable and an optimizer configured to identify an under-performing agent of performance comparable agents and generate updated control information for the identified under-performing agent.

An example servo control system includes one or more components configured to be actuated for movement, a system controller including one or more processors for receiving feedback of the movement of the one or more components and for using the feedback within a control loop to cause an actuator to reduce error of the movement of the one or more components, and a tuned mass damper (TMD) physically connected to the one or more components. Parameters of the TMD are selected to add phase margin at a crossover frequency of the servo control system, and the TMD includes a mass coupled to the one or more components, a damper connected between the mass and the one or more components, and a spring component connected between the mass and the one or more components.

An example servo control system includes one or more components configured to be actuated for movement, a system controller including one or more processors for receiving feedback of the movement of the one or more components and for using the feedback within a control loop to cause an actuator to reduce error of the movement of the one or more components, and a tuned mass damper (TMD) physically connected to the one or more components. Parameters of the TMD are selected to add phase margin at a crossover frequency of the servo control system, and the TMD includes a mass coupled to the one or more components, a damper connected between the mass and the one or more components, and a spring component connected between the mass and the one or more components.

The invention provides a parameters tuning method of energy storage system and the energy storage system, and the method comprises the following steps: using PID control module to construct a closed-loop control subsystem of energy dispatching; acquiring PID initial parameters according to the energy dispatching model of the energy storage system; setting an adaptive model in the PID control module, and processing the PID initial parameters through the adaptive model to obtain PID adjusted and modified parameters; using the PID adjusted and modified parameters to modify the PID parameters and get the PID tuning parameters. What's more, the system comprises a battery module, a bidirectional converter device, an energy dispatching subsystem and a closed-loop control subsystem; and the closed-loop control subsystem is provided with a PID control module, and the PID control module is provided with an adaptive model for realizing the parameters tuning method of the energy storage system. In addition, the invention can realize the parameters tuning of the energy storage system, so that the control can adapt to the characteristics of the distributed energy storage system, deal with the uncertainty to achieve better control effect, and reduce the failure rate and maintenance cost.

The invention provides a parameters tuning method of energy storage system and the energy storage system, and the method comprises the following steps: using PID control module to construct a closed-loop control subsystem of energy dispatching; acquiring PID initial parameters according to the energy dispatching model of the energy storage system; setting an adaptive model in the PID control module, and processing the PID initial parameters through the adaptive model to obtain PID adjusted and modified parameters; using the PID adjusted and modified parameters to modify the PID parameters and get the PID tuning parameters. What's more, the system comprises a battery module, a bidirectional converter device, an energy dispatching subsystem and a closed-loop control subsystem; and the closed-loop control subsystem is provided with a PID control module, and the PID control module is provided with an adaptive model for realizing the parameters tuning method of the energy storage system. In addition, the invention can realize the parameters tuning of the energy storage system, so that the control can adapt to the characteristics of the distributed energy storage system, deal with the uncertainty to achieve better control effect, and reduce the failure rate and maintenance cost.